170 related articles for article (PubMed ID: 33568049)
1. Ranking cancer drivers via betweenness-based outlier detection and random walks.
Erten C; Houdjedj A; Kazan H
BMC Bioinformatics; 2021 Feb; 22(1):62. PubMed ID: 33568049
[TBL] [Abstract][Full Text] [Related]
2. Graph-theoretical comparison of normal and tumor networks in identifying BRCA genes.
Dopazo J; Erten C
BMC Syst Biol; 2017 Nov; 11(1):110. PubMed ID: 29166896
[TBL] [Abstract][Full Text] [Related]
3. PersonaDrive: a method for the identification and prioritization of personalized cancer drivers.
Erten C; Houdjedj A; Kazan H; Taleb Bahmed AA
Bioinformatics; 2022 Jun; 38(13):3407-3414. PubMed ID: 35579340
[TBL] [Abstract][Full Text] [Related]
4. DriverRWH: discovering cancer driver genes by random walk on a gene mutation hypergraph.
Wang C; Shi J; Cai J; Zhang Y; Zheng X; Zhang N
BMC Bioinformatics; 2022 Jul; 23(1):277. PubMed ID: 35831792
[TBL] [Abstract][Full Text] [Related]
5. Discovering potential cancer driver genes by an integrated network-based approach.
Shi K; Gao L; Wang B
Mol Biosyst; 2016 Aug; 12(9):2921-31. PubMed ID: 27426053
[TBL] [Abstract][Full Text] [Related]
6. A random walk-based method to identify driver genes by integrating the subcellular localization and variation frequency into bipartite graph.
Song J; Peng W; Wang F
BMC Bioinformatics; 2019 May; 20(1):238. PubMed ID: 31088372
[TBL] [Abstract][Full Text] [Related]
7. Identifying cancer driver genes based on multi-view heterogeneous graph convolutional network and self-attention mechanism.
Peng W; Wu R; Dai W; Yu N
BMC Bioinformatics; 2023 Jan; 24(1):16. PubMed ID: 36639646
[TBL] [Abstract][Full Text] [Related]
8. Oncogenes and tumor suppressor genes: comparative genomics and network perspectives.
Zhu K; Liu Q; Zhou Y; Tao C; Zhao Z; Sun J; Xu H
BMC Genomics; 2015; 16 Suppl 7(Suppl 7):S8. PubMed ID: 26099335
[TBL] [Abstract][Full Text] [Related]
9. Identifying Cancer genes by combining two-rounds RWR based on multiple biological data.
Zhang W; Lei Ieee Member X; Bian C
BMC Bioinformatics; 2019 Nov; 20(Suppl 18):518. PubMed ID: 31760937
[TBL] [Abstract][Full Text] [Related]
10. HIT'nDRIVE: patient-specific multidriver gene prioritization for precision oncology.
Shrestha R; Hodzic E; Sauerwald T; Dao P; Wang K; Yeung J; Anderson S; Vandin F; Haffari G; Collins CC; Sahinalp SC
Genome Res; 2017 Sep; 27(9):1573-1588. PubMed ID: 28768687
[TBL] [Abstract][Full Text] [Related]
11. Integrating Protein-Protein Interaction Networks and Somatic Mutation Data to Detect Driver Modules in Pan-Cancer.
Wu H; Chen Z; Wu Y; Zhang H; Liu Q
Interdiscip Sci; 2022 Mar; 14(1):151-167. PubMed ID: 34491536
[TBL] [Abstract][Full Text] [Related]
12. A Graph Convolution Network-Based Model for Prioritizing Personalized Cancer Driver Genes of Individual Patients.
Peng W; Yu P; Dai W; Fu X; Liu L; Pan Y
IEEE Trans Nanobioscience; 2023 Oct; 22(4):744-754. PubMed ID: 37195839
[TBL] [Abstract][Full Text] [Related]
13. DGMP: Identifying Cancer Driver Genes by Jointing DGCN and MLP from Multi-omics Genomic Data.
Zhang SW; Xu JY; Zhang T
Genomics Proteomics Bioinformatics; 2022 Oct; 20(5):928-938. PubMed ID: 36464123
[TBL] [Abstract][Full Text] [Related]
14. The Integrative Method Based on the Module-Network for Identifying Driver Genes in Cancer Subtypes.
Lu X; Li X; Liu P; Qian X; Miao Q; Peng S
Molecules; 2018 Jan; 23(2):. PubMed ID: 29364829
[TBL] [Abstract][Full Text] [Related]
15. A Novel Method for Identifying the Potential Cancer Driver Genes Based on Molecular Data Integration.
Zhang W; Wang SL
Biochem Genet; 2020 Feb; 58(1):16-39. PubMed ID: 31115714
[TBL] [Abstract][Full Text] [Related]
16. A novel heterophilic graph diffusion convolutional network for identifying cancer driver genes.
Zhang T; Zhang SW; Xie MY; Li Y
Brief Bioinform; 2023 May; 24(3):. PubMed ID: 37055234
[TBL] [Abstract][Full Text] [Related]
17. KatzDriver: A network based method to cancer causal genes discovery in gene regulatory network.
Akhavan-Safar M; Teimourpour B
Biosystems; 2021 Mar; 201():104326. PubMed ID: 33309969
[TBL] [Abstract][Full Text] [Related]
18. MECoRank: cancer driver genes discovery simultaneously evaluating the impact of SNVs and differential expression on transcriptional networks.
Hui Y; Wei PJ; Xia J; Wang YT; Zheng CH
BMC Med Genomics; 2019 Dec; 12(Suppl 7):140. PubMed ID: 31888623
[TBL] [Abstract][Full Text] [Related]
19. Improving cancer driver gene identification using multi-task learning on graph convolutional network.
Peng W; Tang Q; Dai W; Chen T
Brief Bioinform; 2022 Jan; 23(1):. PubMed ID: 34643232
[TBL] [Abstract][Full Text] [Related]
20. Comparative analysis of protein interactome networks prioritizes candidate genes with cancer signatures.
Li Y; Sahni N; Yi S
Oncotarget; 2016 Nov; 7(48):78841-78849. PubMed ID: 27791983
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]