207 related articles for article (PubMed ID: 34029314)
1. Evaluation of residue-residue contact prediction methods: From retrospective to prospective.
Zhang H; Bei Z; Xi W; Hao M; Ju Z; Saravanan KM; Zhang H; Guo N; Wei Y
PLoS Comput Biol; 2021 May; 17(5):e1009027. PubMed ID: 34029314
[TBL] [Abstract][Full Text] [Related]
2. ComplexContact: a web server for inter-protein contact prediction using deep learning.
Zeng H; Wang S; Zhou T; Zhao F; Li X; Wu Q; Xu J
Nucleic Acids Res; 2018 Jul; 46(W1):W432-W437. PubMed ID: 29790960
[TBL] [Abstract][Full Text] [Related]
3. DeepECA: an end-to-end learning framework for protein contact prediction from a multiple sequence alignment.
Fukuda H; Tomii K
BMC Bioinformatics; 2020 Jan; 21(1):10. PubMed ID: 31918654
[TBL] [Abstract][Full Text] [Related]
4. Deep-learning contact-map guided protein structure prediction in CASP13.
Zheng W; Li Y; Zhang C; Pearce R; Mortuza SM; Zhang Y
Proteins; 2019 Dec; 87(12):1149-1164. PubMed ID: 31365149
[TBL] [Abstract][Full Text] [Related]
5. A Web-Based Protocol for Interprotein Contact Prediction by Deep Learning.
Jing X; Zeng H; Wang S; Xu J
Methods Mol Biol; 2020; 2074():67-80. PubMed ID: 31583631
[TBL] [Abstract][Full Text] [Related]
6. rawMSA: End-to-end Deep Learning using raw Multiple Sequence Alignments.
Mirabello C; Wallner B
PLoS One; 2019; 14(8):e0220182. PubMed ID: 31415569
[TBL] [Abstract][Full Text] [Related]
7. Improving deep learning-based protein distance prediction in CASP14.
Guo Z; Wu T; Liu J; Hou J; Cheng J
Bioinformatics; 2021 Oct; 37(19):3190-3196. PubMed ID: 33961009
[TBL] [Abstract][Full Text] [Related]
8. Predicting protein residue-residue contacts using random forests and deep networks.
Luttrell J; Liu T; Zhang C; Wang Z
BMC Bioinformatics; 2019 Mar; 20(Suppl 2):100. PubMed ID: 30871477
[TBL] [Abstract][Full Text] [Related]
9. COMTOP: Protein Residue-Residue Contact Prediction through Mixed Integer Linear Optimization.
Reza MS; Zhang H; Hossain MT; Jin L; Feng S; Wei Y
Membranes (Basel); 2021 Jun; 11(7):. PubMed ID: 34209399
[TBL] [Abstract][Full Text] [Related]
10. Analysis of several key factors influencing deep learning-based inter-residue contact prediction.
Wu T; Hou J; Adhikari B; Cheng J
Bioinformatics; 2020 Feb; 36(4):1091-1098. PubMed ID: 31504181
[TBL] [Abstract][Full Text] [Related]
11. DNCON2_Inter: predicting interchain contacts for homodimeric and homomultimeric protein complexes using multiple sequence alignments of monomers and deep learning.
Quadir F; Roy RS; Halfmann R; Cheng J
Sci Rep; 2021 Jun; 11(1):12295. PubMed ID: 34112907
[TBL] [Abstract][Full Text] [Related]
12. Protein contact prediction by integrating deep multiple sequence alignments, coevolution and machine learning.
Adhikari B; Hou J; Cheng J
Proteins; 2018 Mar; 86 Suppl 1(Suppl 1):84-96. PubMed ID: 29047157
[TBL] [Abstract][Full Text] [Related]
13. Ensembling multiple raw coevolutionary features with deep residual neural networks for contact-map prediction in CASP13.
Li Y; Zhang C; Bell EW; Yu DJ; Zhang Y
Proteins; 2019 Dec; 87(12):1082-1091. PubMed ID: 31407406
[TBL] [Abstract][Full Text] [Related]
14. A study and benchmark of DNcon: a method for protein residue-residue contact prediction using deep networks.
Eickholt J; Cheng J
BMC Bioinformatics; 2013; 14 Suppl 14(Suppl 14):S12. PubMed ID: 24267585
[TBL] [Abstract][Full Text] [Related]
15. DeepDist: real-value inter-residue distance prediction with deep residual convolutional network.
Wu T; Guo Z; Hou J; Cheng J
BMC Bioinformatics; 2021 Jan; 22(1):30. PubMed ID: 33494711
[TBL] [Abstract][Full Text] [Related]
16. DeepCDpred: Inter-residue distance and contact prediction for improved prediction of protein structure.
Ji S; Oruç T; Mead L; Rehman MF; Thomas CM; Butterworth S; Winn PJ
PLoS One; 2019; 14(1):e0205214. PubMed ID: 30620738
[TBL] [Abstract][Full Text] [Related]
17. Assessing the accuracy of contact predictions in CASP13.
Shrestha R; Fajardo E; Gil N; Fidelis K; Kryshtafovych A; Monastyrskyy B; Fiser A
Proteins; 2019 Dec; 87(12):1058-1068. PubMed ID: 31587357
[TBL] [Abstract][Full Text] [Related]
18. Protein tertiary structure modeling driven by deep learning and contact distance prediction in CASP13.
Hou J; Wu T; Cao R; Cheng J
Proteins; 2019 Dec; 87(12):1165-1178. PubMed ID: 30985027
[TBL] [Abstract][Full Text] [Related]
19. Analyzing effect of quadruple multiple sequence alignments on deep learning based protein inter-residue distance prediction.
Jain A; Terashi G; Kagaya Y; Maddhuri Venkata Subramaniya SR; Christoffer C; Kihara D
Sci Rep; 2021 Apr; 11(1):7574. PubMed ID: 33828153
[TBL] [Abstract][Full Text] [Related]
20. Analysis of distance-based protein structure prediction by deep learning in CASP13.
Xu J; Wang S
Proteins; 2019 Dec; 87(12):1069-1081. PubMed ID: 31471916
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
