BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

194 related articles for article (PubMed ID: 37551622)

  • 21. VarWalker: personalized mutation network analysis of putative cancer genes from next-generation sequencing data.
    Jia P; Zhao Z
    PLoS Comput Biol; 2014 Feb; 10(2):e1003460. PubMed ID: 24516372
    [TBL] [Abstract][Full Text] [Related]  

  • 22. Inferring causal genomic alterations in breast cancer using gene expression data.
    Tran LM; Zhang B; Zhang Z; Zhang C; Xie T; Lamb JR; Dai H; Schadt EE; Zhu J
    BMC Syst Biol; 2011 Aug; 5():121. PubMed ID: 21806811
    [TBL] [Abstract][Full Text] [Related]  

  • 23. A novel network control model for identifying personalized driver genes in cancer.
    Guo WF; Zhang SW; Zeng T; Li Y; Gao J; Chen L
    PLoS Comput Biol; 2019 Nov; 15(11):e1007520. PubMed ID: 31765387
    [TBL] [Abstract][Full Text] [Related]  

  • 24. Prediction of potential drivers connecting different dysfunctional levels in lung adenocarcinoma via a protein-protein interaction network.
    Yuan F; Lu W
    Biochim Biophys Acta Mol Basis Dis; 2018 Jun; 1864(6 Pt B):2284-2293. PubMed ID: 29197663
    [TBL] [Abstract][Full Text] [Related]  

  • 25. GenHITS: A network science approach to driver gene detection in human regulatory network using gene's influence evaluation.
    Akhavan-Safar M; Teimourpour B; Kargari M
    J Biomed Inform; 2021 Feb; 114():103661. PubMed ID: 33326867
    [TBL] [Abstract][Full Text] [Related]  

  • 26. DriverNet: uncovering the impact of somatic driver mutations on transcriptional networks in cancer.
    Bashashati A; Haffari G; Ding J; Ha G; Lui K; Rosner J; Huntsman DG; Caldas C; Aparicio SA; Shah SP
    Genome Biol; 2012 Dec; 13(12):R124. PubMed ID: 23383675
    [TBL] [Abstract][Full Text] [Related]  

  • 27. DrGA: cancer driver gene analysis in a simpler manner.
    Nguyen QH; Nguyen T; Le DH
    BMC Bioinformatics; 2022 Mar; 23(1):86. PubMed ID: 35247965
    [TBL] [Abstract][Full Text] [Related]  

  • 28. Prediction of cancer driver genes through network-based moment propagation of mutation scores.
    Gumpinger AC; Lage K; Horn H; Borgwardt K
    Bioinformatics; 2020 Jul; 36(Suppl_1):i508-i515. PubMed ID: 32657361
    [TBL] [Abstract][Full Text] [Related]  

  • 29. DEOD: uncovering dominant effects of cancer-driver genes based on a partial covariance selection method.
    Amgalan B; Lee H
    Bioinformatics; 2015 Aug; 31(15):2452-60. PubMed ID: 25819079
    [TBL] [Abstract][Full Text] [Related]  

  • 30. DriverML: a machine learning algorithm for identifying driver genes in cancer sequencing studies.
    Han Y; Yang J; Qian X; Cheng WC; Liu SH; Hua X; Zhou L; Yang Y; Wu Q; Liu P; Lu Y
    Nucleic Acids Res; 2019 May; 47(8):e45. PubMed ID: 30773592
    [TBL] [Abstract][Full Text] [Related]  

  • 31. PhenoDriver: interpretable framework for studying personalized phenotype-associated driver genes in breast cancer.
    Li Y; Zhang SW; Xie MY; Zhang T
    Brief Bioinform; 2023 Sep; 24(5):. PubMed ID: 37738403
    [TBL] [Abstract][Full Text] [Related]  

  • 32. Somatic selection distinguishes oncogenes and tumor suppressor genes.
    Chandrashekar P; Ahmadinejad N; Wang J; Sekulic A; Egan JB; Asmann YW; Kumar S; Maley C; Liu L
    Bioinformatics; 2020 Mar; 36(6):1712-1717. PubMed ID: 32176769
    [TBL] [Abstract][Full Text] [Related]  

  • 33. Mutational Profiling of Driver Tumor Suppressor and Oncogenic Genes in Brazilian Malignant Pleural Mesotheliomas.
    Campanella NC; Silva EC; Dix G; de Lima Vazquez F; Escremim de Paula F; Berardinelli GN; Balancin M; Chammas R; Mendoza Lopez RV; Silveira HCS; Capelozzi VL; Reis RM
    Pathobiology; 2020; 87(3):208-216. PubMed ID: 32369821
    [TBL] [Abstract][Full Text] [Related]  

  • 34. Identification of mutated core cancer modules by integrating somatic mutation, copy number variation, and gene expression data.
    Zhang J; Zhang S; Wang Y; Zhang XS
    BMC Syst Biol; 2013; 7 Suppl 2(Suppl 2):S4. PubMed ID: 24565034
    [TBL] [Abstract][Full Text] [Related]  

  • 35. Somatic Mutational Landscape of Splicing Factor Genes and Their Functional Consequences across 33 Cancer Types.
    Seiler M; Peng S; Agrawal AA; Palacino J; Teng T; Zhu P; Smith PG; ; Buonamici S; Yu L
    Cell Rep; 2018 Apr; 23(1):282-296.e4. PubMed ID: 29617667
    [TBL] [Abstract][Full Text] [Related]  

  • 36. Comprehensive patient-level classification and quantification of driver events in TCGA PanCanAtlas cohorts.
    Vyatkin AD; Otnyukov DV; Leonov SV; Belikov AV
    PLoS Genet; 2022 Jan; 18(1):e1009996. PubMed ID: 35030162
    [TBL] [Abstract][Full Text] [Related]  

  • 37. IDENTIFY CANCER DRIVER GENES THROUGH SHARED MENDELIAN DISEASE PATHOGENIC VARIANTS AND CANCER SOMATIC MUTATIONS.
    Ma M; Wang C; Glicksberg BS; Schadt EE; Li SD; Chen R
    Pac Symp Biocomput; 2017; 22():473-484. PubMed ID: 27896999
    [TBL] [Abstract][Full Text] [Related]  

  • 38. MODIG: integrating multi-omics and multi-dimensional gene network for cancer driver gene identification based on graph attention network model.
    Zhao W; Gu X; Chen S; Wu J; Zhou Z
    Bioinformatics; 2022 Oct; 38(21):4901-4907. PubMed ID: 36094338
    [TBL] [Abstract][Full Text] [Related]  

  • 39. DriverMP enables improved identification of cancer driver genes.
    Liu Y; Han J; Kong T; Xiao N; Mei Q; Liu J
    Gigascience; 2022 Dec; 12():. PubMed ID: 38091511
    [TBL] [Abstract][Full Text] [Related]  

  • 40. ProcessDriver: A computational pipeline to identify copy number drivers and associated disrupted biological processes in cancer.
    Baur B; Bozdag S
    Genomics; 2017 Jul; 109(3-4):233-240. PubMed ID: 28438487
    [TBL] [Abstract][Full Text] [Related]  

    [Previous]   [Next]    [New Search]
    of 10.