标题
Improved protein structure prediction using predicted interresidue orientations
作者
关键词
-
出版物
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
Volume 117, Issue 3, Pages 1496-1503
出版商
Proceedings of the National Academy of Sciences
发表日期
2020-01-03
DOI
10.1073/pnas.1914677117
参考文献
相关参考文献
注意:仅列出部分参考文献,下载原文获取全部文献信息。- De novo design of potent and selective mimics of IL-2 and IL-15
- (2019) Daniel-Adriano Silva et al. NATURE
- ResPRE: high-accuracy protein contact prediction by coupling precision matrix with deep residual neural networks
- (2019) Yang Li et al. BIOINFORMATICS
- Protein tertiary structure modeling driven by deep learning and contact distance prediction in CASP13
- (2019) Jie Hou et al. PROTEINS-STRUCTURE FUNCTION AND BIOINFORMATICS
- Protein contact prediction using metagenome sequence data and residual neural networks
- (2019) Qi Wu et al. BIOINFORMATICS
- De novo protein design by citizen scientists
- (2019) Brian Koepnick et al. NATURE
- A further leap of improvement in tertiary structure prediction in CASP13 prompts new routes for future assessments
- (2019) Luciano A. Abriata et al. PROTEINS-STRUCTURE FUNCTION AND BIOINFORMATICS
- Deep‐learning contact‐map guided protein structure prediction in CASP13
- (2019) Wei Zheng et al. PROTEINS-STRUCTURE FUNCTION AND BIOINFORMATICS
- Evaluation of model refinement in CASP13
- (2019) Randy J. Read et al. PROTEINS-STRUCTURE FUNCTION AND BIOINFORMATICS
- Prediction of interresidue contacts with DeepMetaPSICOV in CASP13
- (2019) Shaun M. Kandathil et al. PROTEINS-STRUCTURE FUNCTION AND BIOINFORMATICS
- Driven to Near‐Experimental Accuracy by Refinement via Molecular Dynamics Simulations
- (2019) Lim Heo et al. PROTEINS-STRUCTURE FUNCTION AND BIOINFORMATICS
- Distance-based protein folding powered by deep learning
- (2019) Jinbo Xu PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
- High‐accuracy refinement using Rosetta in CASP13
- (2019) Hahnbeom Park et al. PROTEINS-STRUCTURE FUNCTION AND BIOINFORMATICS
- HMMER web server: 2018 update
- (2018) Simon C Potter et al. NUCLEIC ACIDS RESEARCH
- De novo design of a fluorescence-activating β-barrel
- (2018) Jiayi Dou et al. NATURE
- Continuous Automated Model EvaluatiOn (CAMEO) complementing the critical assessment of structure prediction in CASP12
- (2017) Jürgen Haas et al. PROTEINS-STRUCTURE FUNCTION AND BIOINFORMATICS
- Protein structure determination using metagenome sequence data
- (2017) Sergey Ovchinnikov et al. SCIENCE
- Accurate De Novo Prediction of Protein Contact Map by Ultra-Deep Learning Model
- (2017) Sheng Wang et al. PLoS Computational Biology
- Assessing the utility of coevolution-based residue-residue contact predictions in a sequence- and structure-rich era
- (2013) H. Kamisetty et al. PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
- Principles for designing ideal protein structures
- (2012) Nobuyasu Koga et al. NATURE
- HHblits: lightning-fast iterative protein sequence searching by HMM-HMM alignment
- (2011) Michael Remmert et al. NATURE METHODS
- PyRosetta: a script-based interface for implementing molecular modeling algorithms using Rosetta
- (2010) S. Chaudhury et al. BIOINFORMATICS
- Distance-scaled, finite ideal-gas reference state improves structure-derived potentials of mean force for structure selection and stability prediction
- (2002) Hongyi Zhou et al. PROTEIN SCIENCE
Publish scientific posters with Peeref
Peeref publishes scientific posters from all research disciplines. Our Diamond Open Access policy means free access to content and no publication fees for authors.
Learn MoreCreate your own webinar
Interested in hosting your own webinar? Check the schedule and propose your idea to the Peeref Content Team.
Create Now