AIMC Topic: Protein Conformation

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ProQ3D: improved model quality assessments using deep learning.

Bioinformatics (Oxford, England) May 15, 2017
SUMMARY: Protein quality assessment is a long-standing problem in bioinformatics. For more than a decade we have developed state-of-art predictors by carefully selecting and optimising inputs to a machine learning method. The correlation has increase...
Neural Networks, Computer Support Vector Machine Software Models, Molecular Computational Biology Protein Conformation
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Sphinx: merging knowledge-based and ab initio approaches to improve protein loop prediction.

Bioinformatics (Oxford, England) May 1, 2017
MOTIVATION: Loops are often vital for protein function, however, their irregular structures make them difficult to model accurately. Current loop modelling algorithms can mostly be divided into two categories: knowledge-based, where databases of frag...
Knowledge Bases Protein Conformation Models, Molecular Software Antibodies Animals Computational Biology Algorithms
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From Fuzzy to Function: The New Frontier of Protein-Protein Interactions.

Accounts of chemical research Mar 21, 2017
Conformationally heterogenous or "fuzzy" proteins have often been described as lacking specificity in binding and in function. The activation domains, for example, of transcriptional activators were labeled as negative noodles, with little structure ...
Protein Interaction Maps Fuzzy Logic Proteins Structure-Activity Relationship Protein Conformation
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Improving protein disorder prediction by deep bidirectional long short-term memory recurrent neural networks.

Bioinformatics (Oxford, England) Mar 1, 2017
MOTIVATION: Capturing long-range interactions between structural but not sequence neighbors of proteins is a long-standing challenging problem in bioinformatics. Recently, long short-term memory (LSTM) networks have significantly improved the accurac...
Neural Networks, Computer Machine Learning Algorithms Genetic Diseases, Inborn Caspases Computational Biology Protein Conformation Proteins
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QAcon: single model quality assessment using protein structural and contact information with machine learning techniques.

Bioinformatics (Oxford, England) Feb 15, 2017
MOTIVATION: Protein model quality assessment (QA) plays a very important role in protein structure prediction. It can be divided into two groups of methods: single model and consensus QA method. The consensus QA methods may fail when there is a large...
Quality Control Protein Conformation Humans Machine Learning Proteins Models, Molecular Animals
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Artificial neural networks for dihedral angles prediction in enzyme loops: a novel approach.

International journal of bioinformatics research and applications Jan 1, 2015
Structure prediction of proteins is considered a limiting step and determining factor in drug development and in the introduction of new therapies. Since the 3D structures of proteins determine their functionalities, prediction of dihedral angles rem...
Enzymes Sequence Analysis, Protein Amino Acid Sequence Neural Networks, Computer Models, Molecular Molecular Sequence Data Computer Simulation Protein Conformation Pattern Recognition, Automated Protein Structure, Tertiary Models, Chemical
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Advances in protein contact map prediction based on machine learning.

Medicinal chemistry (Shariqah (United Arab Emirates)) Jan 1, 2015
A protein contact map is a simplified, two-dimensional version of the three-dimensional protein structure. Protein contact map is proved to be crucial in forming the three-dimensional structure. Contact map prediction has now become an indispensable ...
Neural Networks, Computer Protein Conformation Machine Learning Algorithms Computational Biology Proteins
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Architecture and biological applications of artificial neural networks: a tuberculosis perspective.

Methods in molecular biology (Clifton, N.J.) Jan 1, 2015
Advancement of science and technology has prompted researchers to develop new intelligent systems that can solve a variety of problems such as pattern recognition, prediction, and optimization. The ability of the human brain to learn in a fashion tha...
Proteins Models, Biological Protein Conformation Nerve Net Tuberculosis Image Processing, Computer-Assisted Computational Biology Algorithms Drug Discovery Humans Neural Networks, Computer
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GENN: a GEneral Neural Network for learning tabulated data with examples from protein structure prediction.

Methods in molecular biology (Clifton, N.J.) Jan 1, 2015
We present a GEneral Neural Network (GENN) for learning trends from existing data and making predictions of unknown information. The main novelty of GENN is in its generality, simplicity of use, and its specific handling of windowed input/output. Its...
Protein Conformation Computational Biology Neural Networks, Computer Proteins Software Models, Molecular
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Protein structural information derived from NMR chemical shift with the neural network program TALOS-N.

Methods in molecular biology (Clifton, N.J.) Jan 1, 2015
Chemical shifts are obtained at the first stage of any protein structural study by NMR spectroscopy. Chemical shifts are known to be impacted by a wide range of structural factors, and the artificial neural network based TALOS-N program has been trai...
Nuclear Magnetic Resonance, Biomolecular Carbon Isotopes Models, Molecular Protein Conformation Neural Networks, Computer Proteomics Proteins Software
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