{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,10]],"date-time":"2026-06-10T03:16:31Z","timestamp":1781061391208,"version":"3.54.1"},"reference-count":59,"publisher":"Oxford University Press (OUP)","license":[{"start":{"date-parts":[[2024,8,21]],"date-time":"2024-08-21T00:00:00Z","timestamp":1724198400000},"content-version":"vor","delay-in-days":233,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100020703","name":"Centre for Agricultural Bioinformatics","doi-asserted-by":"publisher","award":["1006456"],"award-info":[{"award-number":["1006456"]}],"id":[{"id":"10.13039\/501100020703","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100020703","name":"Centre for Agricultural Bioinformatics","doi-asserted-by":"publisher","award":["1006456"],"award-info":[{"award-number":["1006456"]}],"id":[{"id":"10.13039\/501100020703","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024,8,21]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>MicroRNAs are key players involved in stress responses in plants and reports are available on the role of miRNAs in drought stress response in rice. This work reports the development of a database, RiceMetaSys: Drought-miR, based on the meta-analysis of publicly available sRNA datasets. From 28 drought stress-specific sRNA datasets, we identified 216 drought-responsive miRNAs (DRMs). The major features of the database include genotype-, tissue- and miRNA ID-specific search options and comparison of genotypes to identify common miRNAs. Co-localization of the DRMs with the known quantitative trait loci (QTLs), i.e., meta-QTL regions governing drought tolerance in rice pertaining to different drought adaptive traits, narrowed down this to 37 promising DRMs. To identify the high confidence target genes of DRMs under drought stress, degradome datasets and web resource on drought-responsive genes (RiceMetaSys: DRG) were used. Out of the 216 unique DRMs, only 193 had targets with high stringent parameters. Out of the 1081 target genes identified by Degradome datasets, 730 showed differential expression under drought stress in at least one accession. To retrieve complete information on the target genes, the database has been linked with RiceMetaSys: DRG. Further, we updated the RiceMetaSys: DRGv1 developed earlier with the addition of DRGs identified from RNA-seq datasets from five rice genotypes. We also identified 759 putative novel miRNAs and their target genes employing stringent criteria. Novel miRNA search has all the search options of known miRNAs and additionally, it gives information on their in silico validation features. Simple sequence repeat markers for both the miRNAs and their target genes have also been designed and made available in the database. Network analysis of the target genes identified 60 hub genes which primarily act through abscisic acid pathway and jasmonic acid pathway. Co-localization of the hub genes with the meta-QTL regions governing drought tolerance narrowed down this to 16 most promising DRGs.<\/jats:p>\n               <jats:p>Database URL: http:\/\/14.139.229.201\/RiceMetaSys_miRNA<\/jats:p>\n               <jats:p>Updated database of RiceMetaSys URL: http:\/\/14.139.229.201\/RiceMetaSysA\/Drought\/<\/jats:p>","DOI":"10.1093\/database\/baae076","type":"journal-article","created":{"date-parts":[[2024,8,22]],"date-time":"2024-08-22T02:13:25Z","timestamp":1724292805000},"source":"Crossref","is-referenced-by-count":3,"title":["RiceMetaSys: Drought-miR, a one-stop solution for drought responsive miRNAs-mRNA module in rice"],"prefix":"10.1093","volume":"2024","author":[{"given":"Deepesh","family":"Kumar","sequence":"first","affiliation":[{"name":"ICAR-National Institute for Plant Biotechnology , Pusa Campus, New Delhi 110012, India"},{"name":"The Graduate School, ICAR-Indian Agricultural Research Institute , Pusa Campus, New Delhi 110012, India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8941-2014","authenticated-orcid":false,"given":"SureshKumar","family":"Venkadesan","sequence":"additional","affiliation":[{"name":"ICAR-National Institute for Plant Biotechnology , Pusa Campus, New Delhi 110012, India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ratna","family":"Prabha","sequence":"additional","affiliation":[{"name":"AKMU, ICAR-Indian Agricultural Research Institute , Pusa Campus, New Delhi 110012, India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shbana","family":"Begam","sequence":"additional","affiliation":[{"name":"ICAR-National Institute for Plant Biotechnology , Pusa Campus, New Delhi 110012, India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bipratip","family":"Dutta","sequence":"additional","affiliation":[{"name":"ICAR-National Institute for Plant Biotechnology , Pusa Campus, New Delhi 110012, India"},{"name":"The Graduate School, ICAR-Indian Agricultural Research Institute , Pusa Campus, New Delhi 110012, India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Dwijesh C","family":"Mishra","sequence":"additional","affiliation":[{"name":"ICAR-Indian Agricultural Statistics Research Institute , Pusa Campus, New Delhi 110012, India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"K K","family":"Chaturvedi","sequence":"additional","affiliation":[{"name":"ICAR-Indian Agricultural Statistics Research Institute , Pusa Campus, New Delhi 110012, India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Girish Kumar","family":"Jha","sequence":"additional","affiliation":[{"name":"ICAR-Indian Agricultural Statistics Research Institute , Pusa Campus, New Delhi 110012, India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Amolkumar U","family":"Solanke","sequence":"additional","affiliation":[{"name":"ICAR-National Institute for Plant Biotechnology , Pusa Campus, New Delhi 110012, India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8447-9148","authenticated-orcid":false,"given":"Amitha Mithra","family":"Sevanthi","sequence":"additional","affiliation":[{"name":"ICAR-National Institute for Plant Biotechnology , Pusa Campus, New Delhi 110012, India"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"286","published-online":{"date-parts":[[2024,8,21]]},"reference":[{"key":"2024082804070204200_R1","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1186\/s12284-019-0349-z","article-title":"Identification of genes for salt tolerance and yield-related traits in rice plants grown hydroponically and under saline field conditions by genome-wide association study","volume":"12","author":"Liu","year":"2019","journal-title":"Rice"},{"key":"2024082804070204200_R2","doi-asserted-by":"crossref","DOI":"10.1038\/s41598-021-89812-1","article-title":"Spermine mediated improvements on stomatal features, growth, grain filling and yield of rice under differing water availability","volume":"11","author":"Berahim","year":"2021","journal-title":"Sci Rep"},{"key":"2024082804070204200_R3","doi-asserted-by":"crossref","DOI":"10.1186\/s12864-023-09609-6","article-title":"Integration of miRNA dynamics and drought tolerant QTLs in rice reveals the role of miR2919 in drought stress response","volume":"24","author":"Kumar","year":"2023","journal-title":"BMC Genomics"},{"key":"2024082804070204200_R4","doi-asserted-by":"crossref","first-page":"221","DOI":"10.1093\/jxb\/erl164","article-title":"Gene networks involved in drought stress response and tolerance","volume":"58","author":"Shinozaki","year":"2007","journal-title":"J Exp Bot"},{"key":"2024082804070204200_R5","first-page":"62","article-title":"Drought adaptive mechanisms of plants\u2014a review","volume":"2","author":"Abobatta","year":"2019","journal-title":"Adv Agric Environ Sci"},{"key":"2024082804070204200_R6","doi-asserted-by":"crossref","DOI":"10.1371\/journal.pone.0062795","article-title":"Genetic, physiological, and gene expression analyses reveal that multiple QTL enhance yield of rice mega-variety IR64 under drought","volume":"8","author":"Swamy","year":"2013","journal-title":"PloS One"},{"key":"2024082804070204200_R7","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1186\/s12284-018-0227-0","article-title":"Marker-assisted selection strategy to pyramid two or more QTLs for quantitative trait-grain yield under drought","volume":"11","author":"Kumar","year":"2018","journal-title":"Rice"},{"key":"2024082804070204200_R8","article-title":"MicroRNA: noncoding but still coding, another example of self-catalysis","volume":"23","author":"Kaur","year":"2023","journal-title":"Funct Integrat Genomics"},{"key":"2024082804070204200_R9","doi-asserted-by":"crossref","DOI":"10.3390\/ijms20153766","article-title":"Drought response in rice: the miRNA story","volume":"20","author":"Nadarajah","year":"2019","journal-title":"Int J Mol Sci"},{"key":"2024082804070204200_R10","doi-asserted-by":"crossref","first-page":"1617","DOI":"10.1007\/s00299-021-02736-y","article-title":"miRNAs play critical roles in response to abiotic stress by modulating cross-talk of phytohormone signaling","volume":"40","author":"Singh","year":"2021","journal-title":"Plant Cell Rep"},{"key":"2024082804070204200_R11","doi-asserted-by":"crossref","first-page":"217","DOI":"10.1111\/plb.13361","article-title":"Significance of miRNA in enhancement of flavonoid biosynthesis","volume":"24","author":"Yang","year":"2022","journal-title":"Plant Biol"},{"key":"2024082804070204200_R12","article-title":"MicroRNAs are involved in regulating plant development and stress response through fine-tuning of TIR1\/AFB-dependent auxin signaling","volume":"23","author":"Luo","year":"2022","journal-title":"Int J Mol Sci"},{"key":"2024082804070204200_R13","article-title":"Biogenesis to functional significance of microRNAs under drought stress in rice: recent advances and future perspectives","volume":"l12","author":"Kaur","year":"2024","journal-title":"Plant Stress"},{"key":"2024082804070204200_R14","doi-asserted-by":"crossref","first-page":"585","DOI":"10.1016\/j.bbrc.2007.01.022","article-title":"Identification of drought-induced microRNAs in rice","volume":"354","author":"Zhao","year":"2007","journal-title":"Biochem Biophys Res Commun"},{"key":"2024082804070204200_R15","doi-asserted-by":"crossref","DOI":"10.1016\/j.stress.2023.100302","article-title":"Understanding the role of miRNAs in governing the drought sensitive response of a rice mega variety, swarna at reproductive stage","volume":"11","author":"Kumar","year":"2024","journal-title":"Plant Stress"},{"key":"2024082804070204200_R16","doi-asserted-by":"crossref","first-page":"D155","DOI":"10.1093\/nar\/gky1141","article-title":"miRBase: from microRNA sequences to function","volume":"47","author":"Kozomara","year":"2019","journal-title":"Nucleic Acids Res"},{"key":"2024082804070204200_R17","doi-asserted-by":"crossref","DOI":"10.3389\/fpls.2018.00602","article-title":"ARMOUR\u2013a rice miRNA: mRNA interaction resource","volume":"9","author":"Sanan-Mishra","year":"2018","journal-title":"Front Plant Sci"},{"key":"2024082804070204200_R18","doi-asserted-by":"crossref","first-page":"D1114","DOI":"10.1093\/nar\/gkz894","article-title":"PmiREN: a comprehensive encyclopedia of plant miRNAs","volume":"48","author":"Guo","year":"2020","journal-title":"Nucleic Acids Res"},{"key":"2024082804070204200_R19","doi-asserted-by":"crossref","first-page":"D1475","DOI":"10.1093\/nar\/gkab811","article-title":"PmiREN2. 0: from data annotation to functional exploration of plant microRNAs","volume":"50","author":"Guo","year":"2022","journal-title":"Nucleic Acids Res"},{"key":"2024082804070204200_R20","article-title":"FastQC: a quality control tool for high throughput sequence data","author":"Andrews","year":"2010"},{"key":"2024082804070204200_R21","article-title":"Trim Galore!: a wrapper tool around Cutadapt and FastQC to consistently apply quality and adapter trimming to FastQ files","author":"Krueger","year":"2018"},{"key":"2024082804070204200_R22","doi-asserted-by":"crossref","first-page":"37","DOI":"10.1093\/nar\/gkr688","article-title":"miRDeep2 accurately identifies known and hundreds of novel microRNA genes in seven animal clades","volume":"40","author":"Friedl\u00e4nder","year":"2012","journal-title":"Nucleic Acids Res"},{"key":"2024082804070204200_R23","doi-asserted-by":"crossref","first-page":"740","DOI":"10.1261\/rna.035279.112","article-title":"ShortStack: comprehensive annotation and quantification of small RNA genes","volume":"19","author":"Axtell","year":"2013","journal-title":"Rna"},{"key":"2024082804070204200_R24","doi-asserted-by":"crossref","first-page":"3186","DOI":"10.1105\/tpc.108.064311","article-title":"Criteria for annotation of plant MicroRNAs","volume":"20","author":"Meyers","year":"2008","journal-title":"The Plant Cell"},{"key":"2024082804070204200_R25","doi-asserted-by":"crossref","first-page":"272","DOI":"10.1105\/tpc.17.00851","article-title":"Revisiting criteria for plant microRNA annotation in the era of big data","volume":"30","author":"Axtell","year":"2018","journal-title":"The Plant Cell"},{"key":"2024082804070204200_R26","doi-asserted-by":"crossref","first-page":"W49","DOI":"10.1093\/nar\/gky316","article-title":"psRNATarget: a plant small RNA target analysis server (2017 release)","volume":"46","author":"Dai","year":"2018","journal-title":"Nucleic Acids Res"},{"key":"2024082804070204200_R27","doi-asserted-by":"crossref","first-page":"139","DOI":"10.1093\/bioinformatics\/btp616","article-title":"edgeR: a Bioconductor package for differential expression analysis of digital gene expression data","volume":"26","author":"Robinson","year":"2010","journal-title":"bioinformatics"},{"key":"2024082804070204200_R28","doi-asserted-by":"crossref","first-page":"130","DOI":"10.1093\/bioinformatics\/btn604","article-title":"CleaveLand: a pipeline for using degradome data to find cleaved small RNA targets","volume":"25","author":"Addo-Quaye","year":"2009","journal-title":"Bioinformatics"},{"key":"2024082804070204200_R29","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1186\/s12859-017-1846-y","article-title":"RiceMetaSys for salt and drought stress responsive genes in rice: a web interface for crop improvement","volume":"18","author":"Sandhu","year":"2017","journal-title":"BMC Bioinf"},{"key":"2024082804070204200_R30","doi-asserted-by":"crossref","first-page":"W122","DOI":"10.1093\/nar\/gkx382","article-title":"agriGO v2. 0: a GO analysis toolkit for the agricultural community, 2017 update","volume":"45","author":"Tian","year":"2017","journal-title":"Nucleic Acids Res"},{"key":"2024082804070204200_R31","doi-asserted-by":"crossref","first-page":"W317","DOI":"10.1093\/nar\/gkab447","article-title":"KOBAS-i: intelligent prioritization and exploratory visualization of biological functions for gene enrichment analysis","volume":"49","author":"Bu","year":"2021","journal-title":"Nucleic Acids Res"},{"key":"2024082804070204200_R32","doi-asserted-by":"crossref","first-page":"1667","DOI":"10.1016\/j.molp.2016.09.014","article-title":"iTAK: a program for genome-wide prediction and classification of plant transcription factors, transcriptional regulators, and protein kinases","volume":"9","author":"Zheng","year":"2016","journal-title":"Mol Plant"},{"key":"2024082804070204200_R33","doi-asserted-by":"crossref","first-page":"D1214","DOI":"10.1093\/nar\/gks1122","article-title":"RiceFREND: a platform for retrieving coexpressed gene networks in rice","volume":"41","author":"Sato","year":"2013","journal-title":"Nucleic Acids Res"},{"key":"2024082804070204200_R34","doi-asserted-by":"crossref","first-page":"2498","DOI":"10.1101\/gr.1239303","article-title":"Cytoscape: a software environment for integrated models of biomolecular interaction networks","volume":"13","author":"Shannon","year":"2003","journal-title":"Genome Res"},{"key":"2024082804070204200_R35","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1186\/1752-0509-8-S4-S11","article-title":"cytoHubba: identifying hub objects and sub-networks from complex interactome","volume":"8","author":"Chin","year":"2014","journal-title":"BMC Syst. Biol."},{"key":"2024082804070204200_R36","doi-asserted-by":"crossref","DOI":"10.12688\/f1000research.4477.1","article-title":"Biological network analysis with CentiScaPe: centralities and experimental dataset integration","volume":"3","author":"Scardoni","year":"2014","journal-title":"F1000Research"},{"key":"2024082804070204200_R37","doi-asserted-by":"crossref","DOI":"10.1038\/s41598-021-86259-2","article-title":"Meta-QTL and ortho-MQTL analyses identified genomic regions controlling rice yield, yield-related traits and root architecture under water deficit conditions","volume":"11","author":"Khahani","year":"2021","journal-title":"Sci Rep"},{"key":"2024082804070204200_R38","doi-asserted-by":"crossref","first-page":"D1206","DOI":"10.1093\/nar\/gks1125","article-title":"RiceXPro version 3.0: expanding the informatics resource for rice transcriptome","volume":"41","author":"Sato","year":"2013","journal-title":"Nucleic Acids Res"},{"key":"2024082804070204200_R39","doi-asserted-by":"crossref","first-page":"841","DOI":"10.1093\/bioinformatics\/btq033","article-title":"BEDTools: a flexible suite of utilities for comparing genomic features","volume":"26","author":"Quinlan","year":"2010","journal-title":"Bioinformatics"},{"key":"2024082804070204200_R40","doi-asserted-by":"crossref","DOI":"10.3389\/fpls.2023.1219055","article-title":"MegaSSR: a web server for large scale microsatellite identification, classification, and marker development","volume":"14","author":"Mokhtar","year":"2023","journal-title":"Front Plant Sci"},{"key":"2024082804070204200_R41","doi-asserted-by":"crossref","DOI":"10.1038\/srep23719","article-title":"Transcriptome analysis in different rice cultivars provides novel insights into desiccation and salinity stress responses","volume":"6","author":"Shankar","year":"2016","journal-title":"Sci Rep"},{"key":"2024082804070204200_R42","doi-asserted-by":"crossref","DOI":"10.1111\/ppl.13585","article-title":"Variety-specific transcript accumulation during reproductive stage in drought-stressed rice","volume":"174","author":"Gour","year":"2022","journal-title":"Physiol Plant"},{"key":"2024082804070204200_R43","doi-asserted-by":"crossref","DOI":"10.3390\/ijms24021002","article-title":"Transcriptome and physio-biochemical profiling reveals differential responses of rice cultivars at reproductive-stage drought stress","volume":"24","author":"Kaur","year":"2023","journal-title":"Int J Mol Sci"},{"key":"2024082804070204200_R44","doi-asserted-by":"crossref","first-page":"5780","DOI":"10.1007\/s00344-023-10964-7","article-title":"Differential transcriptional regulation of drought stress revealed by comparative RNA-seq analysis of contrasting indica rice from North East India","volume":"42","author":"Sahoo","year":"2023","journal-title":"J Plant Growth Regul"},{"key":"2024082804070204200_R45","doi-asserted-by":"crossref","first-page":"W29","DOI":"10.1093\/nar\/gkr367","article-title":"HMMER web server: interactive sequence similarity searching","volume":"39","author":"Finn","year":"2011","journal-title":"Nucleic Acids Res"},{"key":"2024082804070204200_R46","doi-asserted-by":"crossref","DOI":"10.3390\/plants12233982","article-title":"The multifaceted role of jasmonic acid in plant stress mitigation: an overview","volume":"12","author":"Rehman","year":"2023","journal-title":"Plants"},{"key":"2024082804070204200_R47","doi-asserted-by":"crossref","first-page":"120","DOI":"10.1016\/j.cj.2020.06.002","article-title":"Abscisic acid and jasmonic acid are involved in drought priming-induced tolerance to drought in wheat","volume":"9","author":"Wang","year":"2021","journal-title":"Crop J"},{"key":"2024082804070204200_R48","doi-asserted-by":"crossref","DOI":"10.1007\/s13205-022-03182-7","article-title":"Identification of major candidate genes for multiple abiotic stress tolerance at seedling stage by network analysis and their validation by expression profiling in rice (Oryza sativa L.)","volume":"12","author":"Ramkumar","year":"2022","journal-title":"3 Biotech"},{"key":"2024082804070204200_R49","doi-asserted-by":"crossref","first-page":"2079","DOI":"10.1111\/pbi.14326","article-title":"miR396b\/GRF6 module contributes to salt tolerance in rice","volume":"22","author":"Yuan","year":"2024","journal-title":"Plant Biotechnol J"},{"key":"2024082804070204200_R50","doi-asserted-by":"crossref","DOI":"10.3389\/fpls.2021.751965","article-title":"OsWAK112, a wall-associated kinase, negatively regulates salt stress responses by inhibiting ethylene production","volume":"12","author":"Lin","year":"2021","journal-title":"Front Plant Sci"},{"key":"2024082804070204200_R51","doi-asserted-by":"crossref","first-page":"113","DOI":"10.1016\/j.rsci.2023.01.004","article-title":"Peptide transporter OsNPF8. 1 contributes to sustainable growth under salt and drought stresses, and grain yield under nitrogen deficiency in rice","volume":"30","author":"Diyang","year":"2023","journal-title":"Rice Sci"},{"key":"2024082804070204200_R52","doi-asserted-by":"crossref","DOI":"10.3390\/plants12081697","article-title":"Meta-analysis of microarray data and their utility in dissecting the mapped QTLs for heat acclimation in rice","volume":"12","author":"Singh","year":"2023","journal-title":"Plants"},{"key":"2024082804070204200_R53","doi-asserted-by":"crossref","DOI":"10.1093\/database\/baz015","article-title":"RiceMetaSysB: a database of blast and bacterial blight responsive genes in rice and its utilization in identifying key blast-resistant WRKY genes","volume":"2019","author":"Sureshkumar","year":"2019","journal-title":"Database"},{"key":"2024082804070204200_R54","doi-asserted-by":"crossref","first-page":"891","DOI":"10.1111\/j.1365-313X.2012.04922.x","article-title":"SoMART: a web server for plant miRNA, tasiRNA and target gene analysis","volume":"70","author":"Li","year":"2012","journal-title":"Plant J"},{"key":"2024082804070204200_R55","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1186\/1471-2229-13-33","article-title":"PASmiR: a literature-curated database for miRNA molecular regulation in plant response to abiotic stress","volume":"13","author":"Zhang","year":"2013","journal-title":"BMC Plant Biol"},{"key":"2024082804070204200_R56","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1186\/1471-2105-14-174","article-title":"PMTED: a plant microRNA target expression database","volume":"14","author":"Sun","year":"2013","journal-title":"BMC Bioinf"},{"key":"2024082804070204200_R57","doi-asserted-by":"crossref","first-page":"D982","DOI":"10.1093\/nar\/gku1162","article-title":"PNRD: a plant non-coding RNA database","volume":"43","author":"Yi","year":"2015","journal-title":"Nucleic Acids Res"},{"key":"2024082804070204200_R58","doi-asserted-by":"crossref","DOI":"10.1093\/database\/baw060","article-title":"PmiRExAt: plant miRNA expression atlas database and web applications","volume":"2016","author":"Gurjar","year":"2016","journal-title":"Database"},{"key":"2024082804070204200_R59","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1186\/s12863-021-00963-6","article-title":"TarDB: an online database for plant miRNA targets and miRNA-triggered phased siRNAs","volume":"22","author":"Liu","year":"2021","journal-title":"BMC Genomics"}],"container-title":["Database"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/academic.oup.com\/database\/article-pdf\/doi\/10.1093\/database\/baae076\/58937588\/baae076.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/database\/article-pdf\/doi\/10.1093\/database\/baae076\/58937588\/baae076.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,8,28]],"date-time":"2024-08-28T04:08:26Z","timestamp":1724818106000},"score":1,"resource":{"primary":{"URL":"https:\/\/academic.oup.com\/database\/article\/doi\/10.1093\/database\/baae076\/7738175"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024]]},"references-count":59,"URL":"https:\/\/doi.org\/10.1093\/database\/baae076","relation":{},"ISSN":["1758-0463"],"issn-type":[{"value":"1758-0463","type":"electronic"}],"subject":[],"published-other":{"date-parts":[[2024]]},"published":{"date-parts":[[2024]]},"article-number":"baae076"}}