PLUS: Predicting cancer metastasis potential based on positive and unlabeled learning.

Zhou, Junyi; Lu, Xiaoyu; Chang, Wennan; Wan, Changlin; Lu, Xiongbin; Zhang, Chi; Cao, Sha

Zhou, Junyi; Lu, Xiaoyu; Chang, Wennan; Wan, Changlin; Lu, Xiongbin; Zhang, Chi; Cao, Sha.

Affiliation

Zhou J; Amgen Inc., Thousand Oaks, California, United States of America.
Lu X; Department of Biostatistics and Health Data Science, Department of Medical and Molecular Genetics and Center for Computational Biology and Bioinformatics, Indiana University School of Medicine, Indianapolis, Indiana, United States of America.
Chang W; Department of BioHealth, Indiana University-Purdue University Indianapolis, Indianapolis, Indiana, United States of America.
Wan C; Department of Biostatistics and Health Data Science, Department of Medical and Molecular Genetics and Center for Computational Biology and Bioinformatics, Indiana University School of Medicine, Indianapolis, Indiana, United States of America.
Lu X; Department of Electrical and Computer Engineering, Purdue University, Indianapolis, Indiana, United States of America.
Zhang C; Department of Biostatistics and Health Data Science, Department of Medical and Molecular Genetics and Center for Computational Biology and Bioinformatics, Indiana University School of Medicine, Indianapolis, Indiana, United States of America.
Cao S; Department of Electrical and Computer Engineering, Purdue University, Indianapolis, Indiana, United States of America.

PLoS Comput Biol ; 18(3): e1009956, 2022 03.

Article in En | MEDLINE | ID: mdl-35349572

Subject(s)

Algorithms; Neoplasms; Humans

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Full text: 1 Database: MEDLINE Main subject: Algorithms / Neoplasms Type of study: Prognostic_studies / Risk_factors_studies Limits: Humans Language: En Journal: PLoS Comput Biol Journal subject: BIOLOGIA / INFORMATICA MEDICA Year: 2022 Type: Article Affiliation country: United States

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