AIMC Topic: Protein Structure, Secondary

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Protein secondary structure prediction improved by recurrent neural networks integrated with two-dimensional convolutional neural networks.

Journal of bioinformatics and computational biology Oct 1, 2018
Protein secondary structure prediction (PSSP) is an important research field in bioinformatics. The representation of protein sequence features could be treated as a matrix, which includes the amino-acid residue (time-step) dimension and the feature ...
Neural Networks, Computer Proteins Databases, Protein Protein Structure, Secondary Deep Learning Computational Biology
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ComplexContact: a web server for inter-protein contact prediction using deep learning.

Nucleic acids research Jul 2, 2018
ComplexContact (http://raptorx2.uchicago.edu/ComplexContact/) is a web server for sequence-based interfacial residue-residue contact prediction of a putative protein complex. Interfacial residue-residue contacts are critical for understanding how pro...
Protein Interaction Domains and Motifs Escherichia coli Proteins Structural Homology, Protein Amino Acid Sequence Sequence Alignment Internet Protein Structure, Secondary Deep Learning Humans Databases, Factual Sequence Homology, Amino Acid Computational Biology Software
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Protein threading using residue co-variation and deep learning.

Bioinformatics (Oxford, England) Jul 1, 2018
MOTIVATION: Template-based modeling, including homology modeling and protein threading, is a popular method for protein 3D structure prediction. However, alignment generation and template selection for protein sequences without close templates remain...
Software Deep Learning Protein Structure, Secondary Sequence Alignment Sequence Analysis, Protein Proteins Models, Molecular
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Sixty-five years of the long march in protein secondary structure prediction: the final stretch?

Briefings in bioinformatics May 1, 2018
Protein secondary structure prediction began in 1951 when Pauling and Corey predicted helical and sheet conformations for protein polypeptide backbone even before the first protein structure was determined. Sixty-five years later, powerful new method...
Protein Structure, Secondary Proteins Databases, Protein Humans Neural Networks, Computer Computational Biology Models, Theoretical Algorithms
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SVM-dependent pairwise HMM: an application to protein pairwise alignments.

Bioinformatics (Oxford, England) Dec 15, 2017
MOTIVATION: Methods able to provide reliable protein alignments are crucial for many bioinformatics applications. In the last years many different algorithms have been developed and various kinds of information, from sequence conservation to secondar...
Sequence Alignment Sequence Analysis, Protein Markov Chains Software Protein Structure, Secondary Support Vector Machine Proteins Algorithms
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An introduction to deep learning on biological sequence data: examples and solutions.

Bioinformatics (Oxford, England) Nov 15, 2017
MOTIVATION: Deep neural network architectures such as convolutional and long short-term memory networks have become increasingly popular as machine learning tools during the recent years. The availability of greater computational resources, more data...
Neural Networks, Computer Machine Learning Sequence Analysis, Protein Computational Biology Peptides Protein Transport Protein Binding Protein Structure, Secondary
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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.

Bioinformatics (Oxford, England) Sep 15, 2017
MOTIVATION: The accuracy of predicting protein local and global structural properties such as secondary structure and solvent accessible surface area has been stagnant for many years because of the challenge of accounting for non-local interactions b...
Models, Molecular Solvents Protein Structure, Secondary Machine Learning Computational Biology Neural Networks, Computer Proteins
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Structural classification of protein sequences based on signal processing and support vector machines.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Aug 1, 2016
The function of any protein depends directly on its secondary and tertiary structure. Proteins can fold into a three-dimensional shape, which is primarily depended on the arrangement of amino acids in the primary structure. In recent years, with the ...
Protein Structure, Secondary Proteins Signal Processing, Computer-Assisted Amino Acid Sequence Computational Biology Support Vector Machine
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VH-VL orientation prediction for antibody humanization candidate selection: A case study.

mAbs Jan 1, 2016
Antibody humanization describes the procedure of grafting a non-human antibody's complementarity-determining regions, i.e., the variable loop regions that mediate specific interactions with the antigen, onto a β-sheet framework that is representative...
Protein Structure, Secondary Complementarity Determining Regions Humans Antibodies, Monoclonal, Humanized Structural Homology, Protein Machine Learning Models, Molecular
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Machine learning of single molecule free energy surfaces and the impact of chemistry and environment upon structure and dynamics.

The Journal of chemical physics Mar 14, 2015
The conformational states explored by polymers and proteins can be controlled by environmental conditions (e.g., temperature, pressure, and solvent) and molecular chemistry (e.g., molecular weight and side chain identity). We introduce an approach em...
Protein Structure, Secondary Proteins Machine Learning Alkanes Thermodynamics Computer Simulation Polyglutamic Acid
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