标题
Distance-based protein folding powered by deep learning
作者
关键词
-
出版物
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
Volume 116, Issue 34, Pages 16856-16865
出版商
Proceedings of the National Academy of Sciences
发表日期
2019-08-10
DOI
10.1073/pnas.1821309116
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。- End-to-End Differentiable Learning of Protein Structure
- (2019) Mohammed AlQuraishi Cell Systems
- High precision in protein contact prediction using fully convolutional neural networks and minimal sequence features
- (2018) David T Jones et al. BIOINFORMATICS
- Protein threading using residue co-variation and deep learning
- (2018) Jianwei Zhu et al. BIOINFORMATICS
- RaptorX-Angle: real-value prediction of protein backbone dihedral angles through a hybrid method of clustering and deep learning
- (2018) Yujuan Gao et al. BMC BIOINFORMATICS
- ComplexContact: a web server for inter-protein contact prediction using deep learning
- (2018) Hong Zeng et al. NUCLEIC ACIDS RESEARCH
- Enhancing Evolutionary Couplings with Deep Convolutional Neural Networks
- (2018) Yang Liu et al. Cell Systems
- Template-based and free modeling of I-TASSER and QUARK pipelines using predicted contact maps in CASP12
- (2017) Chengxin Zhang et al. PROTEINS-STRUCTURE FUNCTION AND BIOINFORMATICS
- Analysis of deep learning methods for blind protein contact prediction in CASP12
- (2017) Sheng Wang et al. PROTEINS-STRUCTURE FUNCTION AND BIOINFORMATICS
- Protein structure prediction using Rosetta in CASP12
- (2017) Sergey Ovchinnikov et al. PROTEINS-STRUCTURE FUNCTION AND BIOINFORMATICS
- Assessment of contact predictions in CASP12: Co-evolution and deep learning coming of age
- (2017) Joerg Schaarschmidt 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
- Folding Membrane Proteins by Deep Transfer Learning
- (2017) Sheng Wang et al. Cell Systems
- Uniclust databases of clustered and deeply annotated protein sequences and alignments
- (2016) Milot Mirdita et al. NUCLEIC ACIDS RESEARCH
- Protein Secondary Structure Prediction Using Deep Convolutional Neural Fields
- (2016) Sheng Wang et al. Scientific Reports
- GDFuzz3D: a method for protein 3D structure reconstruction from contact maps, based on a non-Euclidean distance function
- (2015) Michal J. Pietal et al. BIOINFORMATICS
- Protein contact prediction by integrating joint evolutionary coupling analysis and supervised learning
- (2015) Jianzhu Ma et al. BIOINFORMATICS
- CONFOLD: Residue-residue contact-guidedab initioprotein folding
- (2015) Badri Adhikari et al. PROTEINS-STRUCTURE FUNCTION AND BIOINFORMATICS
- CCMpred—fast and precise prediction of protein residue–residue contacts from correlated mutations
- (2014) Stefan Seemayer et al. BIOINFORMATICS
- MetaPSICOV: combining coevolution methods for accurate prediction of contacts and long range hydrogen bonding in proteins
- (2014) David T. Jones et al. BIOINFORMATICS
- UniRef clusters: a comprehensive and scalable alternative for improving sequence similarity searches
- (2014) B. E. Suzek et al. BIOINFORMATICS
- Toward an accurate prediction of inter-residue distances in proteins using 2D recursive neural networks
- (2014) Predrag Kukic et al. BMC BIOINFORMATICS
- Fast and Accurate Multivariate Gaussian Modeling of Protein Families: Predicting Residue Contacts and Protein-Interaction Partners
- (2014) Carlo Baldassi et al. PLoS One
- Emerging methods in protein co-evolution
- (2013) David de Juan et al. NATURE REVIEWS GENETICS
- 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
- High-Resolution Comparative Modeling with RosettaCM
- (2013) Yifan Song et al. STRUCTURE
- Protein structure alignment beyond spatial proximity
- (2013) Sheng Wang et al. Scientific Reports
- A conditional neural fields model for protein threading
- (2012) Jianzhu Ma et al. BIOINFORMATICS
- Deep architectures for protein contact map prediction
- (2012) Pietro Di Lena et al. BIOINFORMATICS
- Predicting protein residue–residue contacts using deep networks and boosting
- (2012) Jesse Eickholt et al. BIOINFORMATICS
- Protein structure prediction from sequence variation
- (2012) Debora S Marks et al. NATURE BIOTECHNOLOGY
- A Position-Specific Distance-Dependent Statistical Potential for Protein Structure and Functional Study
- (2012) Feng Zhao et al. STRUCTURE
- PSICOV: precise structural contact prediction using sparse inverse covariance estimation on large multiple sequence alignments
- (2011) David T. Jones et al. BIOINFORMATICS
- HHblits: lightning-fast iterative protein sequence searching by HMM-HMM alignment
- (2011) Michael Remmert et al. NATURE METHODS
- Protein 3D Structure Computed from Evolutionary Sequence Variation
- (2011) Debora S. Marks et al. PLoS One
- Direct-coupling analysis of residue coevolution captures native contacts across many protein families
- (2011) F. Morcos et al. PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
- I-TASSER: a unified platform for automated protein structure and function prediction
- (2010) Ambrish Roy et al. Nature Protocols
- Identification of direct residue contacts in protein-protein interaction by message passing
- (2008) M. Weigt et al. PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
Find Funding. Review Successful Grants.
Explore over 25,000 new funding opportunities and over 6,000,000 successful grants.
ExploreFind the ideal target journal for your manuscript
Explore over 38,000 international journals covering a vast array of academic fields.
Search