BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

148 related articles for article (PubMed ID: 31782759)

  • 1. Predicting synthetic lethal interactions using heterogeneous data sources.
    Liany H; Jeyasekharan A; Rajan V
    Bioinformatics; 2020 Apr; 36(7):2209-2216. PubMed ID: 31782759
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Graph contextualized attention network for predicting synthetic lethality in human cancers.
    Long Y; Wu M; Liu Y; Zheng J; Kwoh CK; Luo J; Li X
    Bioinformatics; 2021 Aug; 37(16):2432-2440. PubMed ID: 33609108
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Neural Collective Matrix Factorization for integrated analysis of heterogeneous biomedical data.
    Mariappan R; Jayagopal A; Sien HZ; Rajan V
    Bioinformatics; 2022 Sep; 38(19):4554-4561. PubMed ID: 35929808
    [TBL] [Abstract][Full Text] [Related]  

  • 4. DRIMC: an improved drug repositioning approach using Bayesian inductive matrix completion.
    Zhang W; Xu H; Li X; Gao Q; Wang L
    Bioinformatics; 2020 May; 36(9):2839-2847. PubMed ID: 31999326
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Predicting synthetic lethal interactions in human cancers using graph regularized self-representative matrix factorization.
    Huang J; Wu M; Lu F; Ou-Yang L; Zhu Z
    BMC Bioinformatics; 2019 Dec; 20(Suppl 19):657. PubMed ID: 31870274
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Dual-dropout graph convolutional network for predicting synthetic lethality in human cancers.
    Cai R; Chen X; Fang Y; Wu M; Hao Y
    Bioinformatics; 2020 Aug; 36(16):4458-4465. PubMed ID: 32221609
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Drug response prediction by inferring pathway-response associations with kernelized Bayesian matrix factorization.
    Ammad-Ud-Din M; Khan SA; Malani D; Murumägi A; Kallioniemi O; Aittokallio T; Kaski S
    Bioinformatics; 2016 Sep; 32(17):i455-i463. PubMed ID: 27587662
    [TBL] [Abstract][Full Text] [Related]  

  • 8. KG4SL: knowledge graph neural network for synthetic lethality prediction in human cancers.
    Wang S; Xu F; Li Y; Wang J; Zhang K; Liu Y; Wu M; Zheng J
    Bioinformatics; 2021 Jul; 37(Suppl_1):i418-i425. PubMed ID: 34252965
    [TBL] [Abstract][Full Text] [Related]  

  • 9. NSF4SL: negative-sample-free contrastive learning for ranking synthetic lethal partner genes in human cancers.
    Wang S; Feng Y; Liu X; Liu Y; Wu M; Zheng J
    Bioinformatics; 2022 Sep; 38(Suppl_2):ii13-ii19. PubMed ID: 36124790
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Gene prioritization using Bayesian matrix factorization with genomic and phenotypic side information.
    Zakeri P; Simm J; Arany A; ElShal S; Moreau Y
    Bioinformatics; 2018 Jul; 34(13):i447-i456. PubMed ID: 29949967
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Overcoming selection bias in synthetic lethality prediction.
    Seale C; Tepeli Y; Gonçalves JP
    Bioinformatics; 2022 Sep; 38(18):4360-4368. PubMed ID: 35876858
    [TBL] [Abstract][Full Text] [Related]  

  • 12. ASTER: A Method to Predict Clinically Relevant Synthetic Lethal Genetic Interactions.
    Liany H; Jayagopal A; Huang D; Lim JQ; Nbh NI; Jeyasekharan A; Ong CK; Rajan V
    IEEE J Biomed Health Inform; 2024 Mar; 28(3):1785-1796. PubMed ID: 38227408
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Ensembling graph attention networks for human microbe-drug association prediction.
    Long Y; Wu M; Liu Y; Kwoh CK; Luo J; Li X
    Bioinformatics; 2020 Dec; 36(Suppl_2):i779-i786. PubMed ID: 33381844
    [TBL] [Abstract][Full Text] [Related]  

  • 14. SoFIA: a data integration framework for annotating high-throughput datasets.
    Childs LH; Mamlouk S; Brandt J; Sers C; Leser U
    Bioinformatics; 2016 Sep; 32(17):2590-7. PubMed ID: 27187206
    [TBL] [Abstract][Full Text] [Related]  

  • 15. BioERP: biomedical heterogeneous network-based self-supervised representation learning approach for entity relationship predictions.
    Wang X; Yang Y; Li K; Li W; Li F; Peng S
    Bioinformatics; 2021 Dec; 37(24):4793-4800. PubMed ID: 34329382
    [TBL] [Abstract][Full Text] [Related]  

  • 16. TCGA-assembler 2: software pipeline for retrieval and processing of TCGA/CPTAC data.
    Wei L; Jin Z; Yang S; Xu Y; Zhu Y; Ji Y
    Bioinformatics; 2018 May; 34(9):1615-1617. PubMed ID: 29272348
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Orthogonal matrix factorization enables integrative analysis of multiple RNA binding proteins.
    Stražar M; Žitnik M; Zupan B; Ule J; Curk T
    Bioinformatics; 2016 May; 32(10):1527-35. PubMed ID: 26787667
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Onto2Vec: joint vector-based representation of biological entities and their ontology-based annotations.
    Smaili FZ; Gao X; Hoehndorf R
    Bioinformatics; 2018 Jul; 34(13):i52-i60. PubMed ID: 29949999
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Fast-SL: an efficient algorithm to identify synthetic lethal sets in metabolic networks.
    Pratapa A; Balachandran S; Raman K
    Bioinformatics; 2015 Oct; 31(20):3299-305. PubMed ID: 26085504
    [TBL] [Abstract][Full Text] [Related]  

  • 20. SLGNN: synthetic lethality prediction in human cancers based on factor-aware knowledge graph neural network.
    Zhu Y; Zhou Y; Liu Y; Wang X; Li J
    Bioinformatics; 2023 Feb; 39(2):. PubMed ID: 36645245
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 8.