Single‐sequence‐based prediction of protein secondary structures and solvent accessibility by deep whole‐sequence learning
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Jaswinder Singh | Kuldip K. Paliwal | James G. Lyons | Rhys Heffernan | Yaoqi Zhou | Yuedong Yang | K. Paliwal | Yaoqi Zhou | Yuedong Yang | Rhys Heffernan | Jaswinder Singh
[1] Kuldip K. Paliwal,et al. Highly accurate sequence-based prediction of half-sphere exposures of amino acid residues in proteins , 2016, Bioinform..
[2] K-L Ting,et al. Combining the GOR V algorithm with evolutionary information for protein secondary structure prediction from amino acid sequence , 2002, Proteins.
[3] Kuldip K. Paliwal,et al. Sixty-five years of the long march in protein secondary structure prediction: the final stretch? , 2016, Briefings Bioinform..
[4] Kuldip K. Paliwal,et al. Capturing non‐local interactions by long short‐term memory bidirectional recurrent neural networks for improving prediction of protein secondary structure, backbone angles, contact numbers and solvent accessibility , 2017, Bioinform..
[5] James G. Lyons,et al. Improving prediction of secondary structure, local backbone angles, and solvent accessible surface area of proteins by iterative deep learning , 2015, Scientific Reports.
[6] Y. Duan,et al. Trends in template/fragment-free protein structure prediction , 2010, Theoretical chemistry accounts.
[7] Yaoqi Zhou,et al. Accurate single‐sequence prediction of solvent accessible surface area using local and global features , 2014, Proteins.
[8] Kuldip K. Paliwal,et al. Predicting backbone Cα angles and dihedrals from protein sequences by stacked sparse auto‐encoder deep neural network , 2014, J. Comput. Chem..
[9] Jürgen Schmidhuber,et al. Long Short-Term Memory , 1997, Neural Computation.
[10] Georgios A. Pavlopoulos,et al. Protein structure determination using metagenome sequence data , 2017, Science.
[11] Thomas L. Madden,et al. Gapped BLAST and PSI-BLAST: a new generation of protein database search programs. , 1997, Nucleic acids research.
[12] Gökhan BakIr,et al. Predicting Structured Data , 2008 .
[13] K. Dill,et al. The Protein-Folding Problem, 50 Years On , 2012, Science.
[14] W. Kabsch,et al. Dictionary of protein secondary structure: Pattern recognition of hydrogen‐bonded and geometrical features , 1983, Biopolymers.
[15] Jiangning Song,et al. HSEpred: predict half-sphere exposure from protein sequences , 2008, Bioinform..
[16] Jian Peng,et al. Protein Secondary Structure Prediction Using Deep Convolutional Neural Fields , 2015, Scientific Reports.
[17] Geoffrey E. Hinton,et al. Deep Learning , 2015, Nature.
[18] M. Sternberg,et al. Prediction of protein secondary structure and active sites using the alignment of homologous sequences. , 1987, Journal of molecular biology.
[19] T. Hamelryck. An amino acid has two sides: A new 2D measure provides a different view of solvent exposure , 2005, Proteins.
[20] P. Y. Chou,et al. Prediction of protein conformation. , 1974, Biochemistry.
[21] Douglas L. Brutlag,et al. Bayesian Segmentation of Protein Secondary Structure , 2000, J. Comput. Biol..
[22] S. Henikoff,et al. Amino acid substitution matrices from protein blocks. , 1992, Proceedings of the National Academy of Sciences of the United States of America.
[23] H A Scheraga,et al. Minimization of polypeptide energy. I. Preliminary structures of bovine pancreatic ribonuclease S-peptide. , 1967, Proceedings of the National Academy of Sciences of the United States of America.
[24] J. M. Levin,et al. Exploring the limits of nearest neighbour secondary structure prediction. , 1997, Protein engineering.
[25] Lukasz A. Kurgan,et al. SPINE X: Improving protein secondary structure prediction by multistep learning coupled with prediction of solvent accessible surface area and backbone torsion angles , 2012, J. Comput. Chem..
[26] Belhadri Messabih,et al. Effect of simple ensemble methods on protein secondary structure prediction , 2015, Soft Comput..
[27] A. Biegert,et al. HHblits: lightning-fast iterative protein sequence searching by HMM-HMM alignment , 2011, Nature Methods.
[28] G. G. Stokes. "J." , 1890, The New Yale Book of Quotations.
[29] Zheng Yuan,et al. Better prediction of protein contact number using a support vector regression analysis of amino acid sequence , 2005, BMC Bioinformatics.
[30] Yücel Altunbasak,et al. Protein secondary structure prediction for a single-sequence using hidden semi-Markov models , 2006, BMC Bioinformatics.
[31] Joarder Kamruzzaman,et al. Combining segmental semi-Markov models with neural networks for protein secondary structure prediction , 2009, Neurocomputing.
[32] D T Jones,et al. Protein secondary structure prediction based on position-specific scoring matrices. , 1999, Journal of molecular biology.