AI Medical Compendium Topic:
Protein Conformation

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ISPRED4: interaction sites PREDiction in protein structures with a refining grammar model.

Bioinformatics (Oxford, England)
MOTIVATION: The identification of protein-protein interaction (PPI) sites is an important step towards the characterization of protein functional integration in the cell complexity. Experimental methods are costly and time-consuming and computational...

ProQ3D: improved model quality assessments using deep learning.

Bioinformatics (Oxford, England)
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...

Sphinx: merging knowledge-based and ab initio approaches to improve protein loop prediction.

Bioinformatics (Oxford, England)
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...

From Fuzzy to Function: The New Frontier of Protein-Protein Interactions.

Accounts of chemical research
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 ...

Improving protein disorder prediction by deep bidirectional long short-term memory recurrent neural networks.

Bioinformatics (Oxford, England)
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...

QAcon: single model quality assessment using protein structural and contact information with machine learning techniques.

Bioinformatics (Oxford, England)
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...

Artificial neural networks for dihedral angles prediction in enzyme loops: a novel approach.

International journal of bioinformatics research and applications
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...

Advances in protein contact map prediction based on machine learning.

Medicinal chemistry (Shariqah (United Arab Emirates))
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 ...

Architecture and biological applications of artificial neural networks: a tuberculosis perspective.

Methods in molecular biology (Clifton, N.J.)
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...

GENN: a GEneral Neural Network for learning tabulated data with examples from protein structure prediction.

Methods in molecular biology (Clifton, N.J.)
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...