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Instrument development has largely ensured the effective production of proteomic data, which necessitates commensurate advances in statistical framework to discover the optimal proteomic signature. Current framework mainly emphasizes the generalizability of the identified signature in predicting the independent data but neglects the reproducibility among signatures identified from independently repeated trials on different sub-dataset. These problems seriously restricted the wide application of the proteomic technique in molecular biology and other related directions. Thus, it is crucial to enable the generalizable and reproducible discovery of the proteomic signature with the subsequent indication of phenotype association. However, no such tool has been developed and available yet. Herein, an online tool, POSREG, was therefore constructed to identify the optimal signature for a set of proteomic data. It works by (i) identifying the proteomic signature of good reproducibility and aggregating them to ensemble feature ranking by ensemble learning, (ii) assessing the generalizability of ensemble feature ranking to acquire the optimal signature and (iii) indicating the phenotype association of discovered signature. POSREG is unique in its capacity of discovering the proteomic signature by simultaneously optimizing its reproducibility and generalizability. It is now accessible free of charge without any registration or login requirement at https:\/\/idrblab.org\/posreg\/<\/jats:p>","DOI":"10.1093\/bib\/bbac040","type":"journal-article","created":{"date-parts":[[2022,2,14]],"date-time":"2022-02-14T12:27:24Z","timestamp":1644841644000},"source":"Crossref","is-referenced-by-count":103,"title":["POSREG: proteomic signature discovered by simultaneously optimizing its reproducibility and generalizability"],"prefix":"10.1093","volume":"23","author":[{"given":"Fengcheng","family":"Li","sequence":"first","affiliation":[{"name":"College of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, China"}]},{"given":"Ying","family":"Zhou","sequence":"additional","affiliation":[{"name":"State Key Laboratory for Diagnosis and Treatment of Infectious Disease, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Zhejiang Provincial Key Laboratory for Drug Clinical Research and Evaluation, The First Affiliated Hospital, Zhejiang University, Hangzhou, Zhejiang 310000, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8825-2573","authenticated-orcid":false,"given":"Ying","family":"Zhang","sequence":"additional","affiliation":[{"name":"College of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, China"}]},{"given":"Jiayi","family":"Yin","sequence":"additional","affiliation":[{"name":"College of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, China"}]},{"given":"Yunqing","family":"Qiu","sequence":"additional","affiliation":[{"name":"State Key Laboratory for Diagnosis and Treatment of Infectious Disease, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Zhejiang Provincial Key Laboratory for Drug Clinical Research and Evaluation, The First Affiliated Hospital, Zhejiang University, Hangzhou, Zhejiang 310000, China"}]},{"given":"Jianqing","family":"Gao","sequence":"additional","affiliation":[{"name":"Westlake Laboratory of Life Sciences 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