226 related articles for article (PubMed ID: 26683094)
61. Inference of patient-specific pathway activities from multi-dimensional cancer genomics data using PARADIGM.
Vaske CJ; Benz SC; Sanborn JZ; Earl D; Szeto C; Zhu J; Haussler D; Stuart JM
Bioinformatics; 2010 Jun; 26(12):i237-45. PubMed ID: 20529912
[TBL] [Abstract][Full Text] [Related]
62. Large-scale profiling of microRNAs for The Cancer Genome Atlas.
Chu A; Robertson G; Brooks D; Mungall AJ; Birol I; Coope R; Ma Y; Jones S; Marra MA
Nucleic Acids Res; 2016 Jan; 44(1):e3. PubMed ID: 26271990
[TBL] [Abstract][Full Text] [Related]
63. Single cell genomics reveals activation signatures of endogenous SCAR's networks in aneuploid human embryos and clinically intractable malignant tumors.
Glinsky GV
Cancer Lett; 2016 Oct; 381(1):176-93. PubMed ID: 27497790
[TBL] [Abstract][Full Text] [Related]
64. Automated deconvolution of structured mixtures from heterogeneous tumor genomic data.
Roman T; Xie L; Schwartz R
PLoS Comput Biol; 2017 Oct; 13(10):e1005815. PubMed ID: 29059177
[TBL] [Abstract][Full Text] [Related]
65. TCGA-TCIA Impact on Radiogenomics Cancer Research: A Systematic Review.
Zanfardino M; Pane K; Mirabelli P; Salvatore M; Franzese M
Int J Mol Sci; 2019 Nov; 20(23):. PubMed ID: 31795520
[TBL] [Abstract][Full Text] [Related]
66. Leveraging protein dynamics to identify cancer mutational hotspots using 3D structures.
Kumar S; Clarke D; Gerstein MB
Proc Natl Acad Sci U S A; 2019 Sep; 116(38):18962-18970. PubMed ID: 31462496
[TBL] [Abstract][Full Text] [Related]
67. MONET: Multi-omic module discovery by omic selection.
Rappoport N; Safra R; Shamir R
PLoS Comput Biol; 2020 Sep; 16(9):e1008182. PubMed ID: 32931516
[TBL] [Abstract][Full Text] [Related]
68. Expanding the computational toolbox for mining cancer genomes.
Ding L; Wendl MC; McMichael JF; Raphael BJ
Nat Rev Genet; 2014 Aug; 15(8):556-70. PubMed ID: 25001846
[TBL] [Abstract][Full Text] [Related]
69. Disease gene-fishing in molecular interaction networks: a case study in colorectal cancer.
Huang H; Li J; Chen JY
Annu Int Conf IEEE Eng Med Biol Soc; 2009; 2009():6416-9. PubMed ID: 19964422
[TBL] [Abstract][Full Text] [Related]
70. Unified feature association networks through integration of transcriptomic and proteomic data.
McClure RS; Wendler JP; Adkins JN; Swanstrom J; Baric R; Kaiser BLD; Oxford KL; Waters KM; McDermott JE
PLoS Comput Biol; 2019 Sep; 15(9):e1007241. PubMed ID: 31527878
[TBL] [Abstract][Full Text] [Related]
71. Mining breast cancer genes with a network based noise-tolerant approach.
Nie Y; Yu J
BMC Syst Biol; 2013 Jun; 7():49. PubMed ID: 23799982
[TBL] [Abstract][Full Text] [Related]
72. MOSClip: multi-omic and survival pathway analysis for the identification of survival associated gene and modules.
Martini P; Chiogna M; Calura E; Romualdi C
Nucleic Acids Res; 2019 Aug; 47(14):e80. PubMed ID: 31049575
[TBL] [Abstract][Full Text] [Related]
73. Genome-wide approaches for cancer gene discovery.
Lizardi PM; Forloni M; Wajapeyee N
Trends Biotechnol; 2011 Nov; 29(11):558-68. PubMed ID: 21757246
[TBL] [Abstract][Full Text] [Related]
74. Multi-omic tumor data reveal diversity of molecular mechanisms that correlate with survival.
Ramazzotti D; Lal A; Wang B; Batzoglou S; Sidow A
Nat Commun; 2018 Oct; 9(1):4453. PubMed ID: 30367051
[TBL] [Abstract][Full Text] [Related]
75. Identifying gene subnetworks associated with clinical outcome in ovarian cancer using Network Based Coalition Game.
Razi A; Afghah F; Varadan V
Annu Int Conf IEEE Eng Med Biol Soc; 2015; 2015():6509-13. PubMed ID: 26737784
[TBL] [Abstract][Full Text] [Related]
76. Cancer systems biology: exploring cancer-associated genes on cellular networks.
Wang E; Lenferink A; O'Connor-McCourt M
Cell Mol Life Sci; 2007 Jul; 64(14):1752-62. PubMed ID: 17415519
[TBL] [Abstract][Full Text] [Related]
77. Using drug response data to identify molecular effectors, and molecular "omic" data to identify candidate drugs in cancer.
Reinhold WC; Varma S; Rajapakse VN; Luna A; Sousa FG; Kohn KW; Pommier YG
Hum Genet; 2015 Jan; 134(1):3-11. PubMed ID: 25213708
[TBL] [Abstract][Full Text] [Related]
78. Systematic interpretation of comutated genes in large-scale cancer mutation profiles.
Gu Y; Yang D; Zou J; Ma W; Wu R; Zhao W; Zhang Y; Xiao H; Gong X; Zhang M; Zhu J; Guo Z
Mol Cancer Ther; 2010 Aug; 9(8):2186-95. PubMed ID: 20663929
[TBL] [Abstract][Full Text] [Related]
79. Interpretation of cancer mutations using a multiscale map of protein systems.
Zheng F; Kelly MR; Ramms DJ; Heintschel ML; Tao K; Tutuncuoglu B; Lee JJ; Ono K; Foussard H; Chen M; Herrington KA; Silva E; Liu SN; Chen J; Churas C; Wilson N; Kratz A; Pillich RT; Patel DN; Park J; Kuenzi B; Yu MK; Licon K; Pratt D; Kreisberg JF; Kim M; Swaney DL; Nan X; Fraley SI; Gutkind JS; Krogan NJ; Ideker T
Science; 2021 Oct; 374(6563):eabf3067. PubMed ID: 34591613
[TBL] [Abstract][Full Text] [Related]
80. Extending pathways and processes using molecular interaction networks to analyse cancer genome data.
Glaab E; Baudot A; Krasnogor N; Valencia A
BMC Bioinformatics; 2010 Dec; 11():597. PubMed ID: 21144022
[TBL] [Abstract][Full Text] [Related]
[Previous] [Next] [New Search]
