270 related articles for article (PubMed ID: 34252965)
21. 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]
22. Prediction of gene co-expression from chromatin contacts with graph attention network.
Zhang K; Wang C; Sun L; Zheng J
Bioinformatics; 2022 Sep; 38(19):4457-4465. PubMed ID: 35929807
[TBL] [Abstract][Full Text] [Related]
23. SLKB: synthetic lethality knowledge base.
Gökbağ B; Tang S; Fan K; Cheng L; Yu L; Zhao Y; Li L
Nucleic Acids Res; 2024 Jan; 52(D1):D1418-D1428. PubMed ID: 37889037
[TBL] [Abstract][Full Text] [Related]
24. DeepRank-GNN: a graph neural network framework to learn patterns in protein-protein interfaces.
Réau M; Renaud N; Xue LC; Bonvin AMJJ
Bioinformatics; 2023 Jan; 39(1):. PubMed ID: 36420989
[TBL] [Abstract][Full Text] [Related]
25. 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]
26. XGraphBoost: Extracting Graph Neural Network-Based Features for a Better Prediction of Molecular Properties.
Deng D; Chen X; Zhang R; Lei Z; Wang X; Zhou F
J Chem Inf Model; 2021 Jun; 61(6):2697-2705. PubMed ID: 34009965
[TBL] [Abstract][Full Text] [Related]
27. TARSL: Triple-attention cross-network representation learning to predict synthetic lethality for anti-cancer drug discovery.
Li J; Lu X; Jiang K; Tang D; Ning B; Sun F
IEEE J Biomed Health Inform; 2023 Aug; PP():. PubMed ID: 37603479
[TBL] [Abstract][Full Text] [Related]
28. Domain-adaptive message passing graph neural network.
Shen X; Pan S; Choi KS; Zhou X
Neural Netw; 2023 Jul; 164():439-454. PubMed ID: 37182346
[TBL] [Abstract][Full Text] [Related]
29. MAGCN: A Multiple Attention Graph Convolution Networks for Predicting Synthetic Lethality.
Lu X; Chen G; Li J; Hu X; Sun F
IEEE/ACM Trans Comput Biol Bioinform; 2023; 20(5):2681-2689. PubMed ID: 36374879
[TBL] [Abstract][Full Text] [Related]
30. SS-GNN: A Simple-Structured Graph Neural Network for Affinity Prediction.
Zhang S; Jin Y; Liu T; Wang Q; Zhang Z; Zhao S; Shan B
ACS Omega; 2023 Jun; 8(25):22496-22507. PubMed ID: 37396234
[TBL] [Abstract][Full Text] [Related]
31. In silico prediction of synthetic lethality by meta-analysis of genetic interactions, functions, and pathways in yeast and human cancer.
Wu M; Li X; Zhang F; Li X; Kwoh CK; Zheng J
Cancer Inform; 2014; 13(Suppl 3):71-80. PubMed ID: 25452682
[TBL] [Abstract][Full Text] [Related]
32. 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]
33. Compound-protein interaction prediction with end-to-end learning of neural networks for graphs and sequences.
Tsubaki M; Tomii K; Sese J
Bioinformatics; 2019 Jan; 35(2):309-318. PubMed ID: 29982330
[TBL] [Abstract][Full Text] [Related]
34. ELISL: early-late integrated synthetic lethality prediction in cancer.
Tepeli YI; Seale C; Gonçalves JP
Bioinformatics; 2024 Jan; 40(1):. PubMed ID: 38113447
[TBL] [Abstract][Full Text] [Related]
35. TGSA: protein-protein association-based twin graph neural networks for drug response prediction with similarity augmentation.
Zhu Y; Ouyang Z; Chen W; Feng R; Chen DZ; Cao J; Wu J
Bioinformatics; 2022 Jan; 38(2):461-468. PubMed ID: 34559177
[TBL] [Abstract][Full Text] [Related]
36. Cancer drug response prediction with surrogate modeling-based graph neural architecture search.
Oloulade BM; Gao J; Chen J; Al-Sabri R; Wu Z
Bioinformatics; 2023 Aug; 39(8):. PubMed ID: 37555809
[TBL] [Abstract][Full Text] [Related]
37. Metapath-aggregated heterogeneous graph neural network for drug-target interaction prediction.
Li M; Cai X; Xu S; Ji H
Brief Bioinform; 2023 Jan; 24(1):. PubMed ID: 36592060
[TBL] [Abstract][Full Text] [Related]
38. DiscoverSL: an R package for multi-omic data driven prediction of synthetic lethality in cancers.
Das S; Deng X; Camphausen K; Shankavaram U
Bioinformatics; 2019 Feb; 35(4):701-702. PubMed ID: 30059974
[TBL] [Abstract][Full Text] [Related]
39. IIFDTI: predicting drug-target interactions through interactive and independent features based on attention mechanism.
Cheng Z; Zhao Q; Li Y; Wang J
Bioinformatics; 2022 Sep; 38(17):4153-4161. PubMed ID: 35801934
[TBL] [Abstract][Full Text] [Related]
40. DeepLGP: a novel deep learning method for prioritizing lncRNA target genes.
Zhao T; Hu Y; Peng J; Cheng L
Bioinformatics; 2020 Aug; 36(16):4466-4472. PubMed ID: 32467970
[TBL] [Abstract][Full Text] [Related]
[Previous] [Next] [New Search]