181 related articles for article (PubMed ID: 33454744)
1. NCBRPred: predicting nucleic acid binding residues in proteins based on multilabel learning.
Zhang J; Chen Q; Liu B
Brief Bioinform; 2021 Sep; 22(5):. PubMed ID: 33454744
[TBL] [Abstract][Full Text] [Related]
2. RBscore&NBench: a high-level web server for nucleic acid binding residues prediction with a large-scale benchmarking database.
Miao Z; Westhof E
Nucleic Acids Res; 2016 Jul; 44(W1):W562-7. PubMed ID: 27084939
[TBL] [Abstract][Full Text] [Related]
3. iDRNA-ITF: identifying DNA- and RNA-binding residues in proteins based on induction and transfer framework.
Wang N; Yan K; Zhang J; Liu B
Brief Bioinform; 2022 Jul; 23(4):. PubMed ID: 35709747
[TBL] [Abstract][Full Text] [Related]
4. DRNApred, fast sequence-based method that accurately predicts and discriminates DNA- and RNA-binding residues.
Yan J; Kurgan L
Nucleic Acids Res; 2017 Jun; 45(10):e84. PubMed ID: 28132027
[TBL] [Abstract][Full Text] [Related]
5. ProNA2020 predicts protein-DNA, protein-RNA, and protein-protein binding proteins and residues from sequence.
Qiu J; Bernhofer M; Heinzinger M; Kemper S; Norambuena T; Melo F; Rost B
J Mol Biol; 2020 Mar; 432(7):2428-2443. PubMed ID: 32142788
[TBL] [Abstract][Full Text] [Related]
6. iDRBP_MMC: Identifying DNA-Binding Proteins and RNA-Binding Proteins Based on Multi-Label Learning Model and Motif-Based Convolutional Neural Network.
Zhang J; Chen Q; Liu B
J Mol Biol; 2020 Nov; 432(22):5860-5875. PubMed ID: 32920048
[TBL] [Abstract][Full Text] [Related]
7. MetaDBSite: a meta approach to improve protein DNA-binding sites prediction.
Si J; Zhang Z; Lin B; Schroeder M; Huang B
BMC Syst Biol; 2011 Jun; 5 Suppl 1(Suppl 1):S7. PubMed ID: 21689482
[TBL] [Abstract][Full Text] [Related]
8. GraphBind: protein structural context embedded rules learned by hierarchical graph neural networks for recognizing nucleic-acid-binding residues.
Xia Y; Xia CQ; Pan X; Shen HB
Nucleic Acids Res; 2021 May; 49(9):e51. PubMed ID: 33577689
[TBL] [Abstract][Full Text] [Related]
9. A MOTIF-BASED METHOD FOR PREDICTING INTERFACIAL RESIDUES IN BOTH THE RNA AND PROTEIN COMPONENTS OF PROTEIN-RNA COMPLEXES.
Muppirala U; Lewis BA; Mann CM; Dobbs D
Pac Symp Biocomput; 2016; 21():445-455. PubMed ID: 26776208
[TBL] [Abstract][Full Text] [Related]
10. Novel approach for selecting the best predictor for identifying the binding sites in DNA binding proteins.
Nagarajan R; Ahmad S; Gromiha MM
Nucleic Acids Res; 2013 Sep; 41(16):7606-14. PubMed ID: 23788679
[TBL] [Abstract][Full Text] [Related]
11. NPDock: a web server for protein-nucleic acid docking.
Tuszynska I; Magnus M; Jonak K; Dawson W; Bujnicki JM
Nucleic Acids Res; 2015 Jul; 43(W1):W425-30. PubMed ID: 25977296
[TBL] [Abstract][Full Text] [Related]
12. DeepDISOBind: accurate prediction of RNA-, DNA- and protein-binding intrinsically disordered residues with deep multi-task learning.
Zhang F; Zhao B; Shi W; Li M; Kurgan L
Brief Bioinform; 2022 Jan; 23(1):. PubMed ID: 34905768
[TBL] [Abstract][Full Text] [Related]
13. SOFB is a comprehensive ensemble deep learning approach for elucidating and characterizing protein-nucleic-acid-binding residues.
Zhang B; Hou Z; Yang Y; Wong KC; Zhu H; Li X
Commun Biol; 2024 Jun; 7(1):679. PubMed ID: 38830995
[TBL] [Abstract][Full Text] [Related]
14. Protein-RNA interface residue prediction using machine learning: an assessment of the state of the art.
Walia RR; Caragea C; Lewis BA; Towfic F; Terribilini M; El-Manzalawy Y; Dobbs D; Honavar V
BMC Bioinformatics; 2012 May; 13():89. PubMed ID: 22574904
[TBL] [Abstract][Full Text] [Related]
15. iDRPro-SC: identifying DNA-binding proteins and RNA-binding proteins based on subfunction classifiers.
Yan K; Feng J; Huang J; Wu H
Brief Bioinform; 2023 Jul; 24(4):. PubMed ID: 37405873
[TBL] [Abstract][Full Text] [Related]
16. Prediction of Disordered RNA, DNA, and Protein Binding Regions Using DisoRDPbind.
Peng Z; Wang C; Uversky VN; Kurgan L
Methods Mol Biol; 2017; 1484():187-203. PubMed ID: 27787828
[TBL] [Abstract][Full Text] [Related]
17. APIS: accurate prediction of hot spots in protein interfaces by combining protrusion index with solvent accessibility.
Xia JF; Zhao XM; Song J; Huang DS
BMC Bioinformatics; 2010 Apr; 11():174. PubMed ID: 20377884
[TBL] [Abstract][Full Text] [Related]
18. PRBP: Prediction of RNA-Binding Proteins Using a Random Forest Algorithm Combined with an RNA-Binding Residue Predictor.
Ma X; Guo J; Xiao K; Sun X
IEEE/ACM Trans Comput Biol Bioinform; 2015; 12(6):1385-93. PubMed ID: 26671809
[TBL] [Abstract][Full Text] [Related]
19. BindN+ for accurate prediction of DNA and RNA-binding residues from protein sequence features.
Wang L; Huang C; Yang MQ; Yang JY
BMC Syst Biol; 2010 May; 4 Suppl 1(Suppl 1):S3. PubMed ID: 20522253
[TBL] [Abstract][Full Text] [Related]
20. Accurate prediction of RNA-binding protein residues with two discriminative structural descriptors.
Sun M; Wang X; Zou C; He Z; Liu W; Li H
BMC Bioinformatics; 2016 Jun; 17(1):231. PubMed ID: 27266516
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]