251 related articles for article (PubMed ID: 27842479)
21. PCVMZM: Using the Probabilistic Classification Vector Machines Model Combined with a Zernike Moments Descriptor to Predict Protein-Protein Interactions from Protein Sequences.
Wang Y; You Z; Li X; Chen X; Jiang T; Zhang J
Int J Mol Sci; 2017 May; 18(5):. PubMed ID: 28492483
[TBL] [Abstract][Full Text] [Related]
22. Drug-target interaction prediction from PSSM based evolutionary information.
Mousavian Z; Khakabimamaghani S; Kavousi K; Masoudi-Nejad A
J Pharmacol Toxicol Methods; 2016; 78():42-51. PubMed ID: 26592807
[TBL] [Abstract][Full Text] [Related]
23. GPCR-drug interactions prediction using random forest with drug-association-matrix-based post-processing procedure.
Hu J; Li Y; Yang JY; Shen HB; Yu DJ
Comput Biol Chem; 2016 Feb; 60():59-71. PubMed ID: 26674225
[TBL] [Abstract][Full Text] [Related]
24. PreDTIs: prediction of drug-target interactions based on multiple feature information using gradient boosting framework with data balancing and feature selection techniques.
Mahmud SMH; Chen W; Liu Y; Awal MA; Ahmed K; Rahman MH; Moni MA
Brief Bioinform; 2021 Sep; 22(5):. PubMed ID: 33709119
[TBL] [Abstract][Full Text] [Related]
25. Identifying Drug-Target Interactions with Decision Templates.
Yan XY; Zhang SW
Curr Protein Pept Sci; 2018; 19(5):498-506. PubMed ID: 27829344
[TBL] [Abstract][Full Text] [Related]
26. Inferring Interactions between Novel Drugs and Novel Targets via Instance-Neighborhood-Based Models.
Shi JY; Li JX; Chen BL; Zhang Y
Curr Protein Pept Sci; 2018; 19(5):488-497. PubMed ID: 27829347
[TBL] [Abstract][Full Text] [Related]
27. Predicting Drug-Target Interactions Based on Small Positive Samples.
Hu P; Chan KCC; Hu Y
Curr Protein Pept Sci; 2018; 19(5):479-487. PubMed ID: 27829343
[TBL] [Abstract][Full Text] [Related]
28. Computational Prediction of DrugTarget Interactions Using Chemical, Biological, and Network Features.
Cao DS; Zhang LX; Tan GS; Xiang Z; Zeng WB; Xu QS; Chen AF
Mol Inform; 2014 Oct; 33(10):669-81. PubMed ID: 27485302
[TBL] [Abstract][Full Text] [Related]
29. Predicting drug-target interactions using Lasso with random forest based on evolutionary information and chemical structure.
Shi H; Liu S; Chen J; Li X; Ma Q; Yu B
Genomics; 2019 Dec; 111(6):1839-1852. PubMed ID: 30550813
[TBL] [Abstract][Full Text] [Related]
30. DP-BINDER: machine learning model for prediction of DNA-binding proteins by fusing evolutionary and physicochemical information.
Ali F; Ahmed S; Swati ZNK; Akbar S
J Comput Aided Mol Des; 2019 Jul; 33(7):645-658. PubMed ID: 31123959
[TBL] [Abstract][Full Text] [Related]
31. A Computational-Based Method for Predicting Drug-Target Interactions by Using Stacked Autoencoder Deep Neural Network.
Wang L; You ZH; Chen X; Xia SX; Liu F; Yan X; Zhou Y; Song KJ
J Comput Biol; 2018 Mar; 25(3):361-373. PubMed ID: 28891684
[TBL] [Abstract][Full Text] [Related]
32. RoFDT: Identification of Drug-Target Interactions from Protein Sequence and Drug Molecular Structure Using Rotation Forest.
Wang Y; Wang L; Wong L; Zhao B; Su X; Li Y; You Z
Biology (Basel); 2022 May; 11(5):. PubMed ID: 35625469
[TBL] [Abstract][Full Text] [Related]
33. An Ameliorated Prediction of Drug-Target Interactions Based on Multi-Scale Discrete Wavelet Transform and Network Features.
Shen C; Ding Y; Tang J; Xu X; Guo F
Int J Mol Sci; 2017 Aug; 18(8):. PubMed ID: 28813000
[TBL] [Abstract][Full Text] [Related]
34. Detection of Interactions between Proteins by Using Legendre Moments Descriptor to Extract Discriminatory Information Embedded in PSSM.
Wang YB; You ZH; Li LP; Huang YA; Yi HC
Molecules; 2017 Aug; 22(8):. PubMed ID: 28820478
[TBL] [Abstract][Full Text] [Related]
35. Predicting Protein-Protein Interactions Based on Ensemble Learning-Based Model from Protein Sequence.
Zhan X; Xiao M; You Z; Yan C; Guo J; Wang L; Sun Y; Shang B
Biology (Basel); 2022 Jun; 11(7):. PubMed ID: 36101379
[TBL] [Abstract][Full Text] [Related]
36. Predict protein structural class by incorporating two different modes of evolutionary information into Chou's general pseudo amino acid composition.
Liang Y; Zhang S
J Mol Graph Model; 2017 Nov; 78():110-117. PubMed ID: 29055184
[TBL] [Abstract][Full Text] [Related]
37. SELF-BLM: Prediction of drug-target interactions via self-training SVM.
Keum J; Nam H
PLoS One; 2017; 12(2):e0171839. PubMed ID: 28192537
[TBL] [Abstract][Full Text] [Related]
38. A set of descriptors for identifying the protein-drug interaction in cellular networking.
Nanni L; Lumini A; Brahnam S
J Theor Biol; 2014 Oct; 359():120-8. PubMed ID: 24949993
[TBL] [Abstract][Full Text] [Related]
39. EmbedDTI: Enhancing the Molecular Representations via Sequence Embedding and Graph Convolutional Network for the Prediction of Drug-Target Interaction.
Jin Y; Lu J; Shi R; Yang Y
Biomolecules; 2021 Nov; 11(12):. PubMed ID: 34944427
[TBL] [Abstract][Full Text] [Related]
40. Computational probing protein-protein interactions targeting small molecules.
Wang YC; Chen SL; Deng NY; Wang Y
Bioinformatics; 2016 Jan; 32(2):226-34. PubMed ID: 26415726
[TBL] [Abstract][Full Text] [Related]
[Previous] [Next] [New Search]
