{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,11,4]],"date-time":"2026-11-04T00:02:24Z","timestamp":1793750544576,"version":"4.6.1"},"reference-count":236,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2025,6,19]],"date-time":"2025-06-19T00:00:00Z","timestamp":1750291200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,6,19]],"date-time":"2025-06-19T00:00:00Z","timestamp":1750291200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Funct Integr Genomics"],"published-print":{"date-parts":[[2025,12]]},"DOI":"10.1007\/s10142-025-01645-7","type":"journal-article","created":{"date-parts":[[2025,6,19]],"date-time":"2025-06-19T15:28:50Z","timestamp":1750346930000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":33,"title":["Multi-omics approaches: transforming the landscape of natural product isolation"],"prefix":"10.1007","volume":"25","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4372-5899","authenticated-orcid":false,"given":"Soumitra","family":"Sahana","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jyotirmay","family":"Sarkar","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sourav","family":"Mandal","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Indranil","family":"Chatterjee","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Susmita","family":"Dhar","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Samaresh","family":"Datta","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sumanta","family":"Mondal","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2025,6,19]]},"reference":[{"issue":"9","key":"1645_CR1","doi-asserted-by":"crossref","first-page":"1555","DOI":"10.3390\/ijms17091555","volume":"17","author":"A Tebani","year":"2016","unstructured":"Tebani A et al (2016) Omics-based strategies in precision medicine: toward a paradigm shift in inborn errors of metabolism investigations. Int J Mol Sci 17(9):1555","journal-title":"Int J Mol Sci"},{"issue":"1","key":"1645_CR2","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1186\/s13059-017-1215-1","volume":"18","author":"Y Hasin","year":"2017","unstructured":"Hasin Y, Seldin M, Lusis A (2017a) Multi-omics approaches to disease. Genome Biol 18(1):1\u201315","journal-title":"Genome Biol"},{"issue":"9","key":"1645_CR3","doi-asserted-by":"crossref","first-page":"3777","DOI":"10.1093\/nar\/gkr1255","volume":"40","author":"F Begum","year":"2012","unstructured":"Begum F et al (2012) Comprehensive literature review and statistical considerations for GWAS meta-analysis. Nucleic Acids Res 40(9):3777\u20133784","journal-title":"Nucleic Acids Res"},{"issue":"13","key":"1645_CR4","doi-asserted-by":"crossref","first-page":"4181","DOI":"10.1093\/nar\/gkp552","volume":"37","author":"T LaFramboise","year":"2009","unstructured":"LaFramboise T (2009) Single nucleotide polymorphism arrays: a decade of biological, computational and technological advances. Nucleic Acids Res 37(13):4181\u20134193","journal-title":"Nucleic Acids Res"},{"key":"1645_CR5","doi-asserted-by":"crossref","unstructured":"Vailati-Riboni M, Palombo V, and Loor JJ. 2017 What are omics sciences? Periparturient diseases of dairy cows: a systems biology approach 1\u20137","DOI":"10.1007\/978-3-319-43033-1_1"},{"issue":"5","key":"1645_CR6","doi-asserted-by":"crossref","first-page":"399","DOI":"10.1021\/pr020299f","volume":"1","author":"L Hood","year":"2002","unstructured":"Hood L (2002) A personal view of molecular technology and how it has changed biology. J Proteome Res 1(5):399\u2013409","journal-title":"J Proteome Res"},{"issue":"9","key":"1645_CR7","doi-asserted-by":"crossref","first-page":"373","DOI":"10.1016\/S0167-7799(98)01214-1","volume":"16","author":"SG Oliver","year":"1998","unstructured":"Oliver SG et al (1998) Systematic functional analysis of the yeast genome. Trends Biotechnol 16(9):373\u2013378","journal-title":"Trends Biotechnol"},{"issue":"5","key":"1645_CR8","doi-asserted-by":"crossref","first-page":"299","DOI":"10.1038\/nrg.2018.4","volume":"19","author":"KJ Karczewski","year":"2018","unstructured":"Karczewski KJ, Snyder MP (2018) Integrative omics for health and disease. Nat Rev Genet 19(5):299\u2013310","journal-title":"Nat Rev Genet"},{"key":"1645_CR9","doi-asserted-by":"crossref","unstructured":"Stagljar I. 2016 The power of OMICs. Elsevier. 607\u2013609","DOI":"10.1016\/j.bbrc.2016.09.095"},{"issue":"1","key":"1645_CR10","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.jgeb.2018.01.006","volume":"16","author":"NC Mohana","year":"2018","unstructured":"Mohana NC et al (2018) Omics based approach for biodiscovery of microbial natural products in antibiotic resistance era. J Genet Eng Biotech 16(1):1\u20138","journal-title":"J Genet Eng Biotech"},{"issue":"6","key":"1645_CR11","doi-asserted-by":"crossref","first-page":"855","DOI":"10.1039\/C9NP00004F","volume":"36","author":"J-L Wolfender","year":"2019","unstructured":"Wolfender J-L et al (2019) Innovative omics-based approaches for prioritisation and targeted isolation of natural products\u2013new strategies for drug discovery. Nat Prod Rep 36(6):855\u2013868","journal-title":"Nat Prod Rep"},{"key":"1645_CR12","doi-asserted-by":"crossref","first-page":"111833","DOI":"10.1016\/j.biopha.2021.111833","volume":"141","author":"H-W Zhang","year":"2021","unstructured":"Zhang H-W et al (2021) Application of omics-and multi-omics-based techniques for natural product target discovery. Biomed Pharmacother 141:111833","journal-title":"Biomed Pharmacother"},{"issue":"1","key":"1645_CR13","doi-asserted-by":"crossref","first-page":"74","DOI":"10.1002\/elps.200900410","volume":"31","author":"E Oh","year":"2010","unstructured":"Oh E et al (2010) Growing trend of CE at the omics level: the frontier of systems biology. Electrophoresis 31(1):74\u201392","journal-title":"Electrophoresis"},{"issue":"6","key":"1645_CR14","doi-asserted-by":"crossref","first-page":"768","DOI":"10.1039\/c3np70127a","volume":"31","author":"D Krug","year":"2014","unstructured":"Krug D, M\u00fcller R (2014) Secondary metabolomics: the impact of mass spectrometry-based approaches on the discovery and characterization of microbial natural products. Nat Prod Rep 31(6):768\u2013783","journal-title":"Nat Prod Rep"},{"issue":"4","key":"1645_CR15","doi-asserted-by":"crossref","first-page":"491","DOI":"10.1093\/bib\/bbs043","volume":"14","author":"EL Leung","year":"2013","unstructured":"Leung EL et al (2013) Network-based drug discovery by integrating systems biology and computational technologies. Brief Bioinform 14(4):491\u2013505","journal-title":"Brief Bioinform"},{"key":"1645_CR16","first-page":"199","volume":"99","author":"M Nett","year":"2014","unstructured":"Nett M (2014) Genome mining: concept and strategies for natural product discovery. Prog Chem Org Nat Prod 99:199\u2013245","journal-title":"Prog Chem Org Nat Prod"},{"issue":"6","key":"1645_CR17","doi-asserted-by":"crossref","first-page":"1260","DOI":"10.1021\/acschembio.9b00223","volume":"14","author":"D Acharya","year":"2019","unstructured":"Acharya D et al (2019) Omics technologies to understand activation of a biosynthetic gene cluster in Micromonospora sp WMMB235: Deciphering keyicin biosynthesis. ACS Chem Biol 14(6):1260\u20131270","journal-title":"ACS Chem Biol"},{"key":"1645_CR18","doi-asserted-by":"crossref","first-page":"1031","DOI":"10.3389\/fpls.2015.01031","volume":"6","author":"N Dhar","year":"2015","unstructured":"Dhar N et al (2015) A decade of molecular understanding of withanolide biosynthesis and in vitro studies in Withania somnifera (L) Dunal: prospects and perspectives for pathway engineering. Front Plant Sci 6:1031","journal-title":"Front Plant Sci"},{"issue":"1","key":"1645_CR19","doi-asserted-by":"crossref","first-page":"43","DOI":"10.1016\/j.molp.2022.09.007","volume":"16","author":"S Shen","year":"2023","unstructured":"Shen S et al (2023) Metabolomics-centered mining of plant metabolic diversity and function: Past decade and future perspectives. Mol Plant 16(1):43\u201363","journal-title":"Mol Plant"},{"issue":"11","key":"1645_CR20","doi-asserted-by":"crossref","first-page":"2041","DOI":"10.1039\/D1NP00036E","volume":"38","author":"LK Caesar","year":"2021","unstructured":"Caesar LK et al (2021) Metabolomics and genomics in natural products research: complementary tools for targeting new chemical entities. Nat Prod Rep 38(11):2041\u20132065","journal-title":"Nat Prod Rep"},{"issue":"1","key":"1645_CR21","doi-asserted-by":"crossref","first-page":"586","DOI":"10.1016\/j.synbio.2021.12.012","volume":"7","author":"MH Hussain","year":"2022","unstructured":"Hussain MH et al (2022) Multiscale engineering of microbial cell factories: A step forward towards sustainable natural products industry. Synth Syst Biotechnol 7(1):586\u2013601","journal-title":"Synth Syst Biotechnol"},{"issue":"3","key":"1645_CR22","doi-asserted-by":"crossref","first-page":"200","DOI":"10.1038\/s41573-020-00114-z","volume":"20","author":"AG Atanasov","year":"2021","unstructured":"Atanasov AG et al (2021) Natural products in drug discovery: advances and opportunities. Nat Rev Drug Discovery 20(3):200\u2013216","journal-title":"Nat Rev Drug Discovery"},{"issue":"12","key":"1645_CR23","doi-asserted-by":"crossref","first-page":"1813","DOI":"10.1021\/np050255w","volume":"68","author":"S Rochfort","year":"2005","unstructured":"Rochfort S (2005) Metabolomics reviewed: a new \u201comics\u201d platform technology for systems biology and implications for natural products research. J Nat Prod 68(12):1813\u20131820","journal-title":"J Nat Prod"},{"issue":"37","key":"1645_CR24","doi-asserted-by":"crossref","first-page":"4221","DOI":"10.2174\/0929867323666160926150617","volume":"23","author":"B Karahalil","year":"2016","unstructured":"Karahalil B (2016) Overview of systems biology and omics technologies. Curr Med Chem 23(37):4221\u20134230","journal-title":"Curr Med Chem"},{"issue":"1","key":"1645_CR25","doi-asserted-by":"crossref","first-page":"7","DOI":"10.1039\/D2NP90047E","volume":"40","author":"RJ Cox","year":"2023","unstructured":"Cox RJ, Gulder TA (2023) Introduction to engineering the biosynthesis of fungal natural products. Nat Prod Rep 40(1):7\u20138","journal-title":"Nat Prod Rep"},{"key":"1645_CR26","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1186\/s13059-021-02536-3","volume":"22","author":"BM Perez-Sepulveda","year":"2021","unstructured":"Perez-Sepulveda BM et al (2021) An accessible, efficient and global approach for the large-scale sequencing of bacterial genomes. Genome Biol 22:1\u201318","journal-title":"Genome Biol"},{"issue":"1","key":"1645_CR27","doi-asserted-by":"crossref","first-page":"5","DOI":"10.1186\/s40793-024-00659-1","volume":"20","author":"E Dieppa-Col\u00f3n","year":"2025","unstructured":"Dieppa-Col\u00f3n E et al (2025) Prophage-DB: A comprehensive database to explore diversity, distribution, and ecology of prophages. Environmental Microbiome 20(1):5","journal-title":"Environmental Microbiome"},{"issue":"1","key":"1645_CR28","doi-asserted-by":"crossref","first-page":"3864","DOI":"10.1038\/s41467-021-24133-5","volume":"12","author":"K Scherlach","year":"2021","unstructured":"Scherlach K, Hertweck C (2021) Mining and unearthing hidden biosynthetic potential. Nat Commun 12(1):3864","journal-title":"Nat Commun"},{"issue":"6","key":"1645_CR29","doi-asserted-by":"crossref","first-page":"1100","DOI":"10.1039\/D0NP00055H","volume":"38","author":"D Prihoda","year":"2021","unstructured":"Prihoda D et al (2021) The application potential of machine learning and genomics for understanding natural product diversity, chemistry, and therapeutic translatability. Nat Prod Rep 38(6):1100\u20131108","journal-title":"Nat Prod Rep"},{"issue":"1","key":"1645_CR30","doi-asserted-by":"crossref","first-page":"243","DOI":"10.1186\/s12870-022-03637-2","volume":"22","author":"X Zhao","year":"2022","unstructured":"Zhao X et al (2022) Transcriptome and metabolome reveal the accumulation of secondary metabolites in different varieties of Cinnamomum longepaniculatum. BMC Plant Biol 22(1):243","journal-title":"BMC Plant Biol"},{"issue":"52","key":"1645_CR31","first-page":"E11121","volume":"114","author":"GC Amos","year":"2017","unstructured":"Amos GC et al (2017) Comparative transcriptomics as a guide to natural product discovery and biosynthetic gene cluster functionality. Proc Natl Acad Sci 114(52):E11121\u2013E11130","journal-title":"Proc Natl Acad Sci"},{"issue":"4","key":"1645_CR32","doi-asserted-by":"crossref","first-page":"499","DOI":"10.1080\/17460441.2020.1722636","volume":"15","author":"KA Stuart","year":"2020","unstructured":"Stuart KA et al (2020) Metabolomic tools used in marine natural product drug discovery. Expert Opin Drug Discov 15(4):499\u2013522","journal-title":"Expert Opin Drug Discov"},{"issue":"10","key":"1645_CR33","doi-asserted-by":"crossref","first-page":"931","DOI":"10.1080\/14789450.2017.1377613","volume":"14","author":"SD Robinson","year":"2017","unstructured":"Robinson SD et al (2017) Venom peptides as therapeutics: advances, challenges and the future of venom-peptide discovery. Expert Rev Proteomics 14(10):931\u2013939","journal-title":"Expert Rev Proteomics"},{"issue":"10","key":"1645_CR34","doi-asserted-by":"crossref","first-page":"800","DOI":"10.1111\/j.1744-7909.2011.01073.x","volume":"53","author":"NN Ono","year":"2011","unstructured":"Ono NN et al (2011) Exploring the transcriptome landscape of pomegranate fruit peel for natural product biosynthetic gene and SSR marker discovery F. J Integr Plant Biol 53(10):800\u2013813","journal-title":"J Integr Plant Biol"},{"issue":"16","key":"1645_CR35","doi-asserted-by":"crossref","first-page":"3319","DOI":"10.2174\/0115701808287654240126112003","volume":"21","author":"M Chauhan","year":"2024","unstructured":"Chauhan M et al (2024) A comprehensive review of the advancement in omic technologies in the field of drug discovery and development. Lett Drug des Discovery 21(16):3319\u20133331","journal-title":"Lett Drug des Discovery"},{"issue":"19\u201320","key":"1645_CR36","doi-asserted-by":"crossref","first-page":"6487","DOI":"10.1007\/s00018-021-03918-3","volume":"78","author":"AS Marchev","year":"2021","unstructured":"Marchev AS et al (2021) Metabolomics and health: From nutritional crops and plant-based pharmaceuticals to profiling of human biofluids. Cell Mol Life Sci 78(19\u201320):6487\u20136503","journal-title":"Cell Mol Life Sci"},{"key":"1645_CR37","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.biotno.2023.12.006","volume":"5","author":"V Verma","year":"2024","unstructured":"Verma V et al (2024) Incorporating omics-based tools into endophytic fungal research. Biotechnology Notes 5:1\u20137","journal-title":"Biotechnology Notes"},{"issue":"1","key":"1645_CR38","doi-asserted-by":"crossref","first-page":"13","DOI":"10.1016\/j.gpb.2022.06.006","volume":"21","author":"R Wang","year":"2023","unstructured":"Wang R et al (2023) Integration of computational analysis and spatial transcriptomics in single-cell studies. Genomics Proteomics Bioinformatics 21(1):13\u201323","journal-title":"Genomics Proteomics Bioinformatics"},{"issue":"1","key":"1645_CR39","doi-asserted-by":"crossref","first-page":"330","DOI":"10.1186\/s12967-023-04150-2","volume":"21","author":"J Du","year":"2023","unstructured":"Du J et al (2023) Advances in spatial transcriptomics and related data analysis strategies. J Transl Med 21(1):330","journal-title":"J Transl Med"},{"issue":"11","key":"1645_CR40","doi-asserted-by":"crossref","first-page":"gix092","DOI":"10.1093\/gigascience\/gix092","volume":"6","author":"F Perez-Sanz","year":"2017","unstructured":"Perez-Sanz F, Navarro PJ, Egea-Cortines M (2017) Plant phenomics: An overview of image acquisition technologies and image data analysis algorithms. GigaScience 6(11):gix092","journal-title":"GigaScience"},{"issue":"1","key":"1645_CR41","doi-asserted-by":"crossref","first-page":"104","DOI":"10.1007\/s11676-024-01752-4","volume":"35","author":"Y Shu","year":"2024","unstructured":"Shu Y et al (2024) Over-expression of the Iris laevigata cold-resistance gene MYB97 improves photosynthetic capacity and photoprotection in tobacco (Nicotiana tabacum). Journal of Forestry Research 35(1):104","journal-title":"Journal of Forestry Research"},{"issue":"5","key":"1645_CR42","doi-asserted-by":"crossref","first-page":"308","DOI":"10.3390\/md21050308","volume":"21","author":"SP Gaud\u00eancio","year":"2023","unstructured":"Gaud\u00eancio SP et al (2023) Advanced methods for natural products discovery: bioactivity screening, dereplication, metabolomics profiling, genomic sequencing, databases and informatic tools, and structure elucidation. Mar Drugs 21(5):308","journal-title":"Mar Drugs"},{"issue":"10","key":"1645_CR43","doi-asserted-by":"crossref","first-page":"2644","DOI":"10.1021\/acschembio.7b00413","volume":"12","author":"F Olivon","year":"2017","unstructured":"Olivon F et al (2017) Bioactive natural products prioritization using massive multi-informational molecular networks. ACS Chem Biol 12(10):2644\u20132651","journal-title":"ACS Chem Biol"},{"issue":"39","key":"1645_CR44","doi-asserted-by":"crossref","first-page":"11999","DOI":"10.1073\/pnas.1507743112","volume":"112","author":"KL Kurita","year":"2015","unstructured":"Kurita KL, Glassey E, Linington RG (2015) Integration of high-content screening and untargeted metabolomics for comprehensive functional annotation of natural product libraries. Proc Natl Acad Sci 112(39):11999\u201312004","journal-title":"Proc Natl Acad Sci"},{"issue":"1","key":"1645_CR45","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1080\/09168451.2018.1533804","volume":"83","author":"M Yoshida","year":"2019","unstructured":"Yoshida M (2019) Recent advances in target identification of bioactive natural products. Biosci Biotechnol Biochem 83(1):1\u20139","journal-title":"Biosci Biotechnol Biochem"},{"issue":"8","key":"1645_CR46","doi-asserted-by":"crossref","first-page":"759","DOI":"10.1080\/17460441.2016.1195365","volume":"11","author":"M Cuperlovic-Culf","year":"2016","unstructured":"Cuperlovic-Culf M, Culf A (2016) Applied metabolomics in drug discovery. Expert Opin Drug Discov 11(8):759\u2013770","journal-title":"Expert Opin Drug Discov"},{"issue":"2","key":"1645_CR47","doi-asserted-by":"crossref","first-page":"504","DOI":"10.1002\/med.21444","volume":"38","author":"M Isgut","year":"2018","unstructured":"Isgut M et al (2018) Application of combination high-throughput phenotypic screening and target identification methods for the discovery of natural product-based combination drugs. Med Res Rev 38(2):504\u2013524","journal-title":"Med Res Rev"},{"issue":"1","key":"1645_CR48","doi-asserted-by":"crossref","first-page":"37","DOI":"10.3390\/metabo10010037","volume":"10","author":"MA Salem","year":"2020","unstructured":"Salem MA et al (2020) Metabolomics in the context of plant natural products research: From sample preparation to metabolite analysis. Metabolites 10(1):37","journal-title":"Metabolites"},{"issue":"1","key":"1645_CR49","doi-asserted-by":"crossref","first-page":"371","DOI":"10.1073\/pnas.1901493116","volume":"117","author":"NJ Merwin","year":"2020","unstructured":"Merwin NJ et al (2020) DeepRiPP integrates multiomics data to automate discovery of novel ribosomally synthesized natural products. Proc Natl Acad Sci 117(1):371\u2013380","journal-title":"Proc Natl Acad Sci"},{"issue":"7","key":"1645_CR50","doi-asserted-by":"crossref","first-page":"694","DOI":"10.1039\/C7NP00019G","volume":"34","author":"GD Wright","year":"2017","unstructured":"Wright GD (2017) Opportunities for natural products in 21st century antibiotic discovery. Nat Prod Rep 34(7):694\u2013701","journal-title":"Nat Prod Rep"},{"issue":"5","key":"1645_CR51","doi-asserted-by":"crossref","first-page":"475","DOI":"10.1080\/17460441.2017.1303478","volume":"12","author":"MM Zhang","year":"2017","unstructured":"Zhang MM et al (2017) Using natural products for drug discovery: the impact of the genomics era. Expert Opin Drug Discov 12(5):475\u2013487","journal-title":"Expert Opin Drug Discov"},{"key":"1645_CR52","first-page":"3460","volume":"12","author":"DG Cox","year":"1840","unstructured":"Cox DG et al (1840) 2014 The utility of metabolomics in natural product and biomarker characterization. Biochim Biophys Acta (BBA)-Gen Subj. 12:3460\u20133474","journal-title":"Biochim Biophys Acta (BBA)-Gen Subj."},{"issue":"1","key":"1645_CR53","doi-asserted-by":"crossref","first-page":"1051","DOI":"10.1038\/s41598-020-58046-y","volume":"10","author":"DP Demarque","year":"2020","unstructured":"Demarque DP et al (2020) Mass spectrometry-based metabolomics approach in the isolation of bioactive natural products. Sci Rep 10(1):1051","journal-title":"Sci Rep"},{"key":"1645_CR54","doi-asserted-by":"crossref","unstructured":"Tawfike AF, Viegelmann C, and Edrada-Ebel R. 2013 Metabolomics and dereplication strategies in natural products. Metabolomics tools for natural product discovery: methods and protocols. 227\u2013244","DOI":"10.1007\/978-1-62703-577-4_17"},{"issue":"10","key":"1645_CR55","doi-asserted-by":"crossref","first-page":"526","DOI":"10.3390\/md21100526","volume":"21","author":"VR Mart\u00edn-Arag\u00f3n","year":"2023","unstructured":"Mart\u00edn-Arag\u00f3n VR et al (2023) Induction of new aromatic polyketides from the marine actinobacterium Streptomyces griseorubiginosus through an OSMAC approach. Mar Drugs 21(10):526","journal-title":"Mar Drugs"},{"key":"1645_CR56","doi-asserted-by":"crossref","first-page":"1177123","DOI":"10.3389\/fmicb.2023.1177123","volume":"14","author":"M Ren","year":"2023","unstructured":"Ren M et al (2023) Discovery and excavation of lichen bioactive natural products. Front Microbiol 14:1177123","journal-title":"Front Microbiol"},{"issue":"16","key":"1645_CR57","doi-asserted-by":"crossref","first-page":"9055","DOI":"10.3390\/ijms22169055","volume":"22","author":"F Palma Esposito","year":"2021","unstructured":"Palma Esposito F et al (2021) Combining OSMAC approach and untargeted metabolomics for the identification of new glycolipids with potent antiviral activity produced by a marine Rhodococcus. Int J Mol Sci 22(16):9055","journal-title":"Int J Mol Sci"},{"issue":"2","key":"1645_CR58","doi-asserted-by":"crossref","first-page":"193","DOI":"10.3390\/biom11020193","volume":"11","author":"J Schwarz","year":"2021","unstructured":"Schwarz J et al (2021) Triaging of culture conditions for enhanced secondary metabolite diversity from different bacteria. Biomolecules 11(2):193","journal-title":"Biomolecules"},{"key":"1645_CR59","doi-asserted-by":"crossref","unstructured":"Lenz C, and Dihazi H. 2016 Introduction to proteomics technologies.Stat Anal Proteomics. 3\u201327","DOI":"10.1007\/978-1-4939-3106-4_1"},{"issue":"15","key":"1645_CR60","doi-asserted-by":"crossref","first-page":"2680","DOI":"10.1002\/anie.200905352","volume":"49","author":"T B\u00f6ttcher","year":"2010","unstructured":"B\u00f6ttcher T, Pitscheider M, Sieber SA (2010) Natural products and their biological targets: proteomic and metabolomic labeling strategies. Angew Chem Int Ed 49(15):2680\u20132698","journal-title":"Angew Chem Int Ed"},{"issue":"1","key":"1645_CR61","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1080\/21553769.2017.1279573","volume":"10","author":"MW Mumtaz","year":"2017","unstructured":"Mumtaz MW et al (2017) An overview of recent developments in metabolomics and proteomics\u2013phytotherapic research perspectives. Front Life Sci 10(1):1\u201337","journal-title":"Front Life Sci"},{"issue":"45","key":"1645_CR62","doi-asserted-by":"crossref","first-page":"27950","DOI":"10.1039\/D1RA04283A","volume":"11","author":"S Bhukta","year":"2021","unstructured":"Bhukta S, Gopinath P, Dandela R (2021) Target identification of anticancer natural products using a chemical proteomics approach. RSC Adv 11(45):27950\u201327964","journal-title":"RSC Adv"},{"issue":"3","key":"1645_CR63","doi-asserted-by":"crossref","first-page":"518","DOI":"10.1111\/tpj.13571","volume":"91","author":"FY Zhu","year":"2017","unstructured":"Zhu FY et al (2017) Proteogenomic analysis reveals alternative splicing and translation as part of the abscisic acid response in Arabidopsis seedlings. Plant J 91(3):518\u2013533","journal-title":"Plant J"},{"issue":"6","key":"1645_CR64","doi-asserted-by":"crossref","first-page":"959","DOI":"10.1074\/mcp.MR117.000024","volume":"16","author":"KV Ruggles","year":"2017","unstructured":"Ruggles KV et al (2017) Methods, tools and current perspectives in proteogenomics. Mol Cell Proteomics 16(6):959\u2013981","journal-title":"Mol Cell Proteomics"},{"issue":"11","key":"1645_CR65","doi-asserted-by":"crossref","first-page":"1430","DOI":"10.3390\/plants11111430","volume":"11","author":"MA Ullah","year":"2022","unstructured":"Ullah MA et al (2022) A review of integrative omic approaches for understanding rice salt response mechanisms. Plants 11(11):1430","journal-title":"Plants"},{"issue":"10","key":"1645_CR66","doi-asserted-by":"crossref","first-page":"1800235","DOI":"10.1002\/pmic.201800235","volume":"19","author":"TY Low","year":"2019","unstructured":"Low TY et al (2019) Connecting Proteomics to Next-Generation Sequencing: Proteogenomics and Its Current Applications in Biology. Proteomics 19(10):1800235","journal-title":"Proteomics"},{"issue":"1","key":"1645_CR67","doi-asserted-by":"crossref","first-page":"351","DOI":"10.1002\/jssc.201700709","volume":"41","author":"T Hu","year":"2018","unstructured":"Hu T, Zhang JL (2018) Mass-spectrometry-based lipidomics. J Sep Sci 41(1):351\u2013372","journal-title":"J Sep Sci"},{"key":"1645_CR68","doi-asserted-by":"crossref","unstructured":"Sethi S, et al., 2017 Lipidomics, biomarkers, and schizophrenia: a current perspective. Metabolomics: From Fundamentals to Clinical Applications. 265\u2013290","DOI":"10.1007\/978-3-319-47656-8_11"},{"issue":"4","key":"1645_CR69","doi-asserted-by":"crossref","first-page":"241","DOI":"10.3390\/metabo11040241","volume":"11","author":"AK Sutliff","year":"2021","unstructured":"Sutliff AK et al (2021) Lipidomics-based comparison of molecular compositions of green, yellow, and red bell peppers. Metabolites 11(4):241","journal-title":"Metabolites"},{"issue":"11","key":"1645_CR70","doi-asserted-by":"crossref","first-page":"1395","DOI":"10.1039\/D0NP00059K","volume":"37","author":"SE Motika","year":"2020","unstructured":"Motika SE, Hergenrother PJ (2020) Re-engineering natural products to engage new biological targets. Nat Prod Rep 37(11):1395\u20131403","journal-title":"Nat Prod Rep"},{"issue":"5","key":"1645_CR71","doi-asserted-by":"crossref","first-page":"677","DOI":"10.1039\/C9NP00059C","volume":"37","author":"S Nishimura","year":"2020","unstructured":"Nishimura S, Matsumori N (2020) Chemical diversity and mode of action of natural products targeting lipids in the eukaryotic cell membrane. Nat Prod Rep 37(5):677\u2013702","journal-title":"Nat Prod Rep"},{"key":"1645_CR72","first-page":"201","volume-title":"Plant-Microbe Dynamics","author":"A Shafi","year":"2021","unstructured":"Shafi A, Zahoor I, Habib H (2021) Omics technologies to unravel plant-microbe interactions. Plant-Microbe Dynamics. CRC Press, pp 201\u2013220"},{"key":"1645_CR73","doi-asserted-by":"crossref","first-page":"66","DOI":"10.1016\/j.copbio.2021.10.023","volume":"74","author":"OP Gupta","year":"2022","unstructured":"Gupta OP et al (2022) From gene to biomolecular networks: a review of evidences for understanding complex biological function in plants. Curr Opin Biotechnol 74:66\u201374","journal-title":"Curr Opin Biotechnol"},{"key":"1645_CR74","doi-asserted-by":"crossref","first-page":"102232","DOI":"10.1016\/j.pbi.2022.102232","volume":"68","author":"M Hajheidari","year":"2022","unstructured":"Hajheidari M, Huang SSC (2022) Elucidating the biology of transcription factor\u2013DNA interaction for accurate identification of cis-regulatory elements. Curr Opin Plant Biol 68:102232","journal-title":"Curr Opin Plant Biol"},{"issue":"(suppl_2)","key":"1645_CR75","doi-asserted-by":"crossref","first-page":"W339","DOI":"10.1093\/nar\/gkr466","volume":"39","author":"MH Medema","year":"2011","unstructured":"Medema MH et al (2011) antiSMASH: rapid identification, annotation and analysis of secondary metabolite biosynthesis gene clusters in bacterial and fungal genome sequences. Nucleic Acids Res 39((suppl_2)):W339\u2013W346","journal-title":"Nucleic Acids Res"},{"issue":"4","key":"1645_CR76","doi-asserted-by":"crossref","first-page":"680","DOI":"10.1111\/tpj.12827","volume":"82","author":"F Kellner","year":"2015","unstructured":"Kellner F et al (2015) Genome-guided investigation of plant natural product biosynthesis. Plant J 82(4):680\u2013692","journal-title":"Plant J"},{"issue":"3","key":"1645_CR77","doi-asserted-by":"crossref","first-page":"771","DOI":"10.1111\/nph.13981","volume":"211","author":"HW N\u00fctzmann","year":"2016","unstructured":"N\u00fctzmann HW, Huang A, Osbourn A (2016) Plant metabolic clusters\u2013from genetics to genomics. New Phytol 211(3):771\u2013789","journal-title":"New Phytol"},{"issue":"W1","key":"1645_CR78","doi-asserted-by":"crossref","first-page":"W55","DOI":"10.1093\/nar\/gkx305","volume":"45","author":"SA Kautsar","year":"2017","unstructured":"Kautsar SA et al (2017) plantiSMASH: automated identification, annotation and expression analysis of plant biosynthetic gene clusters. Nucleic Acids Res 45(W1):W55\u2013W63","journal-title":"Nucleic Acids Res"},{"issue":"9","key":"1645_CR79","doi-asserted-by":"crossref","first-page":"625","DOI":"10.1038\/nchembio.1890","volume":"11","author":"MH Medema","year":"2015","unstructured":"Medema MH et al (2015) Minimum information about a biosynthetic gene cluster. Nat Chem Biol 11(9):625\u2013631","journal-title":"Nat Chem Biol"},{"issue":"2","key":"1645_CR80","doi-asserted-by":"crossref","first-page":"111","DOI":"10.1038\/nrd4510","volume":"14","author":"AL Harvey","year":"2015","unstructured":"Harvey AL, Edrada-Ebel R, Quinn RJ (2015) The re-emergence of natural products for drug discovery in the genomics era. Nat Rev Drug Discovery 14(2):111\u2013129","journal-title":"Nat Rev Drug Discovery"},{"issue":"3\u20134","key":"1645_CR81","doi-asserted-by":"crossref","first-page":"281","DOI":"10.1007\/s10295-018-2115-4","volume":"46","author":"RH Baltz","year":"2019","unstructured":"Baltz RH (2019) Natural product drug discovery in the genomic era: realities, conjectures, misconceptions, and opportunities. J Ind Microbiol Biotechnol 46(3\u20134):281\u2013299","journal-title":"J Ind Microbiol Biotechnol"},{"key":"1645_CR82","doi-asserted-by":"crossref","first-page":"163","DOI":"10.1007\/978-981-97-4292-9_9","volume-title":"Ethnopharmacology and OMICS Advances in Medicinal Plants Volume 2: Revealing the Secrets of Medicinal Plants","author":"R Cahyaningsih","year":"2024","unstructured":"Cahyaningsih R et al (2024) DNA Barcoding of Medicinal Plants for Conservation Purposes. Ethnopharmacology and OMICS Advances in Medicinal Plants Volume 2: Revealing the Secrets of Medicinal Plants. Springer, pp 163\u2013212"},{"key":"1645_CR83","doi-asserted-by":"crossref","first-page":"2485","DOI":"10.1007\/s11033-014-3105-x","volume":"41","author":"M Cao","year":"2014","unstructured":"Cao M et al (2014) Authentication of animal signatures in traditional Chinese medicine of Lingyang Qingfei Wan using routine molecular diagnostic assays. Mol Biol Rep 41:2485\u20132491","journal-title":"Mol Biol Rep"},{"issue":"1","key":"1645_CR84","doi-asserted-by":"crossref","first-page":"8","DOI":"10.1111\/pbi.12419","volume":"14","author":"P Mishra","year":"2016","unstructured":"Mishra P et al (2016) DNA barcoding: an efficient tool to overcome authentication challenges in the herbal market. Plant Biotechnol J 14(1):8\u201321","journal-title":"Plant Biotechnol J"},{"key":"1645_CR85","doi-asserted-by":"crossref","first-page":"329","DOI":"10.3389\/fpls.2016.00329","volume":"7","author":"G Pulice","year":"2016","unstructured":"Pulice G, Pelaz S, Mat\u00edas-Hern\u00e1ndez L (2016) Molecular farming in Artemisia annua, a promising approach to improve anti-malarial drug production. Front Plant Sci 7:329","journal-title":"Front Plant Sci"},{"issue":"(W1)","key":"1645_CR86","doi-asserted-by":"crossref","first-page":"W46","DOI":"10.1093\/nar\/gkad344","volume":"51","author":"K Blin","year":"2023","unstructured":"Blin K et al (2023) antiSMASH 7.0: new and improved predictions for detection regulation chemical structures and visualisation. Nucleic Acids Res 51((W1)):W46\u2013W50","journal-title":"Nucleic Acids Res"},{"issue":"1","key":"1645_CR87","doi-asserted-by":"crossref","first-page":"6058","DOI":"10.1038\/s41467-020-19986-1","volume":"11","author":"MA Skinnider","year":"2020","unstructured":"Skinnider MA et al (2020) Comprehensive prediction of secondary metabolite structure and biological activity from microbial genome sequences. Nat Commun 11(1):6058","journal-title":"Nat Commun"},{"issue":"18","key":"1645_CR88","doi-asserted-by":"crossref","first-page":"e110","DOI":"10.1093\/nar\/gkz654","volume":"47","author":"GD Hannigan","year":"2019","unstructured":"Hannigan GD et al (2019) A deep learning genome-mining strategy for biosynthetic gene cluster prediction. Nucleic Acids Res 47(18):e110\u2013e110","journal-title":"Nucleic Acids Res"},{"key":"1645_CR89","unstructured":"Kautsar SA, 20230 Mapping natural product diversity through genomics. Wagening Univ Res"},{"key":"1645_CR90","unstructured":"Debras M, 2022 Analysis of secondary metabolite biosynthetic gene clusters in lichen metagenomes"},{"issue":"1","key":"1645_CR91","doi-asserted-by":"crossref","first-page":"4312","DOI":"10.1038\/s41467-024-48771-7","volume":"15","author":"J Tang","year":"2024","unstructured":"Tang J, Matsuda Y (2024) Discovery of fungal onoceroid triterpenoids through domainless enzyme-targeted global genome mining. Nat Commun 15(1):4312","journal-title":"Nat Commun"},{"issue":"(W1)","key":"1645_CR92","doi-asserted-by":"crossref","first-page":"W546","DOI":"10.1093\/nar\/gkaa374","volume":"48","author":"MD Mungan","year":"2020","unstructured":"Mungan MD et al (2020) ARTS 2.0: feature updates and expansion of the Antibiotic Resistant Target Seeker for comparative genome mining. Nucleic Acids Res 48((W1)):W546\u2013W552","journal-title":"Nucleic Acids Res"},{"issue":"6","key":"1645_CR93","doi-asserted-by":"crossref","first-page":"398","DOI":"10.3390\/md20060398","volume":"20","author":"JJL Malit","year":"2022","unstructured":"Malit JJL, Leung HYC, Qian P-Y (2022) Targeted large-scale genome mining and candidate prioritization for natural product discovery. Mar Drugs 20(6):398","journal-title":"Mar Drugs"},{"issue":"14","key":"1645_CR94","doi-asserted-by":"crossref","first-page":"9614","DOI":"10.1021\/jacs.3c12895","volume":"146","author":"D Chen","year":"2024","unstructured":"Chen D et al (2024) Targeted discovery of glycosylated natural products by tailoring enzyme-guided genome mining and MS-based metabolome analysis. J Am Chem Soc 146(14):9614\u20139622","journal-title":"J Am Chem Soc"},{"key":"1645_CR95","doi-asserted-by":"crossref","first-page":"19","DOI":"10.3389\/fgene.2020.00019","volume":"11","author":"X Yang","year":"2020","unstructured":"Yang X et al (2020) High-throughput transcriptome profiling in drug and biomarker discovery. Front Genet 11:19","journal-title":"Front Genet"},{"issue":"2\u20133","key":"1645_CR96","doi-asserted-by":"crossref","first-page":"129","DOI":"10.1007\/s10295-015-1706-6","volume":"43","author":"M Katz","year":"2016","unstructured":"Katz M, Hover BM, Brady SF (2016) Culture-independent discovery of natural products from soil metagenomes. J Ind Microbiol Biotechnol 43(2\u20133):129\u2013141","journal-title":"J Ind Microbiol Biotechnol"},{"issue":"25","key":"1645_CR97","doi-asserted-by":"crossref","first-page":"9014","DOI":"10.1073\/pnas.0503671102","volume":"102","author":"K Virtaneva","year":"2005","unstructured":"Virtaneva K et al (2005) Longitudinal analysis of the group A Streptococcus transcriptome in experimental pharyngitis in cynomolgus macaques. Proc Natl Acad Sci 102(25):9014\u20139019","journal-title":"Proc Natl Acad Sci"},{"issue":"1","key":"1645_CR98","doi-asserted-by":"crossref","first-page":"5909","DOI":"10.1038\/s41467-021-26044-x","volume":"12","author":"Y He","year":"2021","unstructured":"He Y et al (2021) ClusterMap for multi-scale clustering analysis of spatial gene expression. Nat Commun 12(1):5909","journal-title":"Nat Commun"},{"issue":"8","key":"1645_CR99","doi-asserted-by":"crossref","first-page":"731","DOI":"10.1039\/D2MO00138A","volume":"18","author":"IM Cabral","year":"2022","unstructured":"Cabral IM et al (2022) A drug discovery approach based on comparative transcriptomics between two toxin-secreting marine annelids: Glycera alba and Hediste diversicolor. Molecular Omics 18(8):731\u2013744","journal-title":"Molecular Omics"},{"key":"1645_CR100","doi-asserted-by":"crossref","first-page":"37","DOI":"10.1201\/9781003099079-3","volume-title":"Crop Improvement","author":"R Jain","year":"2021","unstructured":"Jain R et al (2021) Integrated metabolome and transcriptome analysis: a new platform\/technology for functional biology and natural products research. Crop Improvement. CRC Press, pp 37\u201351"},{"issue":"10","key":"1645_CR101","doi-asserted-by":"crossref","first-page":"1412","DOI":"10.1039\/C8NP00091C","volume":"36","author":"L Huo","year":"2019","unstructured":"Huo L et al (2019) Heterologous expression of bacterial natural product biosynthetic pathways. Nat Prod Rep 36(10):1412\u20131436","journal-title":"Nat Prod Rep"},{"issue":"7","key":"1645_CR102","doi-asserted-by":"crossref","first-page":"1882","DOI":"10.1021\/acs.jcim.2c01301","volume":"63","author":"D Das","year":"2023","unstructured":"Das D et al (2023) Gex2SGen: Designing drug-like molecules from desired gene expression signatures. J Chem Inf Model 63(7):1882\u20131893","journal-title":"J Chem Inf Model"},{"issue":"9","key":"1645_CR103","doi-asserted-by":"crossref","first-page":"2242","DOI":"10.1021\/acs.jnatprod.5b00455","volume":"78","author":"JL Ochoa","year":"2015","unstructured":"Ochoa JL et al (2015) Phenotype-guided natural products discovery using cytological profiling. J Nat Prod 78(9):2242\u20132248","journal-title":"J Nat Prod"},{"issue":"4","key":"1645_CR104","doi-asserted-by":"crossref","first-page":"274","DOI":"10.1016\/j.tibs.2017.01.004","volume":"42","author":"X Liu","year":"2017","unstructured":"Liu X, Locasale JW (2017) Metabolomics: a primer. Trends Biochem Sci 42(4):274\u2013284","journal-title":"Trends Biochem Sci"},{"issue":"1","key":"1645_CR105","doi-asserted-by":"crossref","first-page":"a000588","DOI":"10.1101\/mcs.a000588","volume":"1","author":"CB Clish","year":"2015","unstructured":"Clish CB (2015) Metabolomics: an emerging but powerful tool for precision medicine. Molecular Case Studies 1(1):a000588","journal-title":"Molecular Case Studies"},{"key":"1645_CR106","doi-asserted-by":"crossref","first-page":"321","DOI":"10.1007\/s13659-018-0175-9","volume":"8","author":"Q Zhao","year":"2018","unstructured":"Zhao Q, Zhang J-L, Li F (2018) Application of metabolomics in the study of natural products. Nat Prod Bioprospecting 8:321\u2013334","journal-title":"Nat Prod Bioprospecting"},{"issue":"24","key":"1645_CR107","doi-asserted-by":"crossref","first-page":"2297","DOI":"10.4155\/bio-2019-0014","volume":"11","author":"K Segers","year":"2019","unstructured":"Segers K et al (2019) Analytical techniques for metabolomic studies: A review. Bioanalysis 11(24):2297\u20132318","journal-title":"Bioanalysis"},{"issue":"2","key":"1645_CR108","doi-asserted-by":"crossref","first-page":"31","DOI":"10.3390\/metabo8020031","volume":"8","author":"I Bla\u017eenovi\u0107","year":"2018","unstructured":"Bla\u017eenovi\u0107 I et al (2018) Software tools and approaches for compound identification of LC-MS\/MS data in metabolomics. Metabolites 8(2):31","journal-title":"Metabolites"},{"issue":"5","key":"1645_CR109","doi-asserted-by":"crossref","first-page":"1467","DOI":"10.1038\/s41596-023-00950-4","volume":"19","author":"JD Ewald","year":"2024","unstructured":"Ewald JD et al (2024) Web-based multi-omics integration using the Analyst software suite. Nat Protoc 19(5):1467\u20131497","journal-title":"Nat Protoc"},{"issue":"11","key":"1645_CR110","doi-asserted-by":"crossref","first-page":"e1005752","DOI":"10.1371\/journal.pcbi.1005752","volume":"13","author":"F Rohart","year":"2017","unstructured":"Rohart F et al (2017) mixOmics: An R package for \u2018omics feature selection and multiple data integration. PLoS Comput Biol 13(11):e1005752","journal-title":"PLoS Comput Biol"},{"key":"1645_CR111","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1186\/s12859-019-3224-4","volume":"20","author":"B Ulfenborg","year":"2019","unstructured":"Ulfenborg B (2019) Vertical and horizontal integration of multi-omics data with miodin. BMC Bioinformatics 20:1\u201310","journal-title":"BMC Bioinformatics"},{"issue":"4","key":"1645_CR112","doi-asserted-by":"crossref","first-page":"76","DOI":"10.3390\/metabo9040076","volume":"9","author":"FR Pinu","year":"2019","unstructured":"Pinu FR et al (2019) Systems biology and multi-omics integration: viewpoints from the metabolomics research community. Metabolites 9(4):76","journal-title":"Metabolites"},{"key":"1645_CR113","doi-asserted-by":"crossref","unstructured":"Domingo-Almenara X. and Siuzdak G. 2020 Metabolomics data processing using XCMS. Computational methods and data analysis for metabolomics. 11\u201324","DOI":"10.1007\/978-1-0716-0239-3_2"},{"issue":"14","key":"1645_CR114","doi-asserted-by":"crossref","first-page":"6931","DOI":"10.1021\/ac500734c","volume":"86","author":"H Gowda","year":"2014","unstructured":"Gowda H et al (2014) Interactive XCMS Online: simplifying advanced metabolomic data processing and subsequent statistical analyses. Anal Chem 86(14):6931\u20136939","journal-title":"Anal Chem"},{"issue":"4","key":"1645_CR115","doi-asserted-by":"crossref","first-page":"633","DOI":"10.1038\/nprot.2017.151","volume":"13","author":"EM Forsberg","year":"2018","unstructured":"Forsberg EM et al (2018) Data processing, multi-omic pathway mapping, and metabolite activity analysis using XCMS Online. Nat Protoc 13(4):633\u2013651","journal-title":"Nat Protoc"},{"key":"1645_CR116","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1007\/s11306-020-1636-9","volume":"16","author":"OE Alb\u00f3niga","year":"2020","unstructured":"Alb\u00f3niga OE et al (2020) Optimization of XCMS parameters for LC\u2013MS metabolomics: an assessment of automated versus manual tuning and its effect on the final results. Metabolomics 16:1\u201312","journal-title":"Metabolomics"},{"issue":"2","key":"1645_CR117","doi-asserted-by":"crossref","first-page":"1254","DOI":"10.1021\/acs.analchem.6b03890","volume":"89","author":"JR Montenegro-Burke","year":"2017","unstructured":"Montenegro-Burke JR et al (2017) Data streaming for metabolomics: accelerating data processing and analysis from days to minutes. Anal Chem 89(2):1254\u20131259","journal-title":"Anal Chem"},{"key":"1645_CR118","doi-asserted-by":"crossref","unstructured":"Chong J. and Xia J. U2020 sing MetaboAnalyst 4.0 for metabolomics data analysis interpretation and integration with other omics data. Computational methods and data analysis for metabolomics. 337\u2013360","DOI":"10.1007\/978-1-0716-0239-3_17"},{"issue":"1","key":"1645_CR119","doi-asserted-by":"crossref","first-page":"e86","DOI":"10.1002\/cpbi.86","volume":"68","author":"J Chong","year":"2019","unstructured":"Chong J, Wishart DS, Xia J (2019) Using MetaboAnalyst 4 0 for comprehensive and integrative metabolomics data analysis. Curr Protoc In Bioinforma 68(1):e86","journal-title":"Curr Protoc In Bioinforma"},{"key":"1645_CR120","doi-asserted-by":"crossref","unstructured":"Xia J. and Wishart DS., 2011 Metabolomic data processing, analysis, and interpretation using MetaboAnalyst. CurrProtoc Bioinforma. 34(1) 14.10. 1\u201314.10. 48","DOI":"10.1002\/0471250953.bi1410s34"},{"issue":"18","key":"1645_CR121","doi-asserted-by":"crossref","first-page":"1700332","DOI":"10.1002\/pmic.201700332","volume":"18","author":"C Du","year":"2018","unstructured":"Du C, van Wezel GP (2018) Mining for microbial gems: integrating proteomics in the postgenomic natural product discovery pipeline. Proteomics 18(18):1700332","journal-title":"Proteomics"},{"key":"1645_CR122","doi-asserted-by":"crossref","first-page":"504","DOI":"10.3389\/fpls.2015.00504","volume":"6","author":"MJ Mart\u00ednez-Esteso","year":"2015","unstructured":"Mart\u00ednez-Esteso MJ et al (2015) The role of proteomics in progressing insights into plant secondary metabolism. Front Plant Sci 6:504","journal-title":"Front Plant Sci"},{"issue":"6","key":"1645_CR123","doi-asserted-by":"crossref","first-page":"1578","DOI":"10.3390\/ijms19061578","volume":"19","author":"NE Thomford","year":"2018","unstructured":"Thomford NE et al (2018) Natural products for drug discovery in the 21st century: innovations for novel drug discovery. Int J Mol Sci 19(6):1578","journal-title":"Int J Mol Sci"},{"issue":"3","key":"1645_CR124","doi-asserted-by":"crossref","first-page":"535","DOI":"10.1016\/j.jep.2012.01.055","volume":"140","author":"A Buriani","year":"2012","unstructured":"Buriani A et al (2012) Omic techniques in systems biology approaches to traditional Chinese medicine research: present and future. J Ethnopharmacol 140(3):535\u2013544","journal-title":"J Ethnopharmacol"},{"issue":"1","key":"1645_CR125","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.jep.2014.05.022","volume":"155","author":"Y Lao","year":"2014","unstructured":"Lao Y et al (2014) Application of proteomics to determine the mechanism of action of traditional Chinese medicine remedies. J Ethnopharmacol 155(1):1\u20138","journal-title":"J Ethnopharmacol"},{"issue":"9","key":"1645_CR126","doi-asserted-by":"crossref","first-page":"637","DOI":"10.1038\/s41573-022-00409-3","volume":"21","author":"F Meissner","year":"2022","unstructured":"Meissner F et al (2022) The emerging role of mass spectrometry-based proteomics in drug discovery. Nat Rev Drug Discovery 21(9):637\u2013654","journal-title":"Nat Rev Drug Discovery"},{"issue":"9","key":"1645_CR127","doi-asserted-by":"crossref","first-page":"616","DOI":"10.1038\/nchembio.216","volume":"5","author":"U Rix","year":"2009","unstructured":"Rix U, Superti-Furga G (2009) Target profiling of small molecules by chemical proteomics. Nat Chem Biol 5(9):616\u2013624","journal-title":"Nat Chem Biol"},{"issue":"11","key":"1645_CR128","doi-asserted-by":"crossref","first-page":"948","DOI":"10.1021\/cb9002128","volume":"4","author":"JL Meier","year":"2009","unstructured":"Meier JL et al (2009) An orthogonal active site identification system (OASIS) for proteomic profiling of natural product biosynthesis. ACS Chem Biol 4(11):948\u2013957","journal-title":"ACS Chem Biol"},{"key":"1645_CR129","doi-asserted-by":"crossref","unstructured":"Krysiak J. and Breinbauer R. 2012 Activity-based protein profiling for natural product target discovery. Activity-Based Protein Profiling. 43\u201384","DOI":"10.1007\/128_2011_289"},{"issue":"1","key":"1645_CR130","doi-asserted-by":"crossref","first-page":"72","DOI":"10.1016\/j.chembiol.2012.01.002","volume":"19","author":"M Schirle","year":"2012","unstructured":"Schirle M, Bantscheff M, Kuster B (2012) Mass spectrometry-based proteomics in preclinical drug discovery. Chem Biol 19(1):72\u201384","journal-title":"Chem Biol"},{"key":"1645_CR131","unstructured":"Zali H, and REZAEI TM. 2014 Meningioma protein-protein interaction network"},{"issue":"19","key":"1645_CR132","doi-asserted-by":"crossref","first-page":"2009","DOI":"10.1016\/j.jacc.2010.01.036","volume":"55","author":"J Tu\u00f1\u00f3n","year":"2010","unstructured":"Tu\u00f1\u00f3n J et al (2010) Proteomic strategies in the search of new biomarkers in atherothrombosis. J Am Coll Cardiol 55(19):2009\u20132016","journal-title":"J Am Coll Cardiol"},{"issue":"12","key":"1645_CR133","doi-asserted-by":"crossref","first-page":"952","DOI":"10.1038\/nrm2067","volume":"7","author":"M Mann","year":"2006","unstructured":"Mann M (2006) Functional and quantitative proteomics using SILAC. Nat Rev Mol Cell Biol 7(12):952\u2013958","journal-title":"Nat Rev Mol Cell Biol"},{"issue":"12","key":"1645_CR134","doi-asserted-by":"crossref","first-page":"1154","DOI":"10.1074\/mcp.M400129-MCP200","volume":"3","author":"PL Ross","year":"2004","unstructured":"Ross PL et al (2004) Multiplexed protein quantitation in Saccharomyces cerevisiae using amine-reactive isobaric tagging reagents. Mol Cell Proteomics 3(12):1154\u20131169","journal-title":"Mol Cell Proteomics"},{"issue":"10","key":"1645_CR135","doi-asserted-by":"crossref","first-page":"1884","DOI":"10.1016\/j.jprot.2011.04.030","volume":"74","author":"T Wiedl","year":"2011","unstructured":"Wiedl T et al (2011) Activity-based proteomics: identification of ABHD11 and ESD activities as potential biomarkers for human lung adenocarcinoma. J Proteomics 74(10):1884\u20131894","journal-title":"J Proteomics"},{"issue":"1","key":"1645_CR136","doi-asserted-by":"crossref","first-page":"161","DOI":"10.1016\/j.mad.2006.11.021","volume":"128","author":"DA Hall","year":"2007","unstructured":"Hall DA, Ptacek J, Snyder M (2007) Protein microarray technology. Mech Ageing Dev 128(1):161\u2013167","journal-title":"Mech Ageing Dev"},{"issue":"4","key":"1645_CR137","doi-asserted-by":"crossref","first-page":"427","DOI":"10.1016\/S1367-5931(02)00337-X","volume":"6","author":"J Burbaum","year":"2002","unstructured":"Burbaum J, Tobal GM (2002) Proteomics in drug discovery. Curr Opin Chem Biol 6(4):427\u2013433","journal-title":"Curr Opin Chem Biol"},{"key":"1645_CR138","doi-asserted-by":"crossref","first-page":"10","DOI":"10.1016\/j.pharmthera.2016.01.010","volume":"162","author":"J Wang","year":"2016","unstructured":"Wang J et al (2016) Target identification of natural and traditional medicines with quantitative chemical proteomics approaches. Pharmacol Ther 162:10\u201322","journal-title":"Pharmacol Ther"},{"issue":"6","key":"1645_CR139","doi-asserted-by":"crossref","first-page":"1920","DOI":"10.1093\/bib\/bbz121","volume":"21","author":"A Sathyanarayanan","year":"2020","unstructured":"Sathyanarayanan A et al (2020) A comparative study of multi-omics integration tools for cancer driver gene identification and tumour subtyping. Brief Bioinform 21(6):1920\u20131936","journal-title":"Brief Bioinform"},{"key":"1645_CR140","doi-asserted-by":"crossref","unstructured":"Athaya T, et al., 2023 Multimodal deep learning approaches for single-cell multi-omics data integration. Briefings Bioinforma. 24(5): bbad313","DOI":"10.1093\/bib\/bbad313"},{"issue":"43","key":"1645_CR141","doi-asserted-by":"crossref","first-page":"15222","DOI":"10.1021\/ja5062054","volume":"136","author":"NA Jungmann","year":"2014","unstructured":"Jungmann NA et al (2014) Dissecting reactions of nonlinear precursor peptide processing of the class III lanthipeptide curvopeptin. J Am Chem Soc 136(43):15222\u201315228","journal-title":"J Am Chem Soc"},{"issue":"8","key":"1645_CR142","doi-asserted-by":"crossref","first-page":"564","DOI":"10.1038\/nchembio.1856","volume":"11","author":"BJ Burkhart","year":"2015","unstructured":"Burkhart BJ et al (2015) A prevalent peptide-binding domain guides ribosomal natural product biosynthesis. Nat Chem Biol 11(8):564\u2013570","journal-title":"Nat Chem Biol"},{"issue":"12","key":"1645_CR143","doi-asserted-by":"crossref","first-page":"1606","DOI":"10.3390\/biom10121606","volume":"10","author":"SM Lancaster","year":"2020","unstructured":"Lancaster SM et al (2020) A customizable analysis flow in integrative multi-omics. Biomolecules 10(12):1606","journal-title":"Biomolecules"},{"issue":"5","key":"1645_CR144","doi-asserted-by":"crossref","first-page":"202","DOI":"10.3390\/metabo10050202","volume":"10","author":"T Eicher","year":"2020","unstructured":"Eicher T et al (2020) Metabolomics and multi-omics integration: a survey of computational methods and resources. Metabolites 10(5):202","journal-title":"Metabolites"},{"key":"1645_CR145","doi-asserted-by":"crossref","unstructured":"Jiang Y, et al., 2023 Simultaneous multi-omics analysis by direct infusion mass spectrometry (SMAD-MS).bioRxiv","DOI":"10.1101\/2023.06.26.546628"},{"key":"1645_CR146","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1186\/s13059-017-1215-1","volume":"18","author":"Y Hasin","year":"2017","unstructured":"Hasin Y, Seldin M, Lusis A (2017b) Multi-omics approaches to disease. Genome Biol 18:1\u201315","journal-title":"Genome Biol"},{"issue":"1","key":"1645_CR147","doi-asserted-by":"crossref","first-page":"256","DOI":"10.1038\/s41597-019-0202-7","volume":"6","author":"D Gomez-Cabrero","year":"2019","unstructured":"Gomez-Cabrero D et al (2019) STATegra, a comprehensive multi-omics dataset of B-cell differentiation in mouse. Scientific Data 6(1):256","journal-title":"Scientific Data"},{"issue":"6","key":"1645_CR148","doi-asserted-by":"crossref","first-page":"395","DOI":"10.1038\/s43588-021-00086-z","volume":"1","author":"S Tarazona","year":"2021","unstructured":"Tarazona S, Arzalluz-Luque A, Conesa A (2021) Undisclosed, unmet and neglected challenges in multi-omics studies. Nature Computational Science 1(6):395\u2013402","journal-title":"Nature Computational Science"},{"key":"1645_CR149","doi-asserted-by":"crossref","first-page":"967205","DOI":"10.3389\/fmolb.2022.967205","volume":"9","author":"FE Agamah","year":"2022","unstructured":"Agamah FE et al (2022) Computational approaches for network-based integrative multi-omics analysis. Front Mol Biosci 9:967205","journal-title":"Front Mol Biosci"},{"issue":"4","key":"1645_CR150","doi-asserted-by":"crossref","first-page":"e315","DOI":"10.1002\/mco2.315","volume":"4","author":"C Chen","year":"2023","unstructured":"Chen C et al (2023) Applications of multi-omics analysis in human diseases. MedComm 4(4):e315","journal-title":"MedComm"},{"issue":"1","key":"1645_CR151","doi-asserted-by":"crossref","first-page":"14","DOI":"10.1186\/s13073-024-01282-y","volume":"16","author":"P Kiessling","year":"2024","unstructured":"Kiessling P, Kuppe C (2024) Spatial multi-omics: novel tools to study the complexity of cardiovascular diseases. Genome Medicine 16(1):14","journal-title":"Genome Medicine"},{"key":"1645_CR152","doi-asserted-by":"crossref","first-page":"41","DOI":"10.1007\/978-981-19-7952-1_3","volume-title":"Drugs and a Methodological Compendium: From bench to bedside","author":"D Das","year":"2023","unstructured":"Das D, Shafi S (2023) Bioactivity-Guided Fractionation and Identification of Bioactive Molecules: A Basic Method in Drug Discovery. Drugs and a Methodological Compendium: From bench to bedside. Springer, pp 41\u201378"},{"issue":"8","key":"1645_CR153","doi-asserted-by":"crossref","first-page":"1014","DOI":"10.3390\/antibiotics11081014","volume":"11","author":"N Vaou","year":"2022","unstructured":"Vaou N et al (2022) Interactions between medical plant-derived bioactive compounds: Focus on antimicrobial combination effects. Antibiotics 11(8):1014","journal-title":"Antibiotics"},{"issue":"5","key":"1645_CR154","doi-asserted-by":"crossref","first-page":"307","DOI":"10.1039\/C8MO00136G","volume":"14","author":"BC Blum","year":"2018","unstructured":"Blum BC, Mousavi F, Emili A (2018) Single-platform \u2018multi-omic\u2019profiling: unified mass spectrometry and computational workflows for integrative proteomics\u2013metabolomics analysis. Molecular Omics 14(5):307\u2013319","journal-title":"Molecular Omics"},{"key":"1645_CR155","unstructured":"Al Kaabi MK. 2020 Bio-guided fractionation of Tamarix nilotica aqueous extract based on its anticancer property"},{"key":"1645_CR156","doi-asserted-by":"crossref","first-page":"343","DOI":"10.1016\/j.csbj.2021.12.024","volume":"20","author":"AU Geers","year":"2022","unstructured":"Geers AU et al (2022) The natural product biosynthesis potential of the microbiomes of Earth-Bioprospecting for novel anti-microbial agents in the meta-omics era. Comput Struct Biotechnol J 20:343\u2013352","journal-title":"Comput Struct Biotechnol J"},{"key":"1645_CR157","unstructured":"Alvarenga RFR. 2014 Methods for the Metabolomic Standardization of Natural Health Products. 2014, University of Illinois at Chicago"},{"issue":"4","key":"1645_CR158","doi-asserted-by":"crossref","first-page":"758","DOI":"10.1021\/acs.jnatprod.7b00737","volume":"81","author":"L-F Nothias","year":"2018","unstructured":"Nothias L-F et al (2018) Bioactivity-based molecular networking for the discovery of drug leads in natural product bioassay-guided fractionation. J Nat Prod 81(4):758\u2013767","journal-title":"J Nat Prod"},{"issue":"7","key":"1645_CR159","doi-asserted-by":"crossref","first-page":"960","DOI":"10.1039\/C9NP00006B","volume":"36","author":"AEF Ramos","year":"2019","unstructured":"Ramos AEF et al (2019) Natural products targeting strategies involving molecular networking: different manners, one goal. Nat Prod Rep 36(7):960\u2013980","journal-title":"Nat Prod Rep"},{"issue":"2","key":"1645_CR160","first-page":"126","volume":"2","author":"M Zhang","year":"2023","unstructured":"Zhang M, Otsuki K, Li W (2023a) Molecular networking as a natural products discovery strategy. Acta Materia Medica 2(2):126\u2013141","journal-title":"Acta Materia Medica"},{"key":"1645_CR161","doi-asserted-by":"crossref","unstructured":"Chang S, et al., 2024 Bioactivity-Based Molecular Networking-Guided Isolation of Epicolidines A\u2013C from the Endophytic Fungus Epicoccum sp. 1\u2013042. J Nat Prod. 87(6) 1582\u20131590","DOI":"10.1021\/acs.jnatprod.4c00214"},{"issue":"6","key":"1645_CR162","doi-asserted-by":"crossref","first-page":"311","DOI":"10.3390\/md18060311","volume":"18","author":"L Buedenbender","year":"2020","unstructured":"Buedenbender L, Astone FA, Tasdemir D (2020) Bioactive molecular networking for mapping the antimicrobial constituents of the baltic brown alga Fucus vesiculosus. Mar Drugs 18(6):311","journal-title":"Mar Drugs"},{"issue":"21","key":"1645_CR163","doi-asserted-by":"crossref","first-page":"1751","DOI":"10.2174\/1568026622666220726092034","volume":"22","author":"AT Aborode","year":"2022","unstructured":"Aborode AT et al (2022) OMICs Technologies for natural compounds-based drug development. Curr Top Med Chem 22(21):1751\u20131765","journal-title":"Curr Top Med Chem"},{"key":"1645_CR164","doi-asserted-by":"crossref","first-page":"1073848","DOI":"10.3389\/fpls.2023.1073848","volume":"14","author":"W Zhang","year":"2023","unstructured":"Zhang W et al (2023b) Integration of high-throughput omics technologies in medicinal plant research: The new era of natural drug discovery. Front Plant Sci 14:1073848","journal-title":"Front Plant Sci"},{"issue":"1","key":"1645_CR165","doi-asserted-by":"crossref","first-page":"4","DOI":"10.1186\/s13068-018-1350-2","volume":"12","author":"J Miao","year":"2019","unstructured":"Miao J et al (2019) Effects of amino acids on the lignocellulose degradation by Aspergillus fumigatus Z5: insights into performance, transcriptional, and proteomic profiles. Biotechnol Biofuels 12(1):4","journal-title":"Biotechnol Biofuels"},{"key":"1645_CR166","doi-asserted-by":"crossref","unstructured":"Sivaranjani M, et al., 2019 Deciphering the antibacterial mode of action of alpha-mangostin on staphylococcus epidermidis rp62a through an integrated transcriptomic and proteomic approach. Front Microbiol. 10","DOI":"10.3389\/fmicb.2019.00150"},{"issue":"10","key":"1645_CR167","doi-asserted-by":"crossref","first-page":"2463","DOI":"10.3390\/ijms20102463","volume":"20","author":"X Chen","year":"2019","unstructured":"Chen X et al (2019) Transcriptome and Proteome Profiling of Different Colored Rice Reveals Physiological Dynamics Involved in the Flavonoid Pathway. Int J Mol Sci 20(10):2463","journal-title":"Int J Mol Sci"},{"key":"1645_CR168","doi-asserted-by":"publisher","unstructured":"Pattrick CA, et al., 2019 proteomic profiling, transcription factor modeling, and genomics of evolved tolerant strains elucidate mechanisms of vanillin toxicity in escherichia coli. MSystems. 4(4) https:\/\/doi.org\/10.1128\/msystems.00163-19","DOI":"10.1128\/msystems.00163-19"},{"key":"1645_CR169","doi-asserted-by":"crossref","first-page":"191","DOI":"10.1016\/j.jprot.2018.11.018","volume":"194","author":"PP Das","year":"2019","unstructured":"Das PP, Lin Q, Wong S-M (2019) Comparative proteomics of Tobacco mosaic virus-infected Nicotiana tabacum plants identified major host proteins involved in photosystems and plant defence. J Proteomics 194:191\u2013199","journal-title":"J Proteomics"},{"issue":"1","key":"1645_CR170","doi-asserted-by":"crossref","first-page":"15504","DOI":"10.1038\/s41598-020-72596-1","volume":"10","author":"H Gu","year":"2020","unstructured":"Gu H et al (2020) Drought stress triggers proteomic changes involving lignin, flavonoids and fatty acids in tea plants. Sci Rep 10(1):15504","journal-title":"Sci Rep"},{"key":"1645_CR171","doi-asserted-by":"crossref","DOI":"10.1016\/j.foodchem.2019.125244","volume":"303","author":"E Scollo","year":"2020","unstructured":"Scollo E et al (2020) UHPLC\u2013MS\/MS analysis of cocoa bean proteomes from four different genotypes. Food Chem 303:125244","journal-title":"Food Chem"},{"key":"1645_CR172","doi-asserted-by":"crossref","first-page":"124283","DOI":"10.1016\/j.jhazmat.2020.124283","volume":"406","author":"S Rao","year":"2021","unstructured":"Rao S et al (2021) Transcriptome, proteome, and metabolome reveal the mechanism of tolerance to selenate toxicity in Cardamine violifolia. J Hazard Mater 406:124283","journal-title":"J Hazard Mater"},{"issue":"4","key":"1645_CR173","doi-asserted-by":"crossref","first-page":"297","DOI":"10.1007\/s12374-020-09251-9","volume":"63","author":"Y Dai","year":"2020","unstructured":"Dai Y et al (2020) Label-Free Quantitative Proteomic Profiling Identifies Potential Active Components to Exert Pharmacological Effects in the Fruit of Alpinia oxyphylla by Mass Spectrometry. J Plant Biol 63(4):297\u2013310","journal-title":"J Plant Biol"},{"issue":"2","key":"1645_CR174","doi-asserted-by":"crossref","first-page":"e0226888","DOI":"10.1371\/journal.pone.0226888","volume":"15","author":"Z Ye","year":"2020","unstructured":"Ye Z et al (2020) Complementary transcriptome and proteome profiling in the mature seeds of Camellia oleifera from Hainan Island. PLoS ONE 15(2):e0226888","journal-title":"PLoS ONE"},{"issue":"1","key":"1645_CR175","doi-asserted-by":"crossref","first-page":"381","DOI":"10.1007\/s10340-021-01381-4","volume":"95","author":"F Renoz","year":"2022","unstructured":"Renoz F et al (2022) The modes of action of Mentha arvensis essential oil on the granary weevil Sitophilus granarius revealed by a label-free quantitative proteomic analysis. J Pest Sci 95(1):381\u2013395","journal-title":"J Pest Sci"},{"key":"1645_CR176","doi-asserted-by":"crossref","unstructured":"Sohail, et al., 2022 Molecular effects of biogenic zinc nanoparticles on the growth and development of brassica napus L. revealed by proteomics and transcriptomics. Front Plant Sci. 13","DOI":"10.3389\/fpls.2022.798751"},{"issue":"9","key":"1645_CR177","doi-asserted-by":"crossref","first-page":"e528","DOI":"10.1002\/pld3.528","volume":"7","author":"P Suwanchaikasem","year":"2023","unstructured":"Suwanchaikasem P et al (2023) Hormonal and proteomic analyses of southern blight disease caused by Athelia rolfsii and root chitosan priming on Cannabis sativa in an in vitro hydroponic system. Plant Direct 7(9):e528","journal-title":"Plant Direct"},{"key":"1645_CR178","doi-asserted-by":"crossref","unstructured":"Huang C., et al., 2023 Integrated transcriptome and proteome analyses reveal candidate genes for ginsenoside biosynthesis in Panax japonicus C. A. Meyer. Front Plant Sci. 13","DOI":"10.3389\/fpls.2022.1106145"},{"issue":"4","key":"1645_CR179","doi-asserted-by":"crossref","first-page":"518","DOI":"10.3390\/foods13040518","volume":"13","author":"T Ai","year":"2024","unstructured":"Ai T et al (2024) Proteomics Analysis Reveals the Underlying Factors of Mucilage Disappearance in Brasenia schreberi and Its Influence on Nutrient Accumulation. Foods 13(4):518","journal-title":"Foods"},{"issue":"1","key":"1645_CR180","doi-asserted-by":"crossref","first-page":"4789","DOI":"10.1038\/s41598-024-55596-3","volume":"14","author":"F Shi","year":"2024","unstructured":"Shi F et al (2024) Unveiling molecular mechanisms of pepper resistance to Phytophthora capsici through grafting using iTRAQ-based proteomic analysis. Sci Rep 14(1):4789","journal-title":"Sci Rep"},{"issue":"1","key":"1645_CR181","doi-asserted-by":"crossref","first-page":"971","DOI":"10.1038\/s41467-020-14776-1","volume":"11","author":"L Tu","year":"2020","unstructured":"Tu L et al (2020) Genome of Tripterygium wilfordii and identification of cytochrome P450 involved in triptolide biosynthesis. Nat Commun 11(1):971","journal-title":"Nat Commun"},{"issue":"1","key":"1645_CR182","doi-asserted-by":"crossref","first-page":"5","DOI":"10.1186\/s12866-018-1380-8","volume":"19","author":"EN Grady","year":"2019","unstructured":"Grady EN et al (2019) Characterization and complete genome analysis of the surfactin-producing, plant-protecting bacterium Bacillus velezensis 9D\u20136. BMC Microbiol 19(1):5","journal-title":"BMC Microbiol"},{"key":"1645_CR183","doi-asserted-by":"crossref","unstructured":"Hu Z, et al., 2020 Genome-Wide Characterization of the C-repeat Binding Factor (CBF) Gene Family Involved in the Response to Abiotic Stresses in Tea Plant (Camellia sinensis). Front Plant Sci. 11","DOI":"10.3389\/fpls.2020.00921"},{"issue":"5","key":"1645_CR184","doi-asserted-by":"crossref","first-page":"1224","DOI":"10.1111\/tpj.16007","volume":"112","author":"X Han","year":"2022","unstructured":"Han X et al (2022) The chromosome-level genome of female ginseng (Angelica sinensis) provides insights into molecular mechanisms and evolution of coumarin biosynthesis. Plant J 112(5):1224\u20131237","journal-title":"Plant J"},{"key":"1645_CR185","doi-asserted-by":"crossref","unstructured":"Shang X, et al., 2022 Genome-wide analysis of the tcp gene family and their expression pattern analysis in tea plant (Camellia sinensis). Front Plant Sci. 13","DOI":"10.3389\/fpls.2022.840350"},{"issue":"6","key":"1645_CR186","doi-asserted-by":"crossref","first-page":"1442","DOI":"10.1111\/jipb.13469","volume":"65","author":"I Julca","year":"2023","unstructured":"Julca I et al (2023) Genomic, transcriptomic, and metabolomic analysis of Oldenlandia corymbosa reveals the biosynthesis and mode of action of anti-cancer metabolites. J Integr Plant Biol 65(6):1442\u20131466","journal-title":"J Integr Plant Biol"},{"key":"1645_CR187","doi-asserted-by":"crossref","unstructured":"Wu HY., et al., 2023 Whole genome sequence characterization of Aspergillus terreus ATCC 20541 and genome comparison of the fungi A. terreus. Sci Rep. 13(1) 194","DOI":"10.1038\/s41598-022-27311-7"},{"issue":"1","key":"1645_CR188","doi-asserted-by":"crossref","first-page":"90","DOI":"10.1186\/s12864-023-09180-0","volume":"24","author":"N Yanfei","year":"2023","unstructured":"Yanfei N et al (2023) Complete chloroplast genome sequences of the medicinal plant Aconitum transsectum (Ranunculaceae): comparative analysis and phylogenetic relationships. BMC Genomics 24(1):90","journal-title":"BMC Genomics"},{"key":"1645_CR189","doi-asserted-by":"publisher","unstructured":"Silva E, et al. 2021 Untargeted Metabolomics Analysis by UHPLC-MS\/MS of Soybean Plant in a Compatible Response to Phakopsora pachyrhizi Infection. Metabolites. 11. https:\/\/doi.org\/10.3390\/metabo11030179.","DOI":"10.3390\/metabo11030179"},{"issue":"23","key":"1645_CR190","doi-asserted-by":"crossref","first-page":"15776","DOI":"10.1021\/acs.est.1c04059","volume":"55","author":"M Cao","year":"2021","unstructured":"Cao M et al (2021) Transcriptomics and Metabolomics Revealed the Biological Response of Chlorella pyrenoidesa to Single and Repeated Exposures of AgNPs at Different Concentrations. Environ Sci Technol 55(23):15776\u201315787","journal-title":"Environ Sci Technol"},{"key":"1645_CR191","doi-asserted-by":"crossref","unstructured":"Zeng X, et al., 2022 Untargeted metabolomics reveals multiple phytometabolites in the agricultural waste materials and medicinal materials of codonopsispilosula. Front Plant Sci. 12","DOI":"10.3389\/fpls.2021.814011"},{"key":"1645_CR192","doi-asserted-by":"publisher","unstructured":"Alzate Zuluaga MY., et al. 2022 Integrated metabolomics and morpho-biochemical analyses reveal a better performance of azospirillum brasilense over plant-derived biostimulants in counteracting salt stress in tomato. Int J Mol Sci. 23 https:\/\/doi.org\/10.3390\/ijms232214216","DOI":"10.3390\/ijms232214216"},{"key":"1645_CR193","doi-asserted-by":"crossref","unstructured":"Zhou Z., et al., 2022 Combined analysis of lipidomics and transcriptomics revealed the key pathways and genes of lipids in light-sensitive albino tea plant (Camellia sinensis cv. Baijiguan). Front Plant Sci. 13","DOI":"10.3389\/fpls.2022.1035119"},{"key":"1645_CR194","doi-asserted-by":"publisher","unstructured":"Du S., et al. 2022 Lipidomics Analysis of tea leaves cultured in hydroponics reveals that high nitrogen application decreases tea plant resistance to ultraviolet radiation. Horticulturae. 2022. 8, https:\/\/doi.org\/10.3390\/horticulturae8080724","DOI":"10.3390\/horticulturae8080724"},{"issue":"4","key":"1645_CR195","doi-asserted-by":"crossref","first-page":"1152","DOI":"10.1111\/tpj.16329","volume":"116","author":"M Bulut","year":"2023","unstructured":"Bulut M et al (2023) A comprehensive metabolomics and lipidomics atlas for the legumes common bean, chickpea, lentil and lupin. Plant J 116(4):1152\u20131171","journal-title":"Plant J"},{"key":"1645_CR196","doi-asserted-by":"crossref","unstructured":"Wu S, et al., 2023 Integrated metabolomics and lipidomics analyses suggest the temperature-dependent lipid desaturation promotes aflatoxin biosynthesis in Aspergillus flavus. Front Microbiol 14","DOI":"10.3389\/fmicb.2023.1137643"},{"issue":"3","key":"1645_CR197","doi-asserted-by":"crossref","first-page":"1781","DOI":"10.1007\/s12010-022-04233-8","volume":"195","author":"K Rabeh","year":"2023","unstructured":"Rabeh K et al (2023) Lipidomic Profiling of Argania spinosa L. (Skeels) Following Drought Stress. Appl Biochemi Biotechnol. 195(3):1781\u20131799","journal-title":"Appl Biochemi Biotechnol."},{"issue":"12","key":"1645_CR198","doi-asserted-by":"crossref","first-page":"142","DOI":"10.1007\/s11738-023-03623-7","volume":"45","author":"Z Hekmati","year":"2023","unstructured":"Hekmati Z, Zahiri J, Aalami A (2023) Computational prediction of protein\u2013protein interactions\u2019 network in Arabidopsis thaliana. Acta Physiol Plant 45(12):142","journal-title":"Acta Physiol Plant"},{"key":"1645_CR199","doi-asserted-by":"crossref","unstructured":"Gao J, et al., 2021 Iron deficiency induced changes in Fe homeostasis and 14\u20133\u20133 interactomics of Arabidopsis thaliana","DOI":"10.21203\/rs.3.rs-445322\/v1"},{"issue":"3\u20134","key":"1645_CR200","doi-asserted-by":"crossref","first-page":"433","DOI":"10.1007\/s10295-018-2094-5","volume":"46","author":"CN Teijaro","year":"2019","unstructured":"Teijaro CN, Adhikari A, Shen B (2019) Challenges and opportunities for natural product discovery, production, and engineering in native producers versus heterologous hosts. J Ind Microbiol Biotechnol 46(3\u20134):433\u2013444","journal-title":"J Ind Microbiol Biotechnol"},{"issue":"9","key":"1645_CR201","doi-asserted-by":"crossref","first-page":"1876","DOI":"10.1039\/D2NP00032F","volume":"39","author":"KS Singh","year":"2022","unstructured":"Singh KS et al (2022) Integrative omics approaches for biosynthetic pathway discovery in plants. Nat Prod Rep 39(9):1876\u20131896","journal-title":"Nat Prod Rep"},{"issue":"3","key":"1645_CR202","first-page":"498","volume":"18","author":"A Cambiaghi","year":"2017","unstructured":"Cambiaghi A, Ferrario M, Masseroli M (2017) Analysis of metabolomic data: tools, current strategies and future challenges for omics data integration. Brief Bioinform 18(3):498\u2013510","journal-title":"Brief Bioinform"},{"key":"1645_CR203","doi-asserted-by":"crossref","first-page":"52","DOI":"10.1016\/j.micres.2015.01.003","volume":"171","author":"M Fondi","year":"2015","unstructured":"Fondi M, Li\u00f2 P (2015) Multi-omics and metabolic modelling pipelines: challenges and tools for systems microbiology. Microbiol Res 171:52\u201364","journal-title":"Microbiol Res"},{"issue":"2","key":"1645_CR204","doi-asserted-by":"crossref","first-page":"170","DOI":"10.1039\/D0MO00041H","volume":"17","author":"S Graw","year":"2021","unstructured":"Graw S et al (2021) Multi-omics data integration considerations and study design for biological systems and disease. Molecular Omics 17(2):170\u2013185","journal-title":"Molecular Omics"},{"issue":"6","key":"1645_CR205","doi-asserted-by":"crossref","first-page":"3106","DOI":"10.1111\/1541-4337.12618","volume":"19","author":"M Ferone","year":"2020","unstructured":"Ferone M et al (2020) Microbial detection and identification methods: Bench top assays to omics approaches. Compr Rev Food Sci Food Saf 19(6):3106\u20133129","journal-title":"Compr Rev Food Sci Food Saf"},{"issue":"7","key":"1645_CR206","doi-asserted-by":"crossref","first-page":"381","DOI":"10.1038\/s41582-020-0362-2","volume":"16","author":"KD Davis","year":"2020","unstructured":"Davis KD et al (2020) Discovery and validation of biomarkers to aid the development of safe and effective pain therapeutics: challenges and opportunities. Nat Rev Neurol 16(7):381\u2013400","journal-title":"Nat Rev Neurol"},{"issue":"6","key":"1645_CR207","doi-asserted-by":"crossref","first-page":"1151","DOI":"10.1016\/j.copbio.2013.05.001","volume":"24","author":"MM Schofield","year":"2013","unstructured":"Schofield MM, Sherman DH (2013) Meta-omic characterization of prokaryotic gene clusters for natural product biosynthesis. Curr Opin Biotechnol 24(6):1151\u20131158","journal-title":"Curr Opin Biotechnol"},{"issue":"1","key":"1645_CR208","doi-asserted-by":"crossref","first-page":"R21","DOI":"10.1530\/JME-18-0055","volume":"62","author":"BB Misra","year":"2019","unstructured":"Misra BB et al (2019) Integrated omics: tools, advances and future approaches. J Mol Endocrinol 62(1):R21\u2013R45","journal-title":"J Mol Endocrinol"},{"issue":"11","key":"1645_CR209","doi-asserted-by":"crossref","first-page":"1466","DOI":"10.1039\/b817077k","volume":"26","author":"K Yonekura-Sakakibara","year":"2009","unstructured":"Yonekura-Sakakibara K, Saito K (2009) Functional genomics for plant natural product biosynthesis. Nat Prod Rep 26(11):1466\u20131487","journal-title":"Nat Prod Rep"},{"issue":"1","key":"1645_CR210","doi-asserted-by":"crossref","first-page":"197","DOI":"10.3390\/microorganisms9010197","volume":"9","author":"A Singh","year":"2021","unstructured":"Singh A et al (2021) Fungal endophytes as efficient sources of plant-derived bioactive compounds and their prospective applications in natural product drug discovery: Insights, avenues, and challenges. Microorganisms 9(1):197","journal-title":"Microorganisms"},{"key":"1645_CR211","doi-asserted-by":"crossref","first-page":"58","DOI":"10.3389\/fmicb.2015.00058","volume":"6","author":"K Papadimitriou","year":"2015","unstructured":"Papadimitriou K et al (2015) Discovering probiotic microorganisms: in vitro, in vivo, genetic and omics approaches. Front Microbiol 6:58","journal-title":"Front Microbiol"},{"issue":"5","key":"1645_CR212","doi-asserted-by":"crossref","first-page":"269","DOI":"10.3390\/md17050269","volume":"17","author":"C Lauritano","year":"2019","unstructured":"Lauritano C, Ferrante MI, Rogato A (2019) Marine natural products from microalgae: An-omics overview. Mar Drugs 17(5):269","journal-title":"Mar Drugs"},{"key":"1645_CR213","unstructured":"Verma P. and Shah MP., 2022 Bioprospecting of microbial diversity: challenges and applications in biochemical industry agriculture and environment protection"},{"issue":"3\u20134","key":"1645_CR214","doi-asserted-by":"crossref","first-page":"2000235","DOI":"10.1002\/pmic.202000235","volume":"21","author":"TD Veenstra","year":"2021","unstructured":"Veenstra TD (2021) Omics in systems biology: current progress and future outlook. Proteomics 21(3\u20134):2000235","journal-title":"Proteomics"},{"issue":"7","key":"1645_CR215","doi-asserted-by":"crossref","first-page":"997","DOI":"10.3390\/biology12070997","volume":"12","author":"H Satam","year":"2023","unstructured":"Satam H et al (2023) Next-generation sequencing technology: current trends and advancements. Biology 12(7):997","journal-title":"Biology"},{"issue":"3","key":"1645_CR216","doi-asserted-by":"crossref","first-page":"191","DOI":"10.1504\/IJBRA.2019.10022508","volume":"15","author":"K Raza","year":"2019","unstructured":"Raza K, Ahmad S (2019) Recent advancement in next-generation sequencing techniques and its computational analysis. Int J Bioinform Res Appl 15(3):191\u2013220","journal-title":"Int J Bioinform Res Appl"},{"issue":"6","key":"1645_CR217","doi-asserted-by":"crossref","first-page":"1440","DOI":"10.3390\/cells9061440","volume":"9","author":"WN Lin","year":"2020","unstructured":"Lin WN et al (2020) The role of single-cell technology in the study and control of infectious diseases. Cells 9(6):1440","journal-title":"Cells"},{"key":"1645_CR218","doi-asserted-by":"crossref","first-page":"115077","DOI":"10.1016\/j.biopha.2023.115077","volume":"165","author":"N Erfanian","year":"2023","unstructured":"Erfanian N et al (2023) Deep learning applications in single-cell genomics and transcriptomics data analysis. Biomed Pharmacother 165:115077","journal-title":"Biomed Pharmacother"},{"issue":"1","key":"1645_CR219","doi-asserted-by":"crossref","first-page":"49","DOI":"10.1093\/bfgp\/elx018","volume":"17","author":"LT Kagohara","year":"2018","unstructured":"Kagohara LT et al (2018) Epigenetic regulation of gene expression in cancer: techniques, resources and analysis. Brief Funct Genomics 17(1):49\u201363","journal-title":"Brief Funct Genomics"},{"key":"1645_CR220","doi-asserted-by":"crossref","unstructured":"Joshi A, and Romanowska J., 2020 Recent advances in computational-based approaches in epigenetics studies. Epigenetics Methods. 569\u2013590","DOI":"10.1016\/B978-0-12-819414-0.00028-8"},{"issue":"11","key":"1645_CR221","doi-asserted-by":"crossref","first-page":"895","DOI":"10.1038\/s41573-023-00774-7","volume":"22","author":"MW Mullowney","year":"2023","unstructured":"Mullowney MW et al (2023) Artificial intelligence for natural product drug discovery. Nat Rev Drug Discovery 22(11):895\u2013916","journal-title":"Nat Rev Drug Discovery"},{"key":"1645_CR222","doi-asserted-by":"crossref","unstructured":"Manochkumar J, et al., 2023 A critical review of machine-learning for \u201cmulti-omics\u201d marine metabolite datasets. Comput Biol Med. 107425","DOI":"10.1016\/j.compbiomed.2023.107425"},{"issue":"6","key":"1645_CR223","doi-asserted-by":"crossref","first-page":"1526","DOI":"10.1039\/D1SC04471K","volume":"13","author":"F Sald\u00edvar-Gonz\u00e1lez","year":"2022","unstructured":"Sald\u00edvar-Gonz\u00e1lez F et al (2022) Natural product drug discovery in the artificial intelligence era. Chem Sci 13(6):1526\u20131546","journal-title":"Chem Sci"},{"issue":"5","key":"1645_CR224","doi-asserted-by":"crossref","first-page":"1574","DOI":"10.1039\/C7CS00368D","volume":"47","author":"AE Brunetti","year":"2018","unstructured":"Brunetti AE et al (2018) An integrative omics perspective for the analysis of chemical signals in ecological interactions. Chem Soc Rev 47(5):1574\u20131591","journal-title":"Chem Soc Rev"},{"issue":"2","key":"1645_CR225","doi-asserted-by":"crossref","first-page":"212","DOI":"10.1080\/1040841X.2017.1332003","volume":"44","author":"J Gutleben","year":"2018","unstructured":"Gutleben J et al (2018) The multi-omics promise in context: from sequence to microbial isolate. Crit Rev Microbiol 44(2):212\u2013229","journal-title":"Crit Rev Microbiol"},{"issue":"1","key":"1645_CR226","doi-asserted-by":"crossref","first-page":"e202100032","DOI":"10.1002\/anse.202100032","volume":"2","author":"M Dolatmoradi","year":"2022","unstructured":"Dolatmoradi M, Samarah LZ, Vertes A (2022) Single-Cell Metabolomics by Mass Spectrometry: Opportunities and Challenges. Analysis & Sensing 2(1):e202100032","journal-title":"Analysis & Sensing"},{"key":"1645_CR227","doi-asserted-by":"crossref","first-page":"2493","DOI":"10.1007\/s00216-010-3850-1","volume":"398","author":"A Amantonico","year":"2010","unstructured":"Amantonico A, Urban PL, Zenobi R (2010) Analytical techniques for single-cell metabolomics: state of the art and trends. Anal Bioanal Chem 398:2493\u20132504","journal-title":"Anal Bioanal Chem"},{"key":"1645_CR228","doi-asserted-by":"crossref","first-page":"890","DOI":"10.3389\/fmicb.2015.00890","volume":"6","author":"M Trindade","year":"2015","unstructured":"Trindade M et al (2015) Targeted metagenomics as a tool to tap into marine natural product diversity for the discovery and production of drug candidates. Front Microbiol 6:890","journal-title":"Front Microbiol"},{"issue":"2","key":"1645_CR229","doi-asserted-by":"crossref","first-page":"92","DOI":"10.1016\/j.synbio.2020.05.003","volume":"5","author":"Y Tong","year":"2020","unstructured":"Tong Y, Deng Z (2020) An aurora of natural products-based drug discovery is coming. Synth Syst Biotechnol 5(2):92\u201396","journal-title":"Synth Syst Biotechnol"},{"issue":"5","key":"1645_CR230","doi-asserted-by":"crossref","first-page":"632","DOI":"10.3390\/ijms17050632","volume":"17","author":"I Aretz","year":"2016","unstructured":"Aretz I, Meierhofer D (2016) Advantages and pitfalls of mass spectrometry based metabolome profiling in systems biology. Int J Mol Sci 17(5):632","journal-title":"Int J Mol Sci"},{"key":"1645_CR231","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1186\/s12711-016-0217-x","volume":"48","author":"P Suravajhala","year":"2016","unstructured":"Suravajhala P, Kogelman LJ, Kadarmideen HN (2016) Multi-omic data integration and analysis using systems genomics approaches: methods and applications in animal production, health and welfare. Genet Sel Evol 48:1\u201314","journal-title":"Genet Sel Evol"},{"issue":"19","key":"1645_CR232","doi-asserted-by":"crossref","first-page":"2714","DOI":"10.3390\/plants13192714","volume":"13","author":"S Haidar","year":"2024","unstructured":"Haidar S et al (2024) Harnessing Multi-Omics Strategies and Bioinformatics Innovations for Advancing Soybean Improvement: A Comprehensive Review. Plants 13(19):2714","journal-title":"Plants"},{"issue":"11","key":"1645_CR233","doi-asserted-by":"crossref","first-page":"848","DOI":"10.3390\/biology13110848","volume":"13","author":"PHG Sanches","year":"2024","unstructured":"Sanches PHG et al (2024) Integrating molecular perspectives: strategies for comprehensive multi-omics integrative data analysis and machine learning applications in transcriptomics, proteomics, and metabolomics. Biology 13(11):848","journal-title":"Biology"},{"issue":"5","key":"1645_CR234","doi-asserted-by":"crossref","first-page":"549","DOI":"10.1093\/bfgp\/elae013","volume":"23","author":"D Acharya","year":"2024","unstructured":"Acharya D, Mukhopadhyay A (2024) A comprehensive review of machine learning techniques for multi-omics data integration: challenges and applications in precision oncology. Brief Funct Genomics 23(5):549\u2013560","journal-title":"Brief Funct Genomics"},{"key":"1645_CR235","doi-asserted-by":"crossref","DOI":"10.3389\/fmars.2020.613471","volume":"7","author":"M Reverter","year":"2020","unstructured":"Reverter M et al (2020) Metabolomics and marine biotechnology: coupling metabolite profiling and organism biology for the discovery of new compounds. Front Mar Sci 7:613471","journal-title":"Front Mar Sci"},{"issue":"10","key":"1645_CR236","doi-asserted-by":"crossref","first-page":"3140","DOI":"10.3390\/nu12103140","volume":"12","author":"L Khorraminezhad","year":"2020","unstructured":"Khorraminezhad L et al (2020) Statistical and machine-learning analyses in nutritional genomics studies. Nutrients 12(10):3140","journal-title":"Nutrients"}],"container-title":["Functional &amp; Integrative Genomics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10142-025-01645-7.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s10142-025-01645-7","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10142-025-01645-7.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,1,23]],"date-time":"2026-01-23T08:10:06Z","timestamp":1769155806000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s10142-025-01645-7"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,6,19]]},"references-count":236,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2025,12]]}},"alternative-id":["1645"],"URL":"https:\/\/doi.org\/10.1007\/s10142-025-01645-7","relation":{},"ISSN":["1438-793X","1438-7948"],"issn-type":[{"value":"1438-793X","type":"print"},{"value":"1438-7948","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,6,19]]},"assertion":[{"value":"2 January 2025","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"25 March 2025","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"11 June 2025","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"19 June 2025","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"No animal and human data was incorporated in the manuscript.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethical approval"}},{"value":"Authors did not have any conflict of Interest.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interest"}}],"article-number":"132"}}