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Databases, Protein

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TopScore: Using Deep Neural Networks and Large Diverse Data Sets for Accurate Protein Model Quality Assessment.

Journal of chemical theory and computation
The value of protein models obtained with automated protein structure prediction depends primarily on their accuracy. Protein model quality assessment is thus critical to select the model that can best answer biologically relevant questions from an e...

Protein function prediction from protein-protein interaction network using gene ontology based neighborhood analysis and physico-chemical features.

Journal of bioinformatics and computational biology
Protein Function Prediction from Protein-Protein Interaction Network (PPIN) and physico-chemical features using the Gene Ontology (GO) classification are indeed very useful for assigning biological or biochemical functions to a protein. They also lea...

Predicting apoptosis protein subcellular localization by integrating auto-cross correlation and PSSM into Chou's PseAAC.

Journal of theoretical biology
The prediction of subcellular localization of an apoptosis protein is still a challenging task, and existing methods mainly based on protein primary sequences. In this study, we propose a novel model called MACC-PSSM by integrating Moran autocorrelat...

BlaPred: Predicting and classifying β-lactamase using a 3-tier prediction system via Chou's general PseAAC.

Journal of theoretical biology
Antibiotics of β-lactam class account for nearly half of the global antibiotic use. The β-lactamase enzyme is a major element of the bacterial arsenals to escape the lethal effect of β-lactam antibiotics. Different variants of β-lactamases have evolv...

Exploiting MEDLINE for gene molecular function prediction via NMF based multi-label classification.

Journal of biomedical informatics
Gene ontology (GO) provides a representation of terms and categories used to describe genes and their molecular functions, cellular components and biological processes. GO has been the standard for describing the functions of specific genes in differ...

Mathematical deep learning for pose and binding affinity prediction and ranking in D3R Grand Challenges.

Journal of computer-aided molecular design
Advanced mathematics, such as multiscale weighted colored subgraph and element specific persistent homology, and machine learning including deep neural networks were integrated to construct mathematical deep learning models for pose and binding affin...

A New Method for Recognizing Cytokines Based on Feature Combination and a Support Vector Machine Classifier.

Molecules (Basel, Switzerland)
Research on cytokine recognition is of great significance in the medical field due to the fact cytokines benefit the diagnosis and treatment of diseases, but the current methods for cytokine recognition have many shortcomings, such as low sensitivity...

Identifying Phage Virion Proteins by Using Two-Step Feature Selection Methods.

Molecules (Basel, Switzerland)
Accurate identification of phage virion protein is not only a key step for understanding the function of the phage virion protein but also helpful for further understanding the lysis mechanism of the bacterial cell. Since traditional experimental met...

Prediction of 8-state protein secondary structures by a novel deep learning architecture.

BMC bioinformatics
BACKGROUND: Protein secondary structure can be regarded as an information bridge that links the primary sequence and tertiary structure. Accurate 8-state secondary structure prediction can significantly give more precise and high resolution on struct...

Predicting membrane protein types by incorporating a novel feature set into Chou's general PseAAC.

Journal of theoretical biology
Membrane proteins are vital type of proteins that serve as channels, receptors and energy transducers in a cell. They perform various important functions, which are mainly associated with their types. They are also attractive targets of drug discover...