{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,5]],"date-time":"2026-03-05T10:55:52Z","timestamp":1772708152663,"version":"3.50.1"},"reference-count":146,"publisher":"Oxford University Press (OUP)","issue":"2","license":[{"start":{"date-parts":[[2019,1,15]],"date-time":"2019-01-15T00:00:00Z","timestamp":1547510400000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["81872798"],"award-info":[{"award-number":["81872798"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012166","name":"National Key Research and Development Program of China","doi-asserted-by":"publisher","award":["2018YFC0910500"],"award-info":[{"award-number":["2018YFC0910500"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Innovation Project on Industrial Generic Key Technologies of Chongqing","award":["cstc2015zdcy-ztzx120003"],"award-info":[{"award-number":["cstc2015zdcy-ztzx120003"]}]},{"name":"Fundamental Research Funds for Central University","award":["2018QNA7023"],"award-info":[{"award-number":["2018QNA7023"]}]},{"name":"Fundamental Research Funds for Central University","award":["10611CDJXZ238826"],"award-info":[{"award-number":["10611CDJXZ238826"]}]},{"name":"Fundamental Research Funds for Central University","award":["2018CDQYSG0007"],"award-info":[{"award-number":["2018CDQYSG0007"]}]},{"name":"Fundamental Research Funds for Central University","award":["CDJZR14468801"],"award-info":[{"award-number":["CDJZR14468801"]}]},{"name":"Fundamental Research Funds for Central University","award":["CDJKXB14011"],"award-info":[{"award-number":["CDJKXB14011"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2020,3,23]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>Label-free quantification (LFQ) with a specific and sequentially integrated workflow of acquisition technique, quantification tool and processing method has emerged as the popular technique employed in metaproteomic research to provide a comprehensive landscape of the adaptive response of microbes to external stimuli and their interactions with other organisms or host cells. The performance of a specific LFQ workflow is highly dependent on the studied data. Hence, it is essential to discover the most appropriate one for a specific data set. However, it is challenging to perform such discovery due to the large number of possible workflows and the multifaceted nature of the evaluation criteria. Herein, a web server ANPELA (https:\/\/idrblab.org\/anpela\/) was developed and validated as the first tool enabling performance assessment of whole LFQ workflow (collective assessment by five well-established criteria with distinct underlying theories), and it enabled the identification of the optimal LFQ workflow(s) by a comprehensive performance ranking. ANPELA not only automatically detects the diverse formats of data generated by all quantification tools but also provides the most complete set of processing methods among the available web servers and stand-alone tools. Systematic validation using metaproteomic benchmarks revealed ANPELA\u2019s capabilities in 1 discovering well-performing workflow(s), (2) enabling assessment from multiple perspectives and (3) validating LFQ accuracy using spiked proteins. ANPELA has a unique ability to evaluate the performance of whole LFQ workflow and enables the discovery of the optimal LFQs by the comprehensive performance ranking of all 560 workflows. Therefore, it has great potential for applications in metaproteomic and other studies requiring LFQ techniques, as many features are shared among proteomic studies.<\/jats:p>","DOI":"10.1093\/bib\/bby127","type":"journal-article","created":{"date-parts":[[2018,12,7]],"date-time":"2018-12-07T12:08:06Z","timestamp":1544184486000},"page":"621-636","source":"Crossref","is-referenced-by-count":154,"title":["ANPELA: analysis and performance assessment of the label-free quantification workflow for metaproteomic studies"],"prefix":"10.1093","volume":"21","author":[{"given":"Jing","family":"Tang","sequence":"first","affiliation":[{"name":"College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, China"},{"name":"School of Pharmaceutical Sciences and Collaborative Innovation Center for Brain Science, Chongqing University, Chongqing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jianbo","family":"Fu","sequence":"additional","affiliation":[{"name":"College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yunxia","family":"Wang","sequence":"additional","affiliation":[{"name":"College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Bo","family":"Li","sequence":"additional","affiliation":[{"name":"School of Pharmaceutical Sciences and Collaborative Innovation Center for Brain Science, Chongqing University, Chongqing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yinghong","family":"Li","sequence":"additional","affiliation":[{"name":"College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, China"},{"name":"School of Pharmaceutical Sciences and Collaborative Innovation Center for Brain Science, Chongqing University, Chongqing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qingxia","family":"Yang","sequence":"additional","affiliation":[{"name":"College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, China"},{"name":"School of Pharmaceutical Sciences and Collaborative Innovation Center for Brain Science, Chongqing University, Chongqing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xuejiao","family":"Cui","sequence":"additional","affiliation":[{"name":"College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, China"},{"name":"School of Pharmaceutical Sciences and Collaborative Innovation Center for Brain Science, Chongqing University, Chongqing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jiajun","family":"Hong","sequence":"additional","affiliation":[{"name":"College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiaofeng","family":"Li","sequence":"additional","affiliation":[{"name":"College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, China"},{"name":"School of Pharmaceutical Sciences and Collaborative Innovation Center for Brain Science, Chongqing University, Chongqing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yuzong","family":"Chen","sequence":"additional","affiliation":[{"name":"Bioinformatics and Drug Design Group, Department of Pharmacy, National University of Singapore, Singapore, Singapore"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Weiwei","family":"Xue","sequence":"additional","affiliation":[{"name":"School of Pharmaceutical Sciences and Collaborative Innovation Center for Brain Science, Chongqing University, Chongqing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8069-0053","authenticated-orcid":false,"given":"Feng","family":"Zhu","sequence":"additional","affiliation":[{"name":"College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, China"},{"name":"School of Pharmaceutical Sciences and Collaborative Innovation Center for Brain Science, Chongqing University, Chongqing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"286","published-online":{"date-parts":[[2019,1,15]]},"reference":[{"key":"2020080709361982200_ref1","doi-asserted-by":"crossref","first-page":"2557","DOI":"10.1038\/ismej.2016.45","article-title":"Challenges in microbial ecology: building predictive understanding of community function and dynamics","volume":"10","author":"Widder","year":"2016","journal-title":"ISME J"},{"key":"2020080709361982200_ref2","doi-asserted-by":"crossref","first-page":"157","DOI":"10.1186\/s40168-017-0375-2","article-title":"MetaLab: an automated pipeline for metaproteomic data analysis","volume":"5","author":"Cheng","year":"2017","journal-title":"Microbiome"},{"key":"2020080709361982200_ref3","doi-asserted-by":"crossref","first-page":"2369","DOI":"10.1056\/NEJMra1600266","article-title":"The human intestinal microbiome in health and disease","volume":"375","author":"Lynch","year":"2016","journal-title":"N Engl J Med"},{"key":"2020080709361982200_ref4","doi-asserted-by":"crossref","first-page":"228","DOI":"10.1186\/s13059-017-1359-z","article-title":"Experimental design and quantitative analysis of microbial community multiomics","volume":"18","author":"Mallick","year":"2017","journal-title":"Genome Biol"},{"key":"2020080709361982200_ref5","doi-asserted-by":"crossref","first-page":"1674","DOI":"10.1161\/CIRCRESAHA.117.309419","article-title":"Extracellular vesicles in metabolic syndrome","volume":"120","author":"Martinez","year":"2017","journal-title":"Circ Res"},{"key":"2020080709361982200_ref6","doi-asserted-by":"crossref","first-page":"513","DOI":"10.1038\/nature21417","article-title":"Root microbiota drive direct integration of phosphate stress and immunity","volume":"543","author":"Castrillo","year":"2017","journal-title":"Nature"},{"key":"2020080709361982200_ref7","doi-asserted-by":"crossref","first-page":"789","DOI":"10.1038\/nrmicro3109","article-title":"Going back to the roots: the microbial ecology of the rhizosphere","volume":"11","author":"Philippot","year":"2013","journal-title":"Nat Rev Microbiol"},{"key":"2020080709361982200_ref8","doi-asserted-by":"crossref","first-page":"197","DOI":"10.1016\/j.envres.2018.02.006","article-title":"Impact of wastewater effluent containing aged nanoparticles and other components on biological activities of the soil microbiome, Arabidopsis plants, and earthworms","volume":"164","author":"Liu","year":"2018","journal-title":"Environ Res"},{"key":"2020080709361982200_ref9","doi-asserted-by":"crossref","first-page":"1032","DOI":"10.1038\/s41396-018-0062-8","article-title":"Photoautotrophic organisms control microbial abundance, diversity, and physiology in different types of biological soil crusts","volume":"12","author":"Maier","year":"2018","journal-title":"ISME J"},{"key":"2020080709361982200_ref10","doi-asserted-by":"crossref","first-page":"21","DOI":"10.1186\/s40168-018-0408-5","article-title":"Integrated multi-omic analysis of host-microbiota interactions in acute oak decline","volume":"6","author":"Broberg","year":"2018","journal-title":"Microbiome"},{"key":"2020080709361982200_ref11","doi-asserted-by":"crossref","first-page":"E1275","DOI":"10.3390\/ijms17081275","article-title":"Environmental microbial community proteomics: status, challenges and perspectives","volume":"17","author":"Wang","year":"2016","journal-title":"Int J Mol Sci"},{"key":"2020080709361982200_ref12","doi-asserted-by":"crossref","first-page":"6120","DOI":"10.1021\/acs.analchem.6b01412","article-title":"In vitro metabolic labeling of intestinal microbiota for quantitative metaproteomics","volume":"88","author":"Zhang","year":"2016","journal-title":"Anal Chem"},{"key":"2020080709361982200_ref13","doi-asserted-by":"crossref","first-page":"943","DOI":"10.1007\/s00125-017-4278-3","article-title":"The gut microbiome as a target for prevention and treatment of hyperglycaemia in type 2 diabetes: from current human evidence to future possibilities","volume":"60","author":"Brunkwall","year":"2017","journal-title":"Diabetologia"},{"key":"2020080709361982200_ref14","doi-asserted-by":"crossref","first-page":"2160","DOI":"10.1021\/acs.jproteome.6b00974","article-title":"Symbiotic interplay of fungi, algae, and bacteria within the lung lichen Lobaria pulmonaria L. Hoffm. as assessed by state-of-the-art metaproteomics","volume":"16","author":"Eymann","year":"2017","journal-title":"J Proteome Res"},{"key":"2020080709361982200_ref15","doi-asserted-by":"crossref","first-page":"79","DOI":"10.1186\/s40168-017-0293-3","article-title":"Potential and active functions in the gut microbiota of a healthy human cohort","volume":"5","author":"Tanca","year":"2017","journal-title":"Microbiome"},{"key":"2020080709361982200_ref16","doi-asserted-by":"crossref","first-page":"E5576","DOI":"10.1073\/pnas.1722325115","article-title":"Metaproteomics method to determine carbon sources and assimilation pathways of species in microbial communities","volume":"115","author":"Kleiner","year":"2018","journal-title":"Proc Natl Acad Sci U S A"},{"key":"2020080709361982200_ref17","doi-asserted-by":"crossref","first-page":"2873","DOI":"10.1038\/s41467-018-05357-4","article-title":"Metaproteomics reveals associations between microbiome and intestinal extracellular vesicle proteins in pediatric inflammatory bowel disease","volume":"9","author":"Zhang","year":"2018","journal-title":"Nat Commun"},{"key":"2020080709361982200_ref18","doi-asserted-by":"crossref","first-page":"182","DOI":"10.1186\/s40168-018-0567-4","article-title":"Probiotic supplementation restores normal microbiota composition and function in antibiotic-treated and in caesarean-born infants","volume":"6","author":"Korpela","year":"2018","journal-title":"Microbiome"},{"key":"2020080709361982200_ref19","doi-asserted-by":"crossref","first-page":"1877","DOI":"10.1038\/ismej.2013.78","article-title":"Insights from quantitative metaproteomics and protein-stable isotope probing into microbial ecology","volume":"7","author":"Bergen","year":"2013","journal-title":"ISME J"},{"key":"2020080709361982200_ref20","doi-asserted-by":"crossref","first-page":"1130","DOI":"10.1038\/nbt.3685","article-title":"A multicenter study benchmarks software tools for label-free proteome quantification","volume":"34","author":"Navarro","year":"2016","journal-title":"Nat Biotechnol"},{"key":"2020080709361982200_ref21","doi-asserted-by":"crossref","first-page":"1908","DOI":"10.1038\/ismej.2015.93","article-title":"Monitoring host responses to the gut microbiota","volume":"9","author":"Lichtman","year":"2015","journal-title":"ISME J"},{"key":"2020080709361982200_ref22","doi-asserted-by":"crossref","first-page":"2275","DOI":"10.1002\/elps.201700056","article-title":"Phenotyping of gut microbiota: focus on capillary electrophoresis","volume":"38","author":"Ferrer","year":"2017","journal-title":"Electrophoresis"},{"key":"2020080709361982200_ref23","doi-asserted-by":"publisher","DOI":"10.2174\/1381612824666181102125638","article-title":"Computational advances in the label-free quantification of cancer proteomics data","author":"Tang","year":"2018","journal-title":"Curr Pharm Des"},{"key":"2020080709361982200_ref24","doi-asserted-by":"crossref","first-page":"50","DOI":"10.5539\/jmbr.v7n1p50","article-title":"Proteomic approach for extracting cytoplasmic proteins from Streptococcus sanguinis using mass spectrometry","volume":"7","author":"El-Rami","year":"2017","journal-title":"J Mol Biol Res"},{"key":"2020080709361982200_ref25","doi-asserted-by":"crossref","first-page":"e00223","DOI":"10.1128\/mBio.00223-13","article-title":"Metaproteomics reveals abundant transposase expression in mutualistic endosymbionts","volume":"4","author":"Kleiner","year":"2013","journal-title":"MBio"},{"key":"2020080709361982200_ref26","doi-asserted-by":"crossref","first-page":"1582","DOI":"10.1021\/pr200748h","article-title":"Systematic comparison of label-free, metabolic labeling, and isobaric chemical labeling for quantitative proteomics on LTQ Orbitrap Velos","volume":"11","author":"Li","year":"2012","journal-title":"J Proteome Res"},{"key":"2020080709361982200_ref27","doi-asserted-by":"crossref","first-page":"27","DOI":"10.1186\/1559-0275-11-27","article-title":"Identification of psoriatic arthritis mediators in synovial fluid by quantitative mass spectrometry","volume":"11","author":"Cretu","year":"2014","journal-title":"Clin Proteomics"},{"key":"2020080709361982200_ref28","doi-asserted-by":"crossref","first-page":"769","DOI":"10.1080\/14789450.2017.1365602","article-title":"Proteomic studies in the discovery of cerebrospinal fluid biomarkers for amyotrophic lateral sclerosis","volume":"14","author":"Barschke","year":"2017","journal-title":"Expert Rev Proteomics"},{"key":"2020080709361982200_ref29","doi-asserted-by":"crossref","first-page":"1215","DOI":"10.1002\/pmic.201400270","article-title":"SWATH enables precise label-free quantification on proteome scale","volume":"15","author":"Huang","year":"2015","journal-title":"Proteomics"},{"key":"2020080709361982200_ref30","doi-asserted-by":"crossref","first-page":"1936","DOI":"10.1021\/acs.jproteome.6b01014","article-title":"Comparison of false discovery rate control strategies for variant peptide identifications in shotgun proteogenomics","volume":"16","author":"Ivanov","year":"2017","journal-title":"J Proteome Res"},{"key":"2020080709361982200_ref31","doi-asserted-by":"crossref","first-page":"1087","DOI":"10.1007\/s00726-012-1289-8","article-title":"Current challenges in software solutions for mass spectrometry-based quantitative proteomics","volume":"43","author":"Cappadona","year":"2012","journal-title":"Amino Acids"},{"key":"2020080709361982200_ref32","doi-asserted-by":"crossref","first-page":"99","DOI":"10.1586\/14789450.2016.1122529","article-title":"The clinical impact of recent advances in LC-MS for cancer biomarker discovery and verification","volume":"13","author":"Wang","year":"2016","journal-title":"Expert Rev Proteomics"},{"key":"2020080709361982200_ref33","doi-asserted-by":"crossref","first-page":"1410","DOI":"10.1021\/acs.jproteome.6b00645","article-title":"Assessment of label-free quantification in discovery proteomics and impact of technological factors and natural variability of protein abundance","volume":"16","author":"Al Shweiki","year":"2017","journal-title":"J Proteome Res"},{"key":"2020080709361982200_ref34","doi-asserted-by":"crossref","first-page":"E4767","DOI":"10.1073\/pnas.1800541115","article-title":"IonStar enables high-precision, low-missing-data proteomics quantification in large biological cohorts","volume":"115","author":"Shen","year":"2018","journal-title":"Proc Natl Acad Sci U S A"},{"key":"2020080709361982200_ref35","doi-asserted-by":"crossref","first-page":"2324","DOI":"10.1074\/mcp.O112.023804","article-title":"In silico instrumental response correction improves precision of label-free proteomics and accuracy of proteomics-based predictive models","volume":"12","author":"Lyutvinskiy","year":"2013","journal-title":"Mol Cell Proteomics"},{"key":"2020080709361982200_ref36","doi-asserted-by":"crossref","first-page":"1196","DOI":"10.1111\/nph.13312","article-title":"The importance of the microbiome of the plant holobiont","volume":"206","author":"Vandenkoornhuyse","year":"2015","journal-title":"New Phytol"},{"key":"2020080709361982200_ref37","doi-asserted-by":"crossref","first-page":"e54","DOI":"10.1371\/journal.pcbi.0010054","article-title":"Ultrasensitization: switch-like regulation of cellular signaling by transcriptional induction","volume":"1","author":"Legewie","year":"2005","journal-title":"PLoS Comput Biol"},{"key":"2020080709361982200_ref38","doi-asserted-by":"crossref","first-page":"809","DOI":"10.1021\/acs.jproteome.5b00852","article-title":"Testing and validation of computational methods for mass spectrometry","volume":"15","author":"Gatto","year":"2016","journal-title":"J Proteome Res"},{"key":"2020080709361982200_ref39","doi-asserted-by":"crossref","first-page":"D658","DOI":"10.1093\/nar\/gkp933","article-title":"dbDEPC: a database of differentially expressed proteins in human cancers","volume":"38","author":"Li","year":"2010","journal-title":"Nucleic Acids Res"},{"key":"2020080709361982200_ref40","doi-asserted-by":"crossref","first-page":"403","DOI":"10.1007\/s10096-016-2816-4","article-title":"Proteomics progresses in microbial physiology and clinical antimicrobial therapy","volume":"36","author":"Chen","year":"2017","journal-title":"Eur J Clin Microbiol Infect Dis"},{"key":"2020080709361982200_ref41","doi-asserted-by":"crossref","first-page":"989","DOI":"10.1074\/mcp.M114.043463","article-title":"A metaproteomics approach to elucidate host and pathogen protein expression during catheter-associated urinary tract infections (CAUTIs)","volume":"14","author":"Lassek","year":"2015","journal-title":"Mol Cell Proteomics"},{"key":"2020080709361982200_ref42","doi-asserted-by":"crossref","first-page":"144","DOI":"10.1186\/s40168-017-0362-7","article-title":"Dietary changes in nutritional studies shape the structural and functional composition of the pigs\u2019 fecal microbiome-from days to weeks","volume":"5","author":"Tilocca","year":"2017","journal-title":"Microbiome"},{"key":"2020080709361982200_ref43","doi-asserted-by":"crossref","first-page":"749","DOI":"10.1111\/1751-7915.12276","article-title":"Metaproteomics of complex microbial communities in biogas plants","volume":"8","author":"Heyer","year":"2015","journal-title":"J Microbial Biotechnol"},{"key":"2020080709361982200_ref44","doi-asserted-by":"crossref","DOI":"10.1093\/bib\/bbx054","article-title":"A comprehensive evaluation of popular proteomics software workflows for label-free proteome quantification and imputation","author":"Valikangas","year":"2017","journal-title":"Brief Bioinform"},{"key":"2020080709361982200_ref45","doi-asserted-by":"crossref","first-page":"e0150672","DOI":"10.1371\/journal.pone.0150672","article-title":"Analysis of the cerebrospinal fluid proteome in Alzheimer\u2019s disease","volume":"11","author":"Khoonsari","year":"2016","journal-title":"PLoS One"},{"key":"2020080709361982200_ref46","doi-asserted-by":"crossref","first-page":"27","DOI":"10.1186\/s40168-017-0237-y","article-title":"Normalization and microbial differential abundance strategies depend upon data characteristics","volume":"5","author":"Weiss","year":"2017","journal-title":"Microbiome"},{"key":"2020080709361982200_ref47","doi-asserted-by":"crossref","first-page":"606","DOI":"10.1002\/rcm.7829","article-title":"Comparative evaluation of label-free quantification methods for shotgun proteomics","volume":"31","author":"Bubis","year":"2017","journal-title":"Rapid Commun Mass Spectrom"},{"key":"2020080709361982200_ref48","doi-asserted-by":"crossref","first-page":"2261","DOI":"10.1021\/pr201052x","article-title":"Comparative analysis of different label-free mass spectrometry based protein abundance estimates and their correlation with RNA-Seq gene expression data","volume":"11","author":"Ning","year":"2012","journal-title":"J Proteome Res"},{"key":"2020080709361982200_ref49","doi-asserted-by":"crossref","first-page":"676","DOI":"10.1021\/pr500665j","article-title":"Data processing has major impact on the outcome of quantitative label-free LC-MS analysis","volume":"14","author":"Chawade","year":"2015","journal-title":"J Proteome Res"},{"key":"2020080709361982200_ref50","first-page":"1","article-title":"A systematic evaluation of normalization methods in quantitative label-free proteomics","volume":"19","author":"Valikangas","year":"2018","journal-title":"Brief Bioinform"},{"key":"2020080709361982200_ref51","doi-asserted-by":"crossref","first-page":"11395","DOI":"10.1073\/pnas.1322132111","article-title":"Metaproteomics reveals differential modes of metabolic coupling among ubiquitous oxygen minimum zone microbes","volume":"111","author":"Hawley","year":"2014","journal-title":"Proc Natl Acad Sci U S A"},{"key":"2020080709361982200_ref52","doi-asserted-by":"crossref","first-page":"1855","DOI":"10.1016\/j.mayocp.2017.10.004","article-title":"Microbiome at the frontier of personalized medicine","volume":"92","author":"Kashyap","year":"2017","journal-title":"Mayo Clin Proc"},{"key":"2020080709361982200_ref53","doi-asserted-by":"crossref","first-page":"731","DOI":"10.1038\/nmeth.3901","article-title":"The Perseus computational platform for comprehensive analysis of (prote)omics data","volume":"13","author":"Tyanova","year":"2016","journal-title":"Nat Methods"},{"key":"2020080709361982200_ref54","doi-asserted-by":"crossref","first-page":"38178","DOI":"10.1038\/srep38178","article-title":"Mining, visualizing and comparing multidimensional biomolecular data using the Genomics Data Miner (GMine) web-server","volume":"6","author":"Proietti","year":"2016","journal-title":"Sci Rep"},{"issue":"6","key":"2020080709361982200_ref55","doi-asserted-by":"crossref","first-page":"M111.015974","DOI":"10.1074\/mcp.M111.015974","article-title":"msCompare: a framework for quantitative analysis of label-free LC-MS data for comparative candidate biomarker studies","volume":"11","author":"Hoekman","year":"2012","journal-title":"Mol Cell Proteomics"},{"key":"2020080709361982200_ref56","doi-asserted-by":"crossref","first-page":"3114","DOI":"10.1021\/pr401264n","article-title":"Normalyzer: a tool for rapid evaluation of normalization methods for omics data sets","volume":"13","author":"Chawade","year":"2014","journal-title":"J Proteome Res"},{"key":"2020080709361982200_ref57","doi-asserted-by":"crossref","first-page":"4736","DOI":"10.1002\/pmic.201100078","article-title":"A statistical selection strategy for normalization procedures in LC-MS proteomics experiments through dataset-dependent ranking of normalization scaling factors","volume":"11","author":"Webb-Robertson","year":"2011","journal-title":"Proteomics"},{"key":"2020080709361982200_ref58","doi-asserted-by":"crossref","first-page":"1426","DOI":"10.1074\/mcp.TIR117.000438","article-title":"GiaPronto: a one-click graph visualization software for proteomics datasets","volume":"17","author":"Weiner","year":"2018","journal-title":"Mol Cell Proteomics"},{"key":"2020080709361982200_ref59","doi-asserted-by":"crossref","first-page":"E1343","DOI":"10.1073\/pnas.1600645113","article-title":"Quantitative proteomic analyses of mammary organoids reveals distinct signatures after exposure to environmental chemicals","volume":"113","author":"Williams","year":"2016","journal-title":"Proc Natl Acad Sci U S A"},{"key":"2020080709361982200_ref60","doi-asserted-by":"crossref","first-page":"291","DOI":"10.1038\/s41467-017-00249-5","article-title":"Multi-laboratory assessment of reproducibility, qualitative and quantitative performance of SWATH-mass spectrometry","volume":"8","author":"Collins","year":"2017","journal-title":"Nat Commun"},{"key":"2020080709361982200_ref61","doi-asserted-by":"crossref","first-page":"4118","DOI":"10.1021\/acs.jproteome.5b00183","article-title":"Optimization of statistical methods impact on quantitative proteomics data","volume":"14","author":"Pursiheimo","year":"2015","journal-title":"J Proteome Res"},{"key":"2020080709361982200_ref62","doi-asserted-by":"crossref","first-page":"3550","DOI":"10.1021\/acs.jproteome.6b00308","article-title":"Comparing the diagnostic classification accuracy of iTRAQ, peak-area, spectral-counting, and emPAI methods for relative quantification in expression proteomics","volume":"15","author":"Dowle","year":"2016","journal-title":"J Proteome Res"},{"key":"2020080709361982200_ref63","doi-asserted-by":"crossref","first-page":"229","DOI":"10.1016\/j.tips.2017.12.002","article-title":"Clinical success of drug targets prospectively predicted by in silico study","volume":"39","author":"Zhu","year":"2018","journal-title":"Trends Pharmacol Sci"},{"key":"2020080709361982200_ref64","doi-asserted-by":"crossref","first-page":"1340","DOI":"10.1002\/pmic.201000650","article-title":"Abacus: a computational tool for extracting and pre-processing spectral count data for label-free quantitative proteomic analysis","volume":"11","author":"Fermin","year":"2011","journal-title":"Proteomics"},{"key":"2020080709361982200_ref65","doi-asserted-by":"crossref","first-page":"319","DOI":"10.1038\/nmeth.1195","article-title":"A quantitative analysis software tool for mass spectrometry-based proteomics","volume":"5","author":"Park","year":"2008","journal-title":"Nat Methods"},{"key":"2020080709361982200_ref66","doi-asserted-by":"crossref","first-page":"258","DOI":"10.1038\/nmeth.3255","article-title":"DIA-Umpire: comprehensive computational framework for data-independent acquisition proteomics","volume":"12","author":"Tsou","year":"2015","journal-title":"Nat Methods"},{"key":"2020080709361982200_ref67","doi-asserted-by":"crossref","first-page":"21","DOI":"10.1021\/pr015504q","article-title":"DTASelect and Contrast: tools for assembling and comparing protein identifications from shotgun proteomics","volume":"1","author":"Tabb","year":"2002","journal-title":"J Proteome Res"},{"key":"2020080709361982200_ref68","doi-asserted-by":"crossref","first-page":"286","DOI":"10.1016\/j.dib.2015.11.063","article-title":"Spiked proteomic standard dataset for testing label-free quantitative software and statistical methods","volume":"6","author":"Ramus","year":"2016","journal-title":"Data Brief"},{"key":"2020080709361982200_ref69","doi-asserted-by":"crossref","first-page":"1367","DOI":"10.1038\/nbt.1511","article-title":"MaxQuant enables high peptide identification rates, individualized p.p.b.-range mass accuracies and proteome-wide protein quantification","volume":"26","author":"Cox","year":"2008","journal-title":"Nat Biotechnol"},{"key":"2020080709361982200_ref70","doi-asserted-by":"crossref","first-page":"163","DOI":"10.1186\/1471-2105-9-163","article-title":"OpenMS\u2014an open-source software framework for mass spectrometry","volume":"9","author":"Sturm","year":"2008","journal-title":"BMC Bioinformatics"},{"key":"2020080709361982200_ref71","doi-asserted-by":"crossref","first-page":"2337","DOI":"10.1002\/rcm.1196","article-title":"PEAKS: powerful software for peptide de novo sequencing by tandem mass spectrometry","volume":"17","author":"Ma","year":"2003","journal-title":"Rapid Commun Mass Spectrom"},{"key":"2020080709361982200_ref72","doi-asserted-by":"crossref","first-page":"4646","DOI":"10.1021\/ac0341261","article-title":"A statistical model for identifying proteins by tandem mass spectrometry","volume":"75","author":"Nesvizhskii","year":"2003","journal-title":"Anal Chem"},{"key":"2020080709361982200_ref73","doi-asserted-by":"crossref","first-page":"3037","DOI":"10.1021\/pr900189c","article-title":"The proteios software environment: an extensible multiuser platform for management and analysis of proteomics data","volume":"8","author":"Hakkinen","year":"2009","journal-title":"J Proteome Res"},{"key":"2020080709361982200_ref74","doi-asserted-by":"crossref","first-page":"966","DOI":"10.1093\/bioinformatics\/btq054","article-title":"Skyline: an open source document editor for creating and analyzing targeted proteomics experiments","volume":"26","author":"MacLean","year":"2010","journal-title":"Bioinformatics"},{"key":"2020080709361982200_ref75","doi-asserted-by":"crossref","first-page":"1400","DOI":"10.1074\/mcp.M114.044305","article-title":"Extending the limits of quantitative proteome profiling with data-independent acquisition and application to acetaminophen-treated three-dimensional liver microtissues","volume":"14","author":"Bruderer","year":"2015","journal-title":"Mol Cell Proteomics"},{"key":"2020080709361982200_ref76","first-page":"169","article-title":"The Box\u2013Cox transformation technique\u2014a review","volume":"41","author":"Sakia","year":"1992","journal-title":"J R Stat Soc Ser D Stat"},{"key":"2020080709361982200_ref77","doi-asserted-by":"crossref","first-page":"414","DOI":"10.1002\/dta.1681","article-title":"Control of the misuse of testosterone in castrated horses based on an international threshold in plasma","volume":"7","author":"Ho","year":"2015","journal-title":"Drug Test Anal"},{"key":"2020080709361982200_ref78","doi-asserted-by":"crossref","first-page":"10768","DOI":"10.1021\/ac302748b","article-title":"Normalizing and integrating metabolomics data","volume":"84","author":"De Livera","year":"2012","journal-title":"Anal Chem"},{"key":"2020080709361982200_ref79","doi-asserted-by":"crossref","first-page":"54","DOI":"10.1016\/j.atmosenv.2013.01.038","article-title":"Estimating spatiotemporal variability of ambient air pollutant concentrations with a hierarchical model","volume":"71","author":"Li","year":"2013","journal-title":"Atmos Environ (1994)"},{"key":"2020080709361982200_ref80","doi-asserted-by":"crossref","first-page":"684","DOI":"10.1007\/s11306-014-0738-7","article-title":"The influence of scaling metabolomics data on model classification accuracy","volume":"11","author":"Gromski","year":"2015","journal-title":"Metabolomics"},{"key":"2020080709361982200_ref81","doi-asserted-by":"crossref","first-page":"2285","DOI":"10.1074\/mcp.M800514-MCP200","article-title":"Development and evaluation of normalization methods for label-free relative quantification of endogenous peptides","volume":"8","author":"Kultima","year":"2009","journal-title":"Mol Cell Proteomics"},{"key":"2020080709361982200_ref82","doi-asserted-by":"crossref","first-page":"146","DOI":"10.1007\/s11306-011-0350-z","article-title":"State-of-the art data normalization methods improve NMR-based metabolomic analysis","volume":"8","author":"Kohl","year":"2012","journal-title":"Metabolomics"},{"issue":"Suppl 16","key":"2020080709361982200_ref83","doi-asserted-by":"crossref","first-page":"S5","DOI":"10.1186\/1471-2105-13-S16-S5","article-title":"Normalization and missing value imputation for label-free LC-MS analysis","volume":"13","author":"Karpievitch","year":"2012","journal-title":"BMC Bioinformatics"},{"key":"2020080709361982200_ref84","doi-asserted-by":"crossref","first-page":"277","DOI":"10.1021\/pr050300l","article-title":"Normalization approaches for removing systematic biases associated with mass spectrometry and label-free proteomics","volume":"5","author":"Callister","year":"2006","journal-title":"J Proteome Res"},{"key":"2020080709361982200_ref85","doi-asserted-by":"crossref","first-page":"71","DOI":"10.1007\/s00299-005-0037-x","article-title":"Changes in gene expression in maize kernel in response to water and salt stress","volume":"25","author":"Andjelkovic","year":"2006","journal-title":"Plant Cell Rep"},{"key":"2020080709361982200_ref86","doi-asserted-by":"crossref","first-page":"2866","DOI":"10.1093\/bioinformatics\/btr479","article-title":"Improved quality control processing of peptide-centric LC-MS proteomics data","volume":"27","author":"Matzke","year":"2011","journal-title":"Bioinformatics"},{"key":"2020080709361982200_ref87","doi-asserted-by":"crossref","first-page":"142","DOI":"10.1186\/1471-2164-7-142","article-title":"Centering, scaling, and transformations: improving the biological information content of metabolomics data","volume":"7","author":"Berg","year":"2006","journal-title":"BMC Genomics"},{"key":"2020080709361982200_ref88","doi-asserted-by":"crossref","first-page":"4281","DOI":"10.1021\/ac051632c","article-title":"Probabilistic quotient normalization as robust method to account for dilution of complex biological mixtures. Application in 1H NMR metabonomics","volume":"78","author":"Dieterle","year":"2006","journal-title":"Anal Chem"},{"key":"2020080709361982200_ref89","doi-asserted-by":"crossref","first-page":"11568","DOI":"10.1021\/acs.analchem.6b02848","article-title":"Proteome speciation by mass spectrometry: characterization of composite protein mixtures in milk replacers","volume":"88","author":"Gaspari","year":"2016","journal-title":"Anal Chem"},{"key":"2020080709361982200_ref90","doi-asserted-by":"crossref","first-page":"28","DOI":"10.1186\/s12864-015-2353-z","article-title":"Comparison of normalization and differential expression analyses using RNA-seq data from 726 individual Drosophila melanogaster","volume":"17","author":"Lin","year":"2016","journal-title":"BMC Genomics"},{"key":"2020080709361982200_ref91","doi-asserted-by":"crossref","first-page":"38881","DOI":"10.1038\/srep38881","article-title":"Performance evaluation and online realization of data-driven normalization methods used in LC\/MS based untargeted metabolomics analysis","volume":"6","author":"Li","year":"2016","journal-title":"Sci Rep"},{"key":"2020080709361982200_ref92","doi-asserted-by":"crossref","first-page":"M111.014050","DOI":"10.1074\/mcp.M111.014050","article-title":"Comparative proteomic analysis of eleven common cell lines reveals ubiquitous but varying expression of most proteins","volume":"11","author":"Geiger","year":"2012","journal-title":"Mol Cell Proteomics"},{"key":"2020080709361982200_ref93","doi-asserted-by":"crossref","first-page":"520","DOI":"10.1093\/bioinformatics\/17.6.520","article-title":"Missing value estimation methods for DNA microarrays","volume":"17","author":"Troyanskaya","year":"2001","journal-title":"Bioinformatics"},{"key":"2020080709361982200_ref94","doi-asserted-by":"crossref","first-page":"1608","DOI":"10.1093\/nar\/gkl047","article-title":"Microarray missing data imputation based on a set theoretic framework and biological knowledge","volume":"34","author":"Gan","year":"2006","journal-title":"Nucleic Acids Res"},{"key":"2020080709361982200_ref95","doi-asserted-by":"crossref","first-page":"83","DOI":"10.1038\/nbt.1592","article-title":"Label-free, normalized quantification of complex mass spectrometry data for proteomic analysis","volume":"28","author":"Griffin","year":"2010","journal-title":"Nat Biotechnol"},{"key":"2020080709361982200_ref96","doi-asserted-by":"crossref","first-page":"3140","DOI":"10.1002\/pmic.201400396","article-title":"In-depth evaluation of software tools for data-independent acquisition based label-free quantification","volume":"15","author":"Kuharev","year":"2015","journal-title":"Proteomics"},{"key":"2020080709361982200_ref97","doi-asserted-by":"crossref","first-page":"701","DOI":"10.1007\/s00248-017-1072-1","article-title":"Label-free proteomics of a defined, binary co-culture reveals diversity of competitive responses between members of a model soil microbial system","volume":"75","author":"Chignell","year":"2018","journal-title":"Microb Ecol"},{"key":"2020080709361982200_ref98","doi-asserted-by":"crossref","first-page":"405","DOI":"10.1007\/s13361-017-1837-2","article-title":"On the reproducibility of label-free quantitative cross-linking\/mass spectrometry","volume":"29","author":"Muller","year":"2018","journal-title":"J Am Soc Mass Spectrom"},{"key":"2020080709361982200_ref99","doi-asserted-by":"crossref","first-page":"141","DOI":"10.1186\/s40168-017-0359-2","article-title":"Links of gut microbiota composition with alcohol dependence syndrome and alcoholic liver disease","volume":"5","author":"Dubinkina","year":"2017","journal-title":"Microbiome"},{"key":"2020080709361982200_ref100","doi-asserted-by":"crossref","first-page":"142","DOI":"10.1016\/0168-8278(90)90104-Y","article-title":"Prostaglandins and the treatment of hepatorenal syndrome in cirrhosis","volume":"11","author":"Arroyo","year":"1990","journal-title":"J Hepatol"},{"key":"2020080709361982200_ref101","doi-asserted-by":"crossref","first-page":"896","DOI":"10.1038\/nbt.2931","article-title":"Normalization of RNA-seq data using factor analysis of control genes or samples","volume":"32","author":"Risso","year":"2014","journal-title":"Nat Biotechnol"},{"key":"2020080709361982200_ref102","doi-asserted-by":"crossref","first-page":"4769","DOI":"10.1021\/pr4001898","article-title":"Label-free quantitative proteomic analysis of abscisic acid effect in early-stage soybean under flooding","volume":"12","author":"Komatsu","year":"2013","journal-title":"J Proteome Res"},{"key":"2020080709361982200_ref103","doi-asserted-by":"crossref","first-page":"8943","DOI":"10.1021\/ac4022314","article-title":"Data-driven sample size determination for metabolic phenotyping studies","volume":"85","author":"Blaise","year":"2013","journal-title":"Anal Chem"},{"key":"2020080709361982200_ref104","doi-asserted-by":"crossref","first-page":"e1005562","DOI":"10.1371\/journal.pcbi.1005562","article-title":"ROTS: an R package for reproducibility-optimized statistical testing","volume":"13","author":"Suomi","year":"2017","journal-title":"PLoS Comput Biol"},{"key":"2020080709361982200_ref105","doi-asserted-by":"crossref","first-page":"125","DOI":"10.1016\/j.jprot.2017.06.022","article-title":"In-depth proteomic analysis of Glycine max seeds during controlled deterioration treatment reveals a shift in seed metabolism","volume":"169","author":"Min","year":"2017","journal-title":"J Proteomics"},{"key":"2020080709361982200_ref106","doi-asserted-by":"crossref","first-page":"W162","DOI":"10.1093\/nar\/gkx449","article-title":"NOREVA: normalization and evaluation of MS-based metabolomics data","volume":"45","author":"Li","year":"2017","journal-title":"Nucleic Acids Res"},{"key":"2020080709361982200_ref107","doi-asserted-by":"crossref","first-page":"1235","DOI":"10.1039\/C4MB00711E","article-title":"Optimal consistency in microRNA expression analysis using reference-gene-based normalization","volume":"11","author":"Wang","year":"2015","journal-title":"Mol Biosyst"},{"key":"2020080709361982200_ref108","doi-asserted-by":"crossref","first-page":"e1005889","DOI":"10.1371\/journal.ppat.1005889","article-title":"Microbiome composition and function drives wound-healing impairment in the female genital tract","volume":"12","author":"Zevin","year":"2016","journal-title":"PLoS Pathog"},{"key":"2020080709361982200_ref109","doi-asserted-by":"crossref","first-page":"743","DOI":"10.1038\/nprot.2011.319","article-title":"Web-based inference of biological patterns, functions and pathways from metabolomic data using MetaboAnalyst","volume":"6","author":"Xia","year":"2011","journal-title":"Nat Protoc"},{"key":"2020080709361982200_ref110","doi-asserted-by":"crossref","first-page":"65","DOI":"10.1093\/bib\/bbn039","article-title":"Web-based applications for building, managing and analysing kinetic models of biological systems","volume":"10","author":"Lee","year":"2009","journal-title":"Brief Bioinform"},{"key":"2020080709361982200_ref111","doi-asserted-by":"crossref","first-page":"D447","DOI":"10.1093\/nar\/gkv1145","article-title":"2016 update of the PRIDE database and its related tools","volume":"44","author":"Vizcaino","year":"2016","journal-title":"Nucleic Acids Res"},{"key":"2020080709361982200_ref112","doi-asserted-by":"crossref","first-page":"13419","DOI":"10.1038\/ncomms13419","article-title":"Altered intestinal microbiota-host mitochondria crosstalk in new onset Crohn\u2019s disease","volume":"7","author":"Mottawea","year":"2016","journal-title":"Nat Commun"},{"key":"2020080709361982200_ref113","doi-asserted-by":"crossref","first-page":"27","DOI":"10.1016\/j.chom.2017.11.004","article-title":"Bifidobacteria or fiber protects against diet-induced microbiota-mediated colonic mucus deterioration","volume":"23","author":"Schroeder","year":"2018","journal-title":"Cell Host Microbe"},{"key":"2020080709361982200_ref114","doi-asserted-by":"crossref","first-page":"1605","DOI":"10.3389\/fmicb.2017.01605","article-title":"A structural and functional elucidation of the rumen microbiome influenced by various diets and microenvironments","volume":"8","author":"Deusch","year":"2017","journal-title":"Front Microbiol"},{"key":"2020080709361982200_ref115","doi-asserted-by":"crossref","first-page":"44","DOI":"10.1186\/s13073-016-0293-0","article-title":"Ultra-deep and quantitative saliva proteome reveals dynamics of the oral microbiome","volume":"8","author":"Grassl","year":"2016","journal-title":"Genome Med"},{"key":"2020080709361982200_ref116","doi-asserted-by":"crossref","first-page":"2277","DOI":"10.1074\/mcp.M114.040204","article-title":"Membrane protein profiling of human colon reveals distinct regional differences","volume":"13","author":"Post","year":"2014","journal-title":"Mol Cell Proteomics"},{"key":"2020080709361982200_ref117","doi-asserted-by":"crossref","first-page":"1215","DOI":"10.3389\/fmicb.2017.01215","article-title":"Outer membrane proteome of Veillonella parvula: a diderm firmicute of the human microbiome","volume":"8","author":"Poppleton","year":"2017","journal-title":"Front Microbiol"},{"key":"2020080709361982200_ref118","doi-asserted-by":"crossref","first-page":"17337","DOI":"10.1074\/jbc.M117.805036","article-title":"The bacterial arginine glycosyltransferase effector NleB preferentially modifies Fas-associated death domain protein (FADD)","volume":"292","author":"Scott","year":"2017","journal-title":"J Biol Chem"},{"key":"2020080709361982200_ref119","doi-asserted-by":"crossref","first-page":"1232","DOI":"10.1021\/pr060018u","article-title":"Isobaric tags for relative and absolute quantitation (iTRAQ) reproducibility: implication of multiple injections","volume":"5","author":"Chong","year":"2006","journal-title":"J Proteome Res"},{"key":"2020080709361982200_ref120","doi-asserted-by":"crossref","first-page":"254","DOI":"10.1080\/00140139.2014.885588","article-title":"Equations to predict female manual arm strength based on hand location relative to the shoulder","volume":"57","author":"La Delfa","year":"2014","journal-title":"Ergonomics"},{"key":"2020080709361982200_ref121","doi-asserted-by":"crossref","first-page":"10","DOI":"10.1186\/1477-5956-7-10","article-title":"Two-dimensional gel proteome reference map of human small intestine","volume":"7","author":"Simula","year":"2009","journal-title":"Proteome Sci"},{"key":"2020080709361982200_ref122","doi-asserted-by":"crossref","first-page":"1600278","DOI":"10.1002\/pmic.201600278","article-title":"SWATH-MS as a tool for biomarker discovery: from basic research to clinical applications","volume":"17","author":"Anjo","year":"2017","journal-title":"Proteomics"},{"key":"2020080709361982200_ref123","doi-asserted-by":"crossref","first-page":"786","DOI":"10.15252\/msb.20145728","article-title":"Quantitative variability of 342 plasma proteins in a human twin population","volume":"11","author":"Liu","year":"2015","journal-title":"Mol Syst Biol"},{"key":"2020080709361982200_ref124","doi-asserted-by":"crossref","first-page":"3219","DOI":"10.1016\/j.celrep.2017.03.019","article-title":"Precise temporal profiling of signaling complexes in primary cells using SWATH mass spectrometry","volume":"18","author":"Caron","year":"2017","journal-title":"Cell Rep"},{"key":"2020080709361982200_ref125","doi-asserted-by":"crossref","first-page":"14818","DOI":"10.1038\/s41598-017-13858-3","article-title":"Trisomy 21 causes changes in the circulating proteome indicative of chronic autoinflammation","volume":"7","author":"Sullivan","year":"2017","journal-title":"Sci Rep"},{"key":"2020080709361982200_ref126","doi-asserted-by":"crossref","first-page":"407","DOI":"10.1038\/nm.3807","article-title":"Rapid mass spectrometric conversion of tissue biopsy samples into permanent quantitative digital proteome maps","volume":"21","author":"Guo","year":"2015","journal-title":"Nat Med"},{"key":"2020080709361982200_ref127","doi-asserted-by":"crossref","first-page":"1105","DOI":"10.1016\/j.cell.2017.05.010","article-title":"A class of environmental and endogenous toxins induces BRCA2 haploinsufficiency and genome instability","volume":"169","author":"Tan","year":"2017","journal-title":"Cell"},{"key":"2020080709361982200_ref128","doi-asserted-by":"crossref","first-page":"1229","DOI":"10.1016\/j.celrep.2017.07.025","article-title":"Impact of alternative splicing on the human proteome","volume":"20","author":"Liu","year":"2017","journal-title":"Cell Rep"},{"key":"2020080709361982200_ref129","doi-asserted-by":"crossref","first-page":"51","DOI":"10.1016\/j.jprot.2015.11.011","article-title":"Benchmarking quantitative label-free LC-MS data processing workflows using a complex spiked proteomic standard dataset","volume":"132","author":"Ramus","year":"2016","journal-title":"J Proteomics"},{"key":"2020080709361982200_ref130","doi-asserted-by":"crossref","first-page":"308","DOI":"10.1186\/1471-2105-13-308","article-title":"Estimating relative abundances of proteins from shotgun proteomics data","volume":"13","author":"McIlwain","year":"2012","journal-title":"BMC Bioinformatics"},{"key":"2020080709361982200_ref131","doi-asserted-by":"crossref","first-page":"1006","DOI":"10.1074\/mcp.M900513-MCP200","article-title":"In-depth exploration of cerebrospinal fluid by combining peptide ligand library treatment and label-free protein quantification","volume":"9","author":"Mouton-Barbosa","year":"2010","journal-title":"Mol Cell Proteomics"},{"key":"2020080709361982200_ref132","doi-asserted-by":"crossref","first-page":"428","DOI":"10.1074\/mcp.M300041-MCP200","article-title":"The application of new software tools to quantitative protein profiling via isotope-coded affinity tag (ICAT) and tandem mass spectrometry: II. Evaluation of tandem mass spectrometry methodologies for large-scale protein analysis, and the application of statistical tools for data analysis and interpretation","volume":"2","author":"Haller","year":"2003","journal-title":"Mol Cell Proteomics"},{"key":"2020080709361982200_ref133","doi-asserted-by":"crossref","first-page":"2432","DOI":"10.2337\/db12-1770","article-title":"Diabetes induces lysine acetylation of intermediary metabolism enzymes in the kidney","volume":"63","author":"Kosanam","year":"2014","journal-title":"Diabetes"},{"key":"2020080709361982200_ref134","doi-asserted-by":"crossref","first-page":"2254","DOI":"10.1074\/mcp.M800037-MCP200","article-title":"Extensive analysis of the cytoplasmic proteome of human erythrocytes using the peptide ligand library technology and advanced mass spectrometry","volume":"7","author":"Roux-Dalvai","year":"2008","journal-title":"Mol Cell Proteomics"},{"key":"2020080709361982200_ref135","doi-asserted-by":"crossref","first-page":"1628","DOI":"10.1021\/pr300992u","article-title":"An automated pipeline for high-throughput label-free quantitative proteomics","volume":"12","author":"Weisser","year":"2013","journal-title":"J Proteome Res"},{"key":"2020080709361982200_ref136","doi-asserted-by":"crossref","first-page":"M111. 010587","DOI":"10.1074\/mcp.M111.010587","article-title":"PEAKS DB: de novo sequencing assisted database search for sensitive and accurate peptide identification","volume":"11","author":"Zhang","year":"2012","journal-title":"Mol Cell Proteomics"},{"key":"2020080709361982200_ref137","doi-asserted-by":"crossref","first-page":"489","DOI":"10.1089\/omi.2012.0042","article-title":"A software toolkit and interface for performing stable isotope labeling and top3 quantification using Progenesis LC-MS","volume":"16","author":"Qi","year":"2012","journal-title":"OMICS"},{"key":"2020080709361982200_ref138","doi-asserted-by":"crossref","first-page":"1265","DOI":"10.1002\/pmic.200900437","article-title":"Scaffold: a bioinformatic tool for validating MS\/MS-based proteomic studies","volume":"10","author":"Searle","year":"2010","journal-title":"Proteomics"},{"key":"2020080709361982200_ref139","doi-asserted-by":"crossref","first-page":"202","DOI":"10.1074\/mcp.M112.017707","article-title":"Platform-independent and label-free quantitation of proteomic data using MS1 extracted ion chromatograms in skyline: application to protein acetylation and phosphorylation","volume":"11","author":"Schilling","year":"2012","journal-title":"Mol Cell Proteomics"},{"key":"2020080709361982200_ref140","doi-asserted-by":"publisher","DOI":"10.1007\/s10792-017-0791-0","article-title":"Comparative evaluation of the aqueous humor proteome of primary angle closure and primary open angle glaucomas and age-related cataract eyes","author":"Kaur","year":"2018","journal-title":"Int Ophthalmol"},{"key":"2020080709361982200_ref141","doi-asserted-by":"crossref","first-page":"26","DOI":"10.3389\/fnmol.2018.00026","article-title":"Quantitative proteomics of synaptosomal fractions in a rat overexpressing human DISC1 gene indicates profound synaptic dysregulation in the dorsal striatum","volume":"11","author":"Sialana","year":"2018","journal-title":"Front Mol Neurosci"},{"key":"2020080709361982200_ref142","doi-asserted-by":"crossref","first-page":"2208","DOI":"10.1093\/bioinformatics\/btu151","article-title":"Census 2: isobaric labeling data analysis","volume":"30","author":"Park","year":"2014","journal-title":"Bioinformatics"},{"key":"2020080709361982200_ref143","doi-asserted-by":"crossref","first-page":"777","DOI":"10.1038\/nmeth.3954","article-title":"TRIC: an automated alignment strategy for reproducible protein quantification in targeted proteomics","volume":"13","author":"Rost","year":"2016","journal-title":"Nat Methods"},{"key":"2020080709361982200_ref144","doi-asserted-by":"crossref","first-page":"681","DOI":"10.3389\/fphar.2018.00681","article-title":"Discovery of the consistently well-performed analysis vhain for SWATH-MS based pharmacoproteomic quantification","volume":"9","author":"Fu","year":"2018","journal-title":"Front Pharmacol"},{"key":"2020080709361982200_ref145","doi-asserted-by":"crossref","first-page":"1239","DOI":"10.1038\/nmeth.2702","article-title":"Mapping differential interactomes by affinity purification coupled with data-independent mass spectrometry acquisition","volume":"10","author":"Lambert","year":"2013","journal-title":"Nat Methods"},{"key":"2020080709361982200_ref146","doi-asserted-by":"crossref","first-page":"3467","DOI":"10.1021\/pr201240a","article-title":"Label-free quantitation of protein modifications by pseudo selected reaction monitoring with internal reference peptides","volume":"11","author":"Sherrod","year":"2012","journal-title":"J Proteome Res"}],"container-title":["Briefings in Bioinformatics"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/academic.oup.com\/bib\/article-pdf\/21\/2\/621\/33583560\/bby127.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"http:\/\/academic.oup.com\/bib\/article-pdf\/21\/2\/621\/33583560\/bby127.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2020,8,7]],"date-time":"2020-08-07T13:47:48Z","timestamp":1596808068000},"score":1,"resource":{"primary":{"URL":"https:\/\/academic.oup.com\/bib\/article\/21\/2\/621\/5283501"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,1,15]]},"references-count":146,"journal-issue":{"issue":"2","published-online":{"date-parts":[[2019,1,15]]},"published-print":{"date-parts":[[2020,3,23]]}},"URL":"https:\/\/doi.org\/10.1093\/bib\/bby127","relation":{},"ISSN":["1467-5463","1477-4054"],"issn-type":[{"value":"1467-5463","type":"print"},{"value":"1477-4054","type":"electronic"}],"subject":[],"published-other":{"date-parts":[[2020,3]]},"published":{"date-parts":[[2019,1,15]]}}}