GraphBind: protein structural context embedded rules learned by hierarchical graph neural networks for recognizing nucleic-acid-binding residues
出版年份 2021 全文链接
标题
GraphBind: protein structural context embedded rules learned by hierarchical graph neural networks for recognizing nucleic-acid-binding residues
作者
关键词
-
出版物
NUCLEIC ACIDS RESEARCH
Volume -, Issue -, Pages -
出版商
Oxford University Press (OUP)
发表日期
2021-02-11
DOI
10.1093/nar/gkab044
参考文献
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注意:仅列出部分参考文献,下载原文获取全部文献信息。- Protein-ligand binding residue prediction enhancement through hybrid deep heterogeneous learning of sequence and structure data
- (2020) Chun-Qiu Xia et al. BIOINFORMATICS
- A Comprehensive Survey on Graph Neural Networks
- (2020) Zonghan Wu et al. IEEE Transactions on Neural Networks and Learning Systems
- DNAPred: Accurate Identification of DNA-Binding Sites from Protein Sequence by Ensembled Hyperplane-Distance-Based Support Vector Machines
- (2019) Yi-Heng Zhu et al. Journal of Chemical Information and Modeling
- SCRIBER: accurate and partner type-specific prediction of protein-binding residues from proteins sequences
- (2019) Jian Zhang et al. BIOINFORMATICS
- Graph Convolutional Neural Networks for Predicting Drug-Target Interactions
- (2019) Wen Torng et al. Journal of Chemical Information and Modeling
- A deep learning framework to predict binding preference of RNA constituents on protein surface
- (2019) Jordy Homing Lam et al. Nature Communications
- Deciphering interaction fingerprints from protein molecular surfaces using geometric deep learning
- (2019) P. Gainza et al. NATURE METHODS
- Modeling polypharmacy side effects with graph convolutional networks
- (2018) Marinka Zitnik et al. BIOINFORMATICS
- ATPbind: Accurate Protein–ATP Binding Site Prediction by Combining Sequence-Profiling and Structure-Based Comparisons
- (2018) Jun Hu et al. Journal of Chemical Information and Modeling
- COACH-D: improved protein–ligand binding sites prediction with refined ligand-binding poses through molecular docking
- (2018) Qi Wu et al. NUCLEIC ACIDS RESEARCH
- High Precision Protein Functional Site Detection Using 3D Convolutional Neural Networks
- (2018) Wen Torng et al. BIOINFORMATICS
- Improving the prediction of protein–nucleic acids binding residues via multiple sequence profiles and the consensus of complementary methods
- (2018) Hong Su et al. BIOINFORMATICS
- P2Rank: machine learning based tool for rapid and accurate prediction of ligand binding sites from protein structure
- (2018) Radoslav Krivák et al. Journal of Cheminformatics
- Predicting Protein-DNA Binding Residues by Weightedly Combining Sequence-Based Features and Boosting Multiple SVMs
- (2017) Jun Hu et al. IEEE-ACM Transactions on Computational Biology and Bioinformatics
- Recognizing metal and acid radical ion-binding sites by integratingab initiomodeling with template-based transferals
- (2016) Xiuzhen Hu et al. BIOINFORMATICS
- A comprehensive comparative review of sequence-based predictors of DNA- and RNA-binding residues
- (2015) Jing Yan et al. BRIEFINGS IN BIOINFORMATICS
- Quantifying sequence and structural features of protein–RNA interactions
- (2014) Songling Li et al. NUCLEIC ACIDS RESEARCH
- A series of PDB-related databanks for everyday needs
- (2014) Wouter G. Touw et al. NUCLEIC ACIDS RESEARCH
- RNABindRPlus: A Predictor that Combines Machine Learning and Sequence Homology-Based Methods to Improve the Reliability of Predicted RNA-Binding Residues in Proteins
- (2014) Rasna R. Walia et al. PLoS One
- Protein–ligand binding site recognition using complementary binding-specific substructure comparison and sequence profile alignment
- (2013) Jianyi Yang et al. BIOINFORMATICS
- Designing Template-Free Predictor for Targeting Protein-Ligand Binding Sites with Classifier Ensemble and Spatial Clustering
- (2013) Dong-Jun Yu et al. IEEE-ACM Transactions on Computational Biology and Bioinformatics
- Identifying RNA-binding residues based on evolutionary conserved structural and energetic features
- (2013) Yao Chi Chen et al. NUCLEIC ACIDS RESEARCH
- DNABind: A hybrid algorithm for structure-based prediction of DNA-binding residues by combining machine learning- and template-based approaches
- (2013) Rong Liu et al. PROTEINS-STRUCTURE FUNCTION AND BIOINFORMATICS
- 3D Convolutional Neural Networks for Human Action Recognition
- (2012) Shuiwang Ji et al. IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
- BioLiP: a semi-manually curated database for biologically relevant ligand–protein interactions
- (2012) Jianyi Yang et al. NUCLEIC ACIDS RESEARCH
- HHblits: lightning-fast iterative protein sequence searching by HMM-HMM alignment
- (2011) Michael Remmert et al. NATURE METHODS
- A Critical Comparative Assessment of Predictions of Protein-Binding Sites for Biologically Relevant Organic Compounds
- (2011) Ke Chen et al. STRUCTURE
- CD-HIT Suite: a web server for clustering and comparing biological sequences
- (2010) Ying Huang et al. BIOINFORMATICS
- BindN+ for accurate prediction of DNA and RNA-binding residues from protein sequence features
- (2010) Liangjiang Wang et al. BMC Systems Biology
- Genomic repertoires of DNA-binding transcription factors across the tree of life
- (2010) Varodom Charoensawan et al. NUCLEIC ACIDS RESEARCH
- I-TASSER server for protein 3D structure prediction
- (2008) Yang Zhang BMC BIOINFORMATICS
- Stepwise chromatin remodelling by a cascade of transcription initiation of non-coding RNAs
- (2008) Kouji Hirota et al. NATURE
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