BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

167 related articles for article (PubMed ID: 33733356)

  • 1. Brief Survey on Machine Learning in Epistasis.
    Chicco D; Faultless T
    Methods Mol Biol; 2021; 2212():169-179. PubMed ID: 33733356
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Protocol for Epistasis Detection with Machine Learning Using GenEpi Package.
    Petinrin OO; Wong KC
    Methods Mol Biol; 2021; 2212():291-305. PubMed ID: 33733363
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Genotype distribution-based inference of collective effects in genome-wide association studies: insights to age-related macular degeneration disease mechanism.
    Woo HJ; Yu C; Kumar K; Gold B; Reifman J
    BMC Genomics; 2016 Aug; 17(1):695. PubMed ID: 27576376
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Epistasis Analysis: Classification Through Machine Learning Methods.
    Liu L; Wong KC
    Methods Mol Biol; 2021; 2212():337-345. PubMed ID: 33733366
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Machine learning approaches for the discovery of gene-gene interactions in disease data.
    Upstill-Goddard R; Eccles D; Fliege J; Collins A
    Brief Bioinform; 2013 Mar; 14(2):251-60. PubMed ID: 22611119
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Epistasis Detection Based on Epi-GTBN.
    Chen X; Wong KC
    Methods Mol Biol; 2021; 2212():325-335. PubMed ID: 33733365
    [TBL] [Abstract][Full Text] [Related]  

  • 7. WISH-R- a fast and efficient tool for construction of epistatic networks for complex traits and diseases.
    Carmelo VAO; Kogelman LJA; Madsen MB; Kadarmideen HN
    BMC Bioinformatics; 2018 Jul; 19(1):277. PubMed ID: 30064383
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Genetic interactions effects for cancer disease identification using computational models: a review.
    Manavalan R; Priya S
    Med Biol Eng Comput; 2021 Apr; 59(4):733-758. PubMed ID: 33839998
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Introducing Machine Learning Concepts with WEKA.
    Smith TC; Frank E
    Methods Mol Biol; 2016; 1418():353-78. PubMed ID: 27008023
    [TBL] [Abstract][Full Text] [Related]  

  • 10. MUSE: A MULTI-LOCUS SAMPLING-BASED EPISTASIS ALGORITHM FOR QUANTITATIVE GENETIC TRAIT PREDICTION.
    He D; Parida L
    Pac Symp Biocomput; 2017; 22():426-437. PubMed ID: 27896995
    [TBL] [Abstract][Full Text] [Related]  

  • 11. GenEpi: gene-based epistasis discovery using machine learning.
    Chang YC; Wu JT; Hong MY; Tung YA; Hsieh PH; Yee SW; Giacomini KM; Oyang YJ; Chen CY;
    BMC Bioinformatics; 2020 Feb; 21(1):68. PubMed ID: 32093643
    [TBL] [Abstract][Full Text] [Related]  

  • 12. A deep hybrid model to detect multi-locus interacting SNPs in the presence of noise.
    Uppu S; Krishna A
    Int J Med Inform; 2018 Nov; 119():134-151. PubMed ID: 30342681
    [TBL] [Abstract][Full Text] [Related]  

  • 13. A review for detecting gene-gene interactions using machine learning methods in genetic epidemiology.
    Koo CL; Liew MJ; Mohamad MS; Salleh AH
    Biomed Res Int; 2013; 2013():432375. PubMed ID: 24228248
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Two-Stage Testing for Epistasis: Screening and Verification.
    Pecanka J; Jonker MA
    Methods Mol Biol; 2021; 2212():69-92. PubMed ID: 33733351
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Genome-wide association data classification and SNPs selection using two-stage quality-based Random Forests.
    Nguyen TT; Huang J; Wu Q; Nguyen T; Li M
    BMC Genomics; 2015; 16 Suppl 2(Suppl 2):S5. PubMed ID: 25708662
    [TBL] [Abstract][Full Text] [Related]  

  • 16. A Review on Methods for Detecting SNP Interactions in High-Dimensional Genomic Data.
    Uppu S; Krishna A; Gopalan RP
    IEEE/ACM Trans Comput Biol Bioinform; 2018; 15(2):599-612. PubMed ID: 28060710
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Bridging heterogeneous mutation data to enhance disease gene discovery.
    Zhou K; Wang Y; Bretonnel Cohen K; Kim JD; Ma X; Shen Z; Meng X; Xia J
    Brief Bioinform; 2021 Sep; 22(5):. PubMed ID: 33847357
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Revisiting genome-wide association studies from statistical modelling to machine learning.
    Sun S; Dong B; Zou Q
    Brief Bioinform; 2021 Jul; 22(4):. PubMed ID: 33126243
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Epi-GTBN: an approach of epistasis mining based on genetic Tabu algorithm and Bayesian network.
    Guo Y; Zhong Z; Yang C; Hu J; Jiang Y; Liang Z; Gao H; Liu J
    BMC Bioinformatics; 2019 Aug; 20(1):444. PubMed ID: 31455207
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Protocol for Construction of Genome-Wide Epistatic SNP Networks Using WISH-R Package.
    Kadarmideen HN; Carmelo VAO
    Methods Mol Biol; 2021; 2212():155-168. PubMed ID: 33733355
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 9.