BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

207 related articles for article (PubMed ID: 35180244)

  • 21. KNN-MDR: a learning approach for improving interactions mapping performances in genome wide association studies.
    Abo Alchamlat S; Farnir F
    BMC Bioinformatics; 2017 Mar; 18(1):184. PubMed ID: 28327091
    [TBL] [Abstract][Full Text] [Related]  

  • 22. A flexible computational framework for detecting, characterizing, and interpreting statistical patterns of epistasis in genetic studies of human disease susceptibility.
    Moore JH; Gilbert JC; Tsai CT; Chiang FT; Holden T; Barney N; White BC
    J Theor Biol; 2006 Jul; 241(2):252-61. PubMed ID: 16457852
    [TBL] [Abstract][Full Text] [Related]  

  • 23. GWIS--model-free, fast and exhaustive search for epistatic interactions in case-control GWAS.
    Goudey B; Rawlinson D; Wang Q; Shi F; Ferra H; Campbell RM; Stern L; Inouye MT; Ong CS; Kowalczyk A
    BMC Genomics; 2013; 14 Suppl 3(Suppl 3):S10. PubMed ID: 23819779
    [TBL] [Abstract][Full Text] [Related]  

  • 24. Performance analysis of novel methods for detecting epistasis.
    Shang J; Zhang J; Sun Y; Liu D; Ye D; Yin Y
    BMC Bioinformatics; 2011 Dec; 12():475. PubMed ID: 22172045
    [TBL] [Abstract][Full Text] [Related]  

  • 25. Utilizing Deep Learning and Genome Wide Association Studies for Epistatic-Driven Preterm Birth Classification in African-American Women.
    Fergus P; Montanez CC; Abdulaimma B; Lisboa P; Chalmers C; Pineles B
    IEEE/ACM Trans Comput Biol Bioinform; 2020; 17(2):668-678. PubMed ID: 30183645
    [TBL] [Abstract][Full Text] [Related]  

  • 26. Comparative analysis of methods for detecting interacting loci.
    Chen L; Yu G; Langefeld CD; Miller DJ; Guy RT; Raghuram J; Yuan X; Herrington DM; Wang Y
    BMC Genomics; 2011 Jul; 12():344. PubMed ID: 21729295
    [TBL] [Abstract][Full Text] [Related]  

  • 27. A unified model based multifactor dimensionality reduction framework for detecting gene-gene interactions.
    Yu W; Lee S; Park T
    Bioinformatics; 2016 Sep; 32(17):i605-i610. PubMed ID: 27587680
    [TBL] [Abstract][Full Text] [Related]  

  • 28. A comparison of multifactor dimensionality reduction and L1-penalized regression to identify gene-gene interactions in genetic association studies.
    Winham S; Wang C; Motsinger-Reif AA
    Stat Appl Genet Mol Biol; 2011; 10(1):Article 4. PubMed ID: 21291414
    [TBL] [Abstract][Full Text] [Related]  

  • 29. A Belief Degree-Associated Fuzzy Multifactor Dimensionality Reduction Framework for Epistasis Detection.
    Rahaman S; Wong KC
    Methods Mol Biol; 2021; 2212():307-323. PubMed ID: 33733364
    [TBL] [Abstract][Full Text] [Related]  

  • 30. Gene, pathway and network frameworks to identify epistatic interactions of single nucleotide polymorphisms derived from GWAS data.
    Liu Y; Maxwell S; Feng T; Zhu X; Elston RC; Koyutürk M; Chance MR
    BMC Syst Biol; 2012; 6 Suppl 3(Suppl 3):S15. PubMed ID: 23281810
    [TBL] [Abstract][Full Text] [Related]  

  • 31. CMDR based differential evolution identifies the epistatic interaction in genome-wide association studies.
    Yang CH; Chuang LY; Lin YD
    Bioinformatics; 2017 Aug; 33(15):2354-2362. PubMed ID: 28379338
    [TBL] [Abstract][Full Text] [Related]  

  • 32. Enabling personal genomics with an explicit test of epistasis.
    Greene CS; Himmelstein DS; Nelson HH; Kelsey KT; Williams SM; Andrew AS; Karagas MR; Moore JH
    Pac Symp Biocomput; 2010; ():327-36. PubMed ID: 19908385
    [TBL] [Abstract][Full Text] [Related]  

  • 33. Genetic studies of complex human diseases: characterizing SNP-disease associations using Bayesian networks.
    Han B; Chen XW; Talebizadeh Z; Xu H
    BMC Syst Biol; 2012; 6 Suppl 3(Suppl 3):S14. PubMed ID: 23281790
    [TBL] [Abstract][Full Text] [Related]  

  • 34. GEP-EpiSeeker: a gene expression programming-based method for epistatic interaction detection in genome-wide association studies.
    Peng YZ; Lin Y; Huang Y; Li Y; Luo G; Liao J
    BMC Genomics; 2021 Dec; 22(Suppl 1):910. PubMed ID: 34930147
    [TBL] [Abstract][Full Text] [Related]  

  • 35. Identifying genetic interactions in genome-wide data using Bayesian networks.
    Jiang X; Barmada MM; Visweswaran S
    Genet Epidemiol; 2010 Sep; 34(6):575-81. PubMed ID: 20568290
    [TBL] [Abstract][Full Text] [Related]  

  • 36. A cross-validation procedure for general pedigrees and matched odds ratio fitness metric implemented for the multifactor dimensionality reduction pedigree disequilibrium test.
    Edwards TL; Torstensen E; Dudek S; Martin ER; Ritchie MD
    Genet Epidemiol; 2010 Feb; 34(2):194-9. PubMed ID: 19697353
    [TBL] [Abstract][Full Text] [Related]  

  • 37. First-Order Correction of Statistical Significance for Screening Two-Way Epistatic Interactions.
    Cheng L; Zhu M
    Methods Mol Biol; 2021; 2212():181-190. PubMed ID: 33733357
    [TBL] [Abstract][Full Text] [Related]  

  • 38. Epistasis, complexity, and multifactor dimensionality reduction.
    Pan Q; Hu T; Moore JH
    Methods Mol Biol; 2013; 1019():465-77. PubMed ID: 23756906
    [TBL] [Abstract][Full Text] [Related]  

  • 39. bNEAT: a Bayesian network method for detecting epistatic interactions in genome-wide association studies.
    Han B; Chen XW
    BMC Genomics; 2011; 12 Suppl 2(Suppl 2):S9. PubMed ID: 21989368
    [TBL] [Abstract][Full Text] [Related]  

  • 40. Model-Based Multifactor Dimensionality Reduction to detect epistasis for quantitative traits in the presence of error-free and noisy data.
    Mahachie John JM; Van Lishout F; Van Steen K
    Eur J Hum Genet; 2011 Jun; 19(6):696-703. PubMed ID: 21407267
    [TBL] [Abstract][Full Text] [Related]  

    [Previous]   [Next]    [New Search]
    of 11.