Research graph
References from BiGraphDriver: A dual bipartite graph and multi-omics diffusion framework for cancer driver gene identification. Local targets link to admitted publications; unresolved targets remain external evidence.
Cancer genome landscapes
10.1126/science.1235122 · 2013 · External reference
The Cancer Genome Atlas Pan-Cancer analysis project
10.1038/ng.2764 · 2013 · External reference
The international cancer genome consortium data portal
10.1038/s41587-019-0055-9 · 2019 · External reference
Mutational heterogeneity in cancer and the search for new cancer-associated genes
10.1038/nature12213 · 2013 · External reference
MuSiC: identifying mutational significance in cancer genomes
10.1101/gr.134635.111 · 2012 · External reference
Cancer-specific high-throughput annotation of somatic mutations: computational prediction of driver missense mutations
10.1158/0008-5472.can-09-1133 · 2009 · External reference
Functional impact bias reveals cancer drivers
10.1093/nar/gks743 · 2012 · External reference
DriverNet: uncovering the impact of somatic driver mutations on transcriptional networks in cancer
10.1186/gb-2012-13-12-r124 · 2012 · External reference
DawnRank: discovering personalized driver genes in cancer
10.1186/s13073-014-0056-8 · 2014 · External reference
DriverRWH: discovering cancer driver genes by random walk on a gene mutation hypergraph
10.1186/s12859-022-04788-7 · 2022 · External reference
A random walk-based method to identify driver genes by integrating the subcellular localization and variation frequency into bipartite graph
10.1186/s12859-019-2847-9 · 2019 · External reference
De novo discovery of mutated driver pathways in cancer
10.1101/gr.120477.111 · 2012 · External reference
MEXCOwalk: mutual exclusion and coverage based random walk to identify cancer modules
10.1093/bioinformatics/btz655 · 2020 · External reference
Advancing cancer driver gene identification through an integrative network and pathway approach
10.1016/j.jbi.2024.104729 · 2024 · External reference
Identifying cancer driver genes based on multi-view heterogeneous graph convolutional network and self-attention mechanism
10.1186/s12859-023-05140-3 · 2023 · External reference
Explainable multilayer graph neural network for cancer gene prediction
10.1093/bioinformatics/btad643 · 2023 · External reference
SMG: self-supervised masked graph learning for cancer gene identification
10.1093/bib/bbad406 · 2023 · External reference
CGMega: explainable graph neural network framework with attention mechanisms for cancer gene module dissection
2024 · External reference
MCDHGN: heterogeneous network-based cancer driver gene prediction and interpretability analysis
10.1093/bioinformatics/btae362 · 2024 · External reference
Towards simplified graph neural networks for identifying cancer driver genes in heterophilic networks
2025 · External reference
Deep graph convolutional network-based multi-omics integration for cancer driver gene identification
10.1093/bib/bbaf364 · 2025 · External reference
GRAFT: a graph-aware fusion transformer for cancer driver gene prediction
10.1093/bib/bbaf706 · 2026 · External reference
ONCOPLEX: an oncology-inspired hypergraph model integrating diverse biological knowledge for cancer driver gene prediction
2026 · External reference
Visualizing and interpreting cancer genomics data via the Xena platform
10.1038/s41587-020-0546-8 · 2020 · External reference
The COSMIC Cancer Gene Census: describing genetic dysfunction across all human cancers
10.1038/s41568-018-0060-1 · 2018 · External reference
A human functional protein interaction network and its application to cancer data analysis
10.1186/gb-2010-11-5-r53 · 2010 · External reference
Cancer and meiotic gene expression: Two sides of the same coin?
10.1016/bs.ctdb.2022.06.002 · 2023 · External reference
Mutual exclusivity analysis identifies oncogenic network modules
10.1101/gr.125567.111 · 2012 · External reference
Hybrid Recommendation Algorithm Based on Weighted Bipartite Graph and Logistic Regression
2019 · External reference
Network-based stratification of tumor mutations
10.1038/nmeth.2651 · 2013 · External reference
Algorithms for detecting significantly mutated pathways in cancer
10.1089/cmb.2010.0265 · 2011 · External reference
clusterProfiler: an R package for comparing biological themes among gene clusters
10.1089/omi.2011.0118 · 2012 · External reference
GEPIA2: an enhanced web server for large-scale expression profiling and interactive analysis
10.1093/nar/gkz430 · 2019 · External reference
Defining a cancer dependency map
10.1016/j.cell.2017.06.010 · 2017 · External reference
Integration of multiomics data with graph convolutional networks to identify new cancer genes and their associated molecular mechanisms
10.1038/s42256-021-00325-y · 2021 · External reference
SSCI: self-supervised deep learning improves network structure for cancer driver gene identification
10.3390/ijms251910351 · 2024 · External reference
Network medicine: a network-based approach to human disease
10.1038/nrg2918 · 2011 · External reference
on the Path to Cancer
10.1016/j.cell.2012.03.003 · 2012 · External reference
Live or let die: The cell's response to p53
10.1038/nrc864 · 2002 · External reference
Network-based machine learning and graph theory algorithms for precision oncology
10.1038/s41698-017-0029-7 · 2017 · External reference
A decade of exploring the cancer epigenome - biological and translational implications
10.1038/nrc3130 · 2011 · External reference
Molecular origins of cancer: epigenetics in cancer
10.1056/nejmra072067 · 2008 · External reference
MONet: cancer driver gene identification algorithm based on integrated analysis of multi-omics data and network models
10.3389/ebm.2025.10399 · 2025 · External reference
ConsensusPathDB: toward a more complete picture of cell biology
10.1093/nar/gkq1156 · 2011 · External reference
STRING v11: protein-protein association networks with increased coverage, supporting functional discovery in genome-wide experimental datasets
10.1093/nar/gky1131 · 2019 · External reference
Interpretation of Genomic Variants Using a Unified Biological Network Approach
10.1371/journal.pcbi.1002886 · 2013 · External reference
ICE: a driver genes identification method with improved cross-entropy measure
2025 · External reference
Differential expression and action of Toll-like receptors in human adrenocortical cells
10.1016/j.mce.2008.10.028 · 2009 · External reference
Identification of CCT3 as a prognostic factor and correlates with cell survival and invasion of head and neck squamous cell carcinoma
10.1042/bsr20211137 · 2021 · External reference
Potential prognostic biomarkers identified by DNA methylation profiling analysis for patients with lung adenocarcinoma
2018 · External reference
Endocrine-resistant breast cancer: mechanisms and treatment
10.1159/000508675 · 2020 · External reference
The emerging roles of Hedgehog signaling in tumor immune microenvironment
2023 · External reference
Targeting the PI3K/AKT/mTOR Pathway in Bladder Cancer
2018 · External reference
BCL-2 protein family: attractive targets for cancer therapy
10.1007/s10495-022-01780-7 · 2022 · External reference
The Network of Cancer Genes (NCG): a comprehensive catalogue of known and candidate cancer genes from cancer sequencing screens
10.1186/s13059-018-1612-0 · 2019 · External reference
OncoKB: a precision oncology knowledge base
10.1200/po.17.00011 · 2017 · External reference
IntOGen-mutations identifies cancer drivers across tumor types
10.1038/nmeth.2642 · 2013 · External reference
CancerMine: a literature-mined resource for drivers, oncogenes and tumor suppressors in cancer
10.1038/s41592-019-0422-y · 2019 · External reference
PubTator 3.0: an AI-powered literature resource for unlocking biomedical knowledge
10.1093/nar/gkae235 · 2024 · External reference
RBM22, a key player of pre-mRNA splicing and gene expression regulation, is altered in cancer
10.3390/cancers14030643 · 2022 · External reference
EXOSC10 is a novel hepatocellular carcinoma prognostic biomarker: a comprehensive bioinformatics analysis and experiment verification
10.7717/peerj.15860 · 2023 · External reference
BCL-2 protein family: attractive targets for cancer therapy
10.1007/s10495-022-01780-7 · ExternalCitation · doi-reference
Cancer and meiotic gene expression: Two sides of the same coin?
10.1016/bs.ctdb.2022.06.002 · ExternalCitation · doi-reference
on the Path to Cancer
10.1016/j.cell.2012.03.003 · ExternalCitation · doi-reference
Defining a cancer dependency map
10.1016/j.cell.2017.06.010 · ExternalCitation · doi-reference
Advancing cancer driver gene identification through an integrative network and pathway approach
10.1016/j.jbi.2024.104729 · ExternalCitation · doi-reference
Differential expression and action of Toll-like receptors in human adrenocortical cells
10.1016/j.mce.2008.10.028 · ExternalCitation · doi-reference
Mutational heterogeneity in cancer and the search for new cancer-associated genes
10.1038/nature12213 · ExternalCitation · doi-reference
The Cancer Genome Atlas Pan-Cancer analysis project
10.1038/ng.2764 · ExternalCitation · doi-reference
IntOGen-mutations identifies cancer drivers across tumor types
10.1038/nmeth.2642 · ExternalCitation · doi-reference
Network-based stratification of tumor mutations
10.1038/nmeth.2651 · ExternalCitation · doi-reference
A decade of exploring the cancer epigenome - biological and translational implications
10.1038/nrc3130 · ExternalCitation · doi-reference
Live or let die: The cell's response to p53
10.1038/nrc864 · ExternalCitation · doi-reference
Network medicine: a network-based approach to human disease
10.1038/nrg2918 · ExternalCitation · doi-reference
The COSMIC Cancer Gene Census: describing genetic dysfunction across all human cancers
10.1038/s41568-018-0060-1 · ExternalCitation · doi-reference
The international cancer genome consortium data portal
10.1038/s41587-019-0055-9 · ExternalCitation · doi-reference
Visualizing and interpreting cancer genomics data via the Xena platform
10.1038/s41587-020-0546-8 · ExternalCitation · doi-reference
CancerMine: a literature-mined resource for drivers, oncogenes and tumor suppressors in cancer
10.1038/s41592-019-0422-y · ExternalCitation · doi-reference
Network-based machine learning and graph theory algorithms for precision oncology
10.1038/s41698-017-0029-7 · ExternalCitation · doi-reference
Integration of multiomics data with graph convolutional networks to identify new cancer genes and their associated molecular mechanisms
10.1038/s42256-021-00325-y · ExternalCitation · doi-reference
Identification of CCT3 as a prognostic factor and correlates with cell survival and invasion of head and neck squamous cell carcinoma
10.1042/bsr20211137 · ExternalCitation · doi-reference
Molecular origins of cancer: epigenetics in cancer
10.1056/nejmra072067 · ExternalCitation · doi-reference
Algorithms for detecting significantly mutated pathways in cancer
10.1089/cmb.2010.0265 · ExternalCitation · doi-reference
clusterProfiler: an R package for comparing biological themes among gene clusters
10.1089/omi.2011.0118 · ExternalCitation · doi-reference
SMG: self-supervised masked graph learning for cancer gene identification
10.1093/bib/bbad406 · ExternalCitation · doi-reference
Deep graph convolutional network-based multi-omics integration for cancer driver gene identification
10.1093/bib/bbaf364 · ExternalCitation · doi-reference
GRAFT: a graph-aware fusion transformer for cancer driver gene prediction
10.1093/bib/bbaf706 · ExternalCitation · doi-reference
Explainable multilayer graph neural network for cancer gene prediction
10.1093/bioinformatics/btad643 · ExternalCitation · doi-reference
MCDHGN: heterogeneous network-based cancer driver gene prediction and interpretability analysis
10.1093/bioinformatics/btae362 · ExternalCitation · doi-reference
MEXCOwalk: mutual exclusion and coverage based random walk to identify cancer modules
10.1093/bioinformatics/btz655 · ExternalCitation · doi-reference
PubTator 3.0: an AI-powered literature resource for unlocking biomedical knowledge
10.1093/nar/gkae235 · ExternalCitation · doi-reference
ConsensusPathDB: toward a more complete picture of cell biology
10.1093/nar/gkq1156 · ExternalCitation · doi-reference
Functional impact bias reveals cancer drivers
10.1093/nar/gks743 · ExternalCitation · doi-reference
STRING v11: protein-protein association networks with increased coverage, supporting functional discovery in genome-wide experimental datasets
10.1093/nar/gky1131 · ExternalCitation · doi-reference
GEPIA2: an enhanced web server for large-scale expression profiling and interactive analysis
10.1093/nar/gkz430 · ExternalCitation · doi-reference
De novo discovery of mutated driver pathways in cancer
10.1101/gr.120477.111 · ExternalCitation · doi-reference
Mutual exclusivity analysis identifies oncogenic network modules
10.1101/gr.125567.111 · ExternalCitation · doi-reference
MuSiC: identifying mutational significance in cancer genomes
10.1101/gr.134635.111 · ExternalCitation · doi-reference
Cancer genome landscapes
10.1126/science.1235122 · ExternalCitation · doi-reference
Cancer-specific high-throughput annotation of somatic mutations: computational prediction of driver missense mutations
10.1158/0008-5472.can-09-1133 · ExternalCitation · doi-reference
Endocrine-resistant breast cancer: mechanisms and treatment
10.1159/000508675 · ExternalCitation · doi-reference
A human functional protein interaction network and its application to cancer data analysis
10.1186/gb-2010-11-5-r53 · ExternalCitation · doi-reference
DriverNet: uncovering the impact of somatic driver mutations on transcriptional networks in cancer
10.1186/gb-2012-13-12-r124 · ExternalCitation · doi-reference
A random walk-based method to identify driver genes by integrating the subcellular localization and variation frequency into bipartite graph
10.1186/s12859-019-2847-9 · ExternalCitation · doi-reference
DriverRWH: discovering cancer driver genes by random walk on a gene mutation hypergraph
10.1186/s12859-022-04788-7 · ExternalCitation · doi-reference
Identifying cancer driver genes based on multi-view heterogeneous graph convolutional network and self-attention mechanism
10.1186/s12859-023-05140-3 · ExternalCitation · doi-reference
The Network of Cancer Genes (NCG): a comprehensive catalogue of known and candidate cancer genes from cancer sequencing screens
10.1186/s13059-018-1612-0 · ExternalCitation · doi-reference
DawnRank: discovering personalized driver genes in cancer
10.1186/s13073-014-0056-8 · ExternalCitation · doi-reference
OncoKB: a precision oncology knowledge base
10.1200/po.17.00011 · ExternalCitation · doi-reference
Interpretation of Genomic Variants Using a Unified Biological Network Approach
10.1371/journal.pcbi.1002886 · ExternalCitation · doi-reference
MONet: cancer driver gene identification algorithm based on integrated analysis of multi-omics data and network models
10.3389/ebm.2025.10399 · ExternalCitation · doi-reference
RBM22, a key player of pre-mRNA splicing and gene expression regulation, is altered in cancer
10.3390/cancers14030643 · ExternalCitation · doi-reference
SSCI: self-supervised deep learning improves network structure for cancer driver gene identification
10.3390/ijms251910351 · ExternalCitation · doi-reference
EXOSC10 is a novel hepatocellular carcinoma prognostic biomarker: a comprehensive bioinformatics analysis and experiment verification
10.7717/peerj.15860 · ExternalCitation · doi-reference
