Highly accurate and high-resolution function prediction of RNA binding proteins by fold recognition and binding affinity prediction
出版年份 2011 全文链接
标题
Highly accurate and high-resolution function prediction of RNA binding proteins by fold recognition and binding affinity prediction
作者
关键词
-
出版物
RNA Biology
Volume 8, Issue 6, Pages 988-996
出版商
Informa UK Limited
发表日期
2011-12-04
DOI
10.4161/rna.8.6.17813
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。- Improving protein fold recognition and template-based modeling by employing probabilistic-based matching between predicted one-dimensional structural properties of query and corresponding native properties of templates
- (2011) Y. Yang et al. BIOINFORMATICS
- Prediction of protein–RNA binding sites by a random forest method with combined features
- (2010) Zhi-Ping Liu et al. BIOINFORMATICS
- Structure-based prediction of DNA-binding proteins by structural alignment and a volume-fraction corrected DFIRE-based energy function
- (2010) H. Zhao et al. BIOINFORMATICS
- SVM based prediction of RNA-binding proteins using binding residues and evolutionary information
- (2010) Manish Kumar et al. JOURNAL OF MOLECULAR RECOGNITION
- Structure-based prediction of RNA-binding domains and RNA-binding sites and application to structural genomics targets
- (2010) H. Zhao et al. NUCLEIC ACIDS RESEARCH
- Proteome-Wide Search Reveals Unexpected RNA-Binding Proteins in Saccharomyces cerevisiae
- (2010) Nikoleta G. Tsvetanova et al. PLoS One
- A Screen for RNA-Binding Proteins in Yeast Indicates Dual Functions for Many Enzymes
- (2010) Tanja Scherrer et al. PLoS One
- Improve the Prediction of RNA-Binding Residues Using Structural Neighbours
- (2010) Quan Li et al. PROTEIN AND PEPTIDE LETTERS
- Protein function annotation from sequence: prediction of residues interacting with RNA
- (2009) R. V. Spriggs et al. BIOINFORMATICS
- Exploiting structural and topological information to improve prediction of RNA-protein binding sites
- (2009) Stefan R Maetschke et al. BMC BIOINFORMATICS
- Predicting DNA- and RNA-binding proteins from sequences with kernel methods
- (2009) Xiaojian Shao et al. JOURNAL OF THEORETICAL BIOLOGY
- Optimal protein-RNA area, OPRA: A propensity-based method to identify RNA-binding sites on proteins
- (2009) Laura Pérez-Cano et al. PROTEINS-STRUCTURE FUNCTION AND BIOINFORMATICS
- Fast and accurate automatic structure prediction with HHpred
- (2009) Andrea Hildebrand et al. PROTEINS-STRUCTURE FUNCTION AND BIOINFORMATICS
- Predicting Continuous Local Structure and the Effect of Its Substitution for Secondary Structure in Fragment-Free Protein Structure Prediction
- (2009) Eshel Faraggi et al. STRUCTURE
- A Threading-Based Method for the Prediction of DNA-Binding Proteins with Application to the Human Genome
- (2009) Mu Gao et al. PLoS Computational Biology
- PRINTR: Prediction of RNA binding sites in proteins using SVM and profiles
- (2008) Y. Wang et al. AMINO ACIDS
- Predicting RNA-binding sites of proteins using support vector machines and evolutionary information
- (2008) Cheng-Wei Cheng et al. BMC BIOINFORMATICS
- RISP: A web-based server for prediction of RNA-binding sites in proteins
- (2008) Jing Tong et al. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE
- Predicting RNA-binding sites from the protein structure based on electrostatics, evolution and geometry
- (2008) Yao Chi Chen et al. NUCLEIC ACIDS RESEARCH
- RNA-binding proteins in human genetic disease
- (2008) Kiven E. Lukong et al. TRENDS IN GENETICS
- Classifying RNA-Binding Proteins Based on Electrostatic Properties
- (2008) Shula Shazman et al. PLoS Computational Biology
- Prediction of RNA binding sites in a protein using SVM and PSSM profile
- (2007) Manish Kumar et al. PROTEINS-STRUCTURE FUNCTION AND 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
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