{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,4]],"date-time":"2026-03-04T10:30:21Z","timestamp":1772620221846,"version":"3.50.1"},"reference-count":10,"publisher":"Oxford University Press (OUP)","issue":"10","license":[{"start":{"date-parts":[[2016,10,12]],"date-time":"2016-10-12T00:00:00Z","timestamp":1476230400000},"content-version":"vor","delay-in-days":264,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2016,5,15]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>Summary: The R\/Bioconductor package Protein Array Analyzer (PAA) facilitates a flexible analysis of protein microarrays for biomarker discovery (esp., ProtoArrays). It provides a complete data analysis workflow including preprocessing and quality control, uni- and multivariate feature selection as well as several different plots and results tables to outline and evaluate the analysis results. As a main feature, PAA\u2019s multivariate feature selection methods are based on recursive feature elimination (e.g. SVM-recursive feature elimination, SVM-RFE) with stability ensuring strategies such as ensemble feature selection. This enables PAA to detect stable and reliable biomarker candidate panels.<\/jats:p>\n               <jats:p>Availability and implementation: \u00a0PAA is freely available (BSD 3-clause license) from http:\/\/www.bioconductor.org\/packages\/PAA\/.<\/jats:p>\n               <jats:p>Contact: \u00a0michael.turewicz@rub.de or martin.eisenacher@rub.de<\/jats:p>","DOI":"10.1093\/bioinformatics\/btw037","type":"journal-article","created":{"date-parts":[[2016,2,15]],"date-time":"2016-02-15T01:09:07Z","timestamp":1455498547000},"page":"1577-1579","source":"Crossref","is-referenced-by-count":25,"title":["PAA: an R\/bioconductor package for biomarker discovery with protein microarrays"],"prefix":"10.1093","volume":"32","author":[{"given":"Michael","family":"Turewicz","sequence":"first","affiliation":[{"name":"Medizinisches Proteom-Center, Ruhr-University Bochum, Bochum, 44801, Germany"}]},{"given":"Maike","family":"Ahrens","sequence":"additional","affiliation":[{"name":"Medizinisches Proteom-Center, Ruhr-University Bochum, Bochum, 44801, Germany"}]},{"given":"Caroline","family":"May","sequence":"additional","affiliation":[{"name":"Medizinisches Proteom-Center, Ruhr-University Bochum, Bochum, 44801, Germany"}]},{"given":"Katrin","family":"Marcus","sequence":"additional","affiliation":[{"name":"Medizinisches Proteom-Center, Ruhr-University Bochum, Bochum, 44801, Germany"}]},{"given":"Martin","family":"Eisenacher","sequence":"additional","affiliation":[{"name":"Medizinisches Proteom-Center, Ruhr-University Bochum, Bochum, 44801, Germany"}]}],"member":"286","published-online":{"date-parts":[[2016,1,22]]},"reference":[{"key":"2023020112251509200_btw037-B1","doi-asserted-by":"crossref","first-page":"392","DOI":"10.1093\/bioinformatics\/btp630","article-title":"Robust biomarker identification for cancer diagnosis with ensemble feature selection methods","volume":"26","author":"Abeel","year":"2010","journal-title":"Bioinformatics"},{"key":"2023020112251509200_btw037-B2","doi-asserted-by":"crossref","first-page":"537","DOI":"10.1093\/bib\/bbp016","article-title":"Development of biomarker classifiers from high-dimensional data","volume":"10","author":"Baek","year":"2009","journal-title":"Brief Bioinform"},{"key":"2023020112251509200_btw037-B3","doi-asserted-by":"crossref","first-page":"389","DOI":"10.1023\/A:1012487302797","article-title":"Gene selection for cancer classification using support vector machines","volume":"46","author":"Guyon","year":"2002","journal-title":"Mach. 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