Search details
1.
De novo design of luciferases using deep learning.
Nature
; 614(7949): 774-780, 2023 02.
Article
in English
| MEDLINE | ID: mdl-36813896
2.
Accurate prediction of protein-nucleic acid complexes using RoseTTAFoldNA.
Nat Methods
; 21(1): 117-121, 2024 Jan.
Article
in English
| MEDLINE | ID: mdl-37996753
3.
De novo protein design by deep network hallucination.
Nature
; 600(7889): 547-552, 2021 12.
Article
in English
| MEDLINE | ID: mdl-34853475
4.
Characterizing and explaining the impact of disease-associated mutations in proteins without known structures or structural homologs.
Brief Bioinform
; 23(4)2022 07 18.
Article
in English
| MEDLINE | ID: mdl-35641150
5.
Protein sequence design by conformational landscape optimization.
Proc Natl Acad Sci U S A
; 118(11)2021 03 16.
Article
in English
| MEDLINE | ID: mdl-33712545
6.
Improved protein structure prediction using predicted interresidue orientations.
Proc Natl Acad Sci U S A
; 117(3): 1496-1503, 2020 01 21.
Article
in English
| MEDLINE | ID: mdl-31896580
7.
Structural basis for autophagy inhibition by the human Rubicon-Rab7 complex.
Proc Natl Acad Sci U S A
; 117(29): 17003-17010, 2020 07 21.
Article
in English
| MEDLINE | ID: mdl-32632011
8.
Protein oligomer modeling guided by predicted interchain contacts in CASP14.
Proteins
; 89(12): 1824-1833, 2021 12.
Article
in English
| MEDLINE | ID: mdl-34324224
9.
Protein tertiary structure prediction and refinement using deep learning and Rosetta in CASP14.
Proteins
; 89(12): 1722-1733, 2021 12.
Article
in English
| MEDLINE | ID: mdl-34331359
10.
Protein contact prediction using metagenome sequence data and residual neural networks.
Bioinformatics
; 36(1): 41-48, 2020 01 01.
Article
in English
| MEDLINE | ID: mdl-31173061
11.
Origins of coevolution between residues distant in protein 3D structures.
Proc Natl Acad Sci U S A
; 114(34): 9122-9127, 2017 08 22.
Article
in English
| MEDLINE | ID: mdl-28784799
12.
High-accuracy refinement using Rosetta in CASP13.
Proteins
; 87(12): 1276-1282, 2019 12.
Article
in English
| MEDLINE | ID: mdl-31325340
13.
Gene ontology improves template selection in comparative protein docking.
Proteins
; 87(3): 245-253, 2019 03.
Article
in English
| MEDLINE | ID: mdl-30520123
14.
Template-based modeling by ClusPro in CASP13 and the potential for using co-evolutionary information in docking.
Proteins
; 87(12): 1241-1248, 2019 12.
Article
in English
| MEDLINE | ID: mdl-31444975
15.
Contact Potential for Structure Prediction of Proteins and Protein Complexes from Potts Model.
Biophys J
; 115(5): 809-821, 2018 09 04.
Article
in English
| MEDLINE | ID: mdl-30122295
16.
Modeling CAPRI targets 110-120 by template-based and free docking using contact potential and combined scoring function.
Proteins
; 86 Suppl 1: 302-310, 2018 03.
Article
in English
| MEDLINE | ID: mdl-28905425
17.
Modeling complexes of modeled proteins.
Proteins
; 85(3): 470-478, 2017 03.
Article
in English
| MEDLINE | ID: mdl-27701777
18.
Structural quality of unrefined models in protein docking.
Proteins
; 85(1): 39-45, 2017 01.
Article
in English
| MEDLINE | ID: mdl-27756103
19.
Structural templates for comparative protein docking.
Proteins
; 83(9): 1563-70, 2015 Sep.
Article
in English
| MEDLINE | ID: mdl-25488330
20.
Protein models docking benchmark 2.
Proteins
; 83(5): 891-7, 2015 May.
Article
in English
| MEDLINE | ID: mdl-25712716