AIMC Topic: Proteins

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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...

A Hybrid Deep Learning Model for Predicting Protein Hydroxylation Sites.

International journal of molecular sciences
Protein hydroxylation is one type of post-translational modifications (PTMs) playing critical roles in human diseases. It is known that protein sequence contains many uncharacterized residues of proline and lysine. The question that needs to be answe...

Detecting Proline and Non-Proline Cis Isomers in Protein Structures from Sequences Using Deep Residual Ensemble Learning.

Journal of chemical information and modeling
It has been long established that cis conformations of amino acid residues play many biologically important roles despite their rare occurrence in protein structure. Because of this rarity, few methods have been developed for predicting cis isomers f...

Transferable Dynamic Molecular Charge Assignment Using Deep Neural Networks.

Journal of chemical theory and computation
The ability to accurately and efficiently compute quantum-mechanical partial atomistic charges has many practical applications, such as calculations of IR spectra, analysis of chemical bonding, and classical force field parametrization. Machine learn...

Uncertainty, imprecision, and many-valued logics in protein bioinformatics.

Mathematical biosciences
Understanding proteins, their structures, functions, mutual interactions, activity in cellular reactions, interactions with drugs, and expression in body cells is a key to efficient medical diagnosis, drug production, and treatment of patients. Machi...

PROSES: A Web Server for Sequence-Based Protein Encoding.

Journal of computational biology : a journal of computational molecular cell biology
Recently, the number of the amino acid sequences shared in online databases is growing rapidly in huge amounts. By using sequence-derived features, machine learning algorithms are successfully applied to prediction of protein functional classes, prot...

SVM-SulfoSite: A support vector machine based predictor for sulfenylation sites.

Scientific reports
Protein S-sulfenylation, which results from oxidation of free thiols on cysteine residues, has recently emerged as an important post-translational modification that regulates the structure and function of proteins involved in a variety of physiologic...

Automatic extraction of protein-protein interactions using grammatical relationship graph.

BMC medical informatics and decision making
BACKGROUND: Relationships between bio-entities (genes, proteins, diseases, etc.) constitute a significant part of our knowledge. Most of this information is documented as unstructured text in different forms, such as books, articles and on-line pages...

De novo profile generation based on sequence context specificity with the long short-term memory network.

BMC bioinformatics
BACKGROUND: Long short-term memory (LSTM) is one of the most attractive deep learning methods to learn time series or contexts of input data. Increasing studies, including biological sequence analyses in bioinformatics, utilize this architecture. Ami...

Protein Secondary Structure Prediction Based on Data Partition and Semi-Random Subspace Method.

Scientific reports
Protein secondary structure prediction is one of the most important and challenging problems in bioinformatics. Machine learning techniques have been applied to solve the problem and have gained substantial success in this research area. However ther...