148 related articles for article (PubMed ID: 35072838)
1. Detection of polypharmacy side effects by integrating multiple data sources and convolutional neural networks.
Lakizadeh A; Babaei M
Mol Divers; 2022 Dec; 26(6):3193-3203. PubMed ID: 35072838
[TBL] [Abstract][Full Text] [Related]
2. DeepPSE: Prediction of polypharmacy side effects by fusing deep representation of drug pairs and attention mechanism.
Lin S; Zhang G; Wei DQ; Xiong Y
Comput Biol Med; 2022 Oct; 149():105984. PubMed ID: 35994933
[TBL] [Abstract][Full Text] [Related]
3. A neural network-based method for polypharmacy side effects prediction.
Masumshah R; Aghdam R; Eslahchi C
BMC Bioinformatics; 2021 Jul; 22(1):385. PubMed ID: 34303360
[TBL] [Abstract][Full Text] [Related]
4. Modeling polypharmacy side effects with graph convolutional networks.
Zitnik M; Agrawal M; Leskovec J
Bioinformatics; 2018 Jul; 34(13):i457-i466. PubMed ID: 29949996
[TBL] [Abstract][Full Text] [Related]
5. Polypharmacy side-effect prediction with enhanced interpretability based on graph feature attention network.
Bang S; Jhee JH; Shin H
Bioinformatics; 2021 Sep; 37(18):2955-2962. PubMed ID: 33714994
[TBL] [Abstract][Full Text] [Related]
6. Multi-type feature fusion based on graph neural network for drug-drug interaction prediction.
He C; Liu Y; Li H; Zhang H; Mao Y; Qin X; Liu L; Zhang X
BMC Bioinformatics; 2022 Jun; 23(1):224. PubMed ID: 35689200
[TBL] [Abstract][Full Text] [Related]
7. MDF-SA-DDI: predicting drug-drug interaction events based on multi-source drug fusion, multi-source feature fusion and transformer self-attention mechanism.
Lin S; Wang Y; Zhang L; Chu Y; Liu Y; Fang Y; Jiang M; Wang Q; Zhao B; Xiong Y; Wei DQ
Brief Bioinform; 2022 Jan; 23(1):. PubMed ID: 34671814
[TBL] [Abstract][Full Text] [Related]
8. DPSP: a multimodal deep learning framework for polypharmacy side effects prediction.
Masumshah R; Eslahchi C
Bioinform Adv; 2023; 3(1):vbad110. PubMed ID: 37701676
[TBL] [Abstract][Full Text] [Related]
9. Predicting Adverse Drug-Drug Interactions with Neural Embedding of Semantic Predications.
Burkhardt HA; Subramanian D; Mower J; Cohen T
AMIA Annu Symp Proc; 2019; 2019():992-1001. PubMed ID: 32308896
[TBL] [Abstract][Full Text] [Related]
10. Prediction of drug-drug interaction events using graph neural networks based feature extraction.
Al-Rabeah MH; Lakizadeh A
Sci Rep; 2022 Sep; 12(1):15590. PubMed ID: 36114278
[TBL] [Abstract][Full Text] [Related]
11. Prediction of Drug-Drug Interaction Using an Attention-Based Graph Neural Network on Drug Molecular Graphs.
Feng YH; Zhang SW
Molecules; 2022 May; 27(9):. PubMed ID: 35566354
[TBL] [Abstract][Full Text] [Related]
12. A learning-based method for drug-target interaction prediction based on feature representation learning and deep neural network.
Peng J; Li J; Shang X
BMC Bioinformatics; 2020 Sep; 21(Suppl 13):394. PubMed ID: 32938374
[TBL] [Abstract][Full Text] [Related]
13. Effective knowledge graph embeddings based on multidirectional semantics relations for polypharmacy side effects prediction.
Yao J; Sun W; Jian Z; Wu Q; Wang X
Bioinformatics; 2022 Apr; 38(8):2315-2322. PubMed ID: 35176135
[TBL] [Abstract][Full Text] [Related]
14. Predicting Polypharmacy Side-effects Using Knowledge Graph Embeddings.
Nováček V; Mohamed SK
AMIA Jt Summits Transl Sci Proc; 2020; 2020():449-458. PubMed ID: 32477666
[TBL] [Abstract][Full Text] [Related]
15. Inferring Drug-Related Diseases Based on Convolutional Neural Network and Gated Recurrent Unit.
Xuan P; Zhao L; Zhang T; Ye Y; Zhang Y
Molecules; 2019 Jul; 24(15):. PubMed ID: 31349692
[TBL] [Abstract][Full Text] [Related]
16. DPDDI: a deep predictor for drug-drug interactions.
Feng YH; Zhang SW; Shi JY
BMC Bioinformatics; 2020 Sep; 21(1):419. PubMed ID: 32972364
[TBL] [Abstract][Full Text] [Related]
17. Inferring Drug-Target Interactions Based on Random Walk and Convolutional Neural Network.
Xu X; Xuan P; Zhang T; Chen B; Sheng N
IEEE/ACM Trans Comput Biol Bioinform; 2022; 19(4):2294-2304. PubMed ID: 33729947
[TBL] [Abstract][Full Text] [Related]
18. SPARSE: a sparse hypergraph neural network for learning multiple types of latent combinations to accurately predict drug-drug interactions.
Nguyen DA; Nguyen CH; Petschner P; Mamitsuka H
Bioinformatics; 2022 Jun; 38(Suppl 1):i333-i341. PubMed ID: 35758803
[TBL] [Abstract][Full Text] [Related]
19. Identifying relations of medications with adverse drug events using recurrent convolutional neural networks and gradient boosting.
Yang X; Bian J; Fang R; Bjarnadottir RI; Hogan WR; Wu Y
J Am Med Inform Assoc; 2020 Jan; 27(1):65-72. PubMed ID: 31504605
[TBL] [Abstract][Full Text] [Related]
20. Identifying drug-target interactions via heterogeneous graph attention networks combined with cross-modal similarities.
Jiang L; Sun J; Wang Y; Ning Q; Luo N; Yin M
Brief Bioinform; 2022 Mar; 23(2):. PubMed ID: 35224614
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]