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Article

Bayesian semi-nonnegative matrix tri-factorization to identify pathways associated with cancer phenotypes.

Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing - 1 Jan 2020

Park Sunho, Kar Nabhonil, Cheong Jae-Ho, Hwang Tae Hyun

Abstract excerpt

Accurate identification of pathways associated with cancer phenotypes (e.g., cancer subtypes and treatment outcomes) could lead to discovering reliable prognostic and/or predictive biomarkers for better patients stratification and treatment guidance. In our previous work, we have shown that non-negative matrix tri-factorization (NMTF) can be successfully applied to identify pathways associated with specific...

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PMID: 31797616

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PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 7 Sept 2026. Manifest publication-graph-cohort-2026-09-08.1.

Source receipt: pubmed, retrieved 7 Sept 2026.

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