BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

220 related articles for article (PubMed ID: 30717303)

  • 1. Self-Adjusting Ant Colony Optimization Based on Information Entropy for Detecting Epistatic Interactions.
    Guan B; Zhao Y
    Genes (Basel); 2019 Feb; 10(2):. PubMed ID: 30717303
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Ant colony optimization with an automatic adjustment mechanism for detecting epistatic interactions.
    Guan B; Zhao Y; Sun W
    Comput Biol Chem; 2018 Dec; 77():354-362. PubMed ID: 30466044
    [TBL] [Abstract][Full Text] [Related]  

  • 3. epiACO - a method for identifying epistasis based on ant Colony optimization algorithm.
    Sun Y; Shang J; Liu JX; Li S; Zheng CH
    BioData Min; 2017; 10():23. PubMed ID: 28694848
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Introducing Heuristic Information Into Ant Colony Optimization Algorithm for Identifying Epistasis.
    Sun Y; Wang X; Shang J; Liu JX; Zheng CH; Lei X
    IEEE/ACM Trans Comput Biol Bioinform; 2020; 17(4):1253-1261. PubMed ID: 30403637
    [TBL] [Abstract][Full Text] [Related]  

  • 5. AntEpiSeeker: detecting epistatic interactions for case-control studies using a two-stage ant colony optimization algorithm.
    Wang Y; Liu X; Robbins K; Rekaya R
    BMC Res Notes; 2010 Apr; 3():117. PubMed ID: 20426808
    [TBL] [Abstract][Full Text] [Related]  

  • 6. CINOEDV: a co-information based method for detecting and visualizing n-order epistatic interactions.
    Shang J; Sun Y; Liu JX; Xia J; Zhang J; Zheng CH
    BMC Bioinformatics; 2016 May; 17(1):214. PubMed ID: 27184783
    [TBL] [Abstract][Full Text] [Related]  

  • 7. SAMA: A Fast Self-Adaptive Memetic Algorithm for Detecting SNP-SNP Interactions Associated with Disease.
    Yin Y; Guan B; Zhao Y; Li Y
    Biomed Res Int; 2020; 2020():5610658. PubMed ID: 32908899
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Cloud computing for detecting high-order genome-wide epistatic interaction via dynamic clustering.
    Guo X; Meng Y; Yu N; Pan Y
    BMC Bioinformatics; 2014 Apr; 15():102. PubMed ID: 24717145
    [TBL] [Abstract][Full Text] [Related]  

  • 9. A Markov blanket-based method for detecting causal SNPs in GWAS.
    Han B; Park M; Chen XW
    BMC Bioinformatics; 2010 Apr; 11 Suppl 3(Suppl 3):S5. PubMed ID: 20438652
    [TBL] [Abstract][Full Text] [Related]  

  • 10. 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]  

  • 11. 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]  

  • 12. A Novel Multitasking Ant Colony Optimization Method for Detecting Multiorder SNP Interactions.
    Tuo S; Li C; Liu F; Zhu Y; Chen T; Feng Z; Liu H; Li A
    Interdiscip Sci; 2022 Dec; 14(4):814-832. PubMed ID: 35788965
    [TBL] [Abstract][Full Text] [Related]  

  • 13. IPP: An Intelligent Privacy-Preserving Scheme for Detecting Interactions in Genome Association Studies.
    Wang H; Wu X
    IEEE/ACM Trans Comput Biol Bioinform; 2023; 20(1):455-464. PubMed ID: 35239492
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Fast detection of high-order epistatic interactions in genome-wide association studies using information theoretic measure.
    Leem S; Jeong HH; Lee J; Wee K; Sohn KA
    Comput Biol Chem; 2014 Jun; 50():19-28. PubMed ID: 24581733
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Detecting genome-wide epistases based on the clustering of relatively frequent items.
    Xie M; Li J; Jiang T
    Bioinformatics; 2012 Jan; 28(1):5-12. PubMed ID: 22053078
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Evaluating the detection ability of a range of epistasis detection methods on simulated data for pure and impure epistatic models.
    Russ D; Williams JA; Cardoso VR; Bravo-Merodio L; Pendleton SC; Aziz F; Acharjee A; Gkoutos GV
    PLoS One; 2022; 17(2):e0263390. PubMed ID: 35180244
    [TBL] [Abstract][Full Text] [Related]  

  • 17. SNPHarvester: a filtering-based approach for detecting epistatic interactions in genome-wide association studies.
    Yang C; He Z; Wan X; Yang Q; Xue H; Yu W
    Bioinformatics; 2009 Feb; 25(4):504-11. PubMed ID: 19098029
    [TBL] [Abstract][Full Text] [Related]  

  • 18. MDSN: A Module Detection Method for Identifying High-Order Epistatic Interactions.
    Sun Y; Gu Y; Ren Q; Li Y; Shang J; Liu JX; Guan B
    Genes (Basel); 2022 Dec; 13(12):. PubMed ID: 36553670
    [TBL] [Abstract][Full Text] [Related]  

  • 19. MACOED: a multi-objective ant colony optimization algorithm for SNP epistasis detection in genome-wide association studies.
    Jing PJ; Shen HB
    Bioinformatics; 2015 Mar; 31(5):634-41. PubMed ID: 25338719
    [TBL] [Abstract][Full Text] [Related]  

  • 20. ClusterMI: Detecting High-Order SNP Interactions Based on Clustering and Mutual Information.
    Cao X; Yu G; Liu J; Jia L; Wang J
    Int J Mol Sci; 2018 Aug; 19(8):. PubMed ID: 30072632
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 11.