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NetG2P: Network-based genotype-to-phenotype transformation identifies key signaling crosstalk for prognosis in pan-cancer study.

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Bibliographic Details
Title: NetG2P: Network-based genotype-to-phenotype transformation identifies key signaling crosstalk for prognosis in pan-cancer study.
Authors: Lee J; Research Institute, National Cancer Center, Goyang, 10408, Republic of Korea., Jang SW; Research Institute, National Cancer Center, Goyang, 10408, Republic of Korea., Lee B; Research Institute, National Cancer Center, Goyang, 10408, Republic of Korea., Shin J; Research Institute, National Cancer Center, Goyang, 10408, Republic of Korea.; Deparment of Biochemistry and Molecular Genetics, University of Virginia School of Medicine, Charlottesville, VA, 22903, USA.; Department of Genome Sciences, University of Virginia School of Medicine, Charlottesville, VA, 22903, USA., Gong JR; Department of Bio and Brain Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, 34141, Republic of Korea., Shin D; Research Institute, National Cancer Center, Goyang, 10408, Republic of Korea. dshin@ncc.re.kr.; Department of Cancer Biomedical Science, National Cancer Center Graduate School of Cancer Science and Policy, Goyang, 10408, Republic of Korea. dshin@ncc.re.kr.
Source: BMC biology [BMC Biol] 2026 Feb 24; Vol. 24 (1). Date of Electronic Publication: 2026 Feb 24.
Publication Type: Journal Article
Journal Info: Publisher: BioMed Central Country of Publication: England NLM ID: 101190720 Publication Model: Electronic Cited Medium: Internet ISSN: 1741-7007 (Electronic) Linking ISSN: 17417007 NLM ISO Abbreviation: BMC Biol Subsets: MEDLINE
Database: MEDLINE Ultimate
Description
ISSN:1741-7007
DOI:10.1186/s12915-026-02559-x