AI Medical Compendium Topic:
Amino Acid Sequence

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Recent Advances in Machine Learning Methods for Predicting Heat Shock Proteins.

Current drug metabolism
BACKGROUND: As molecular chaperones, Heat Shock Proteins (HSPs) not only play key roles in protein folding and maintaining protein stabilities, but are also linked with multiple kinds of diseases. Therefore, HSPs have been regarded as the focus of dr...

Accurate prediction of protein contact maps by coupling residual two-dimensional bidirectional long short-term memory with convolutional neural networks.

Bioinformatics (Oxford, England)
MOTIVATION: Accurate prediction of a protein contact map depends greatly on capturing as much contextual information as possible from surrounding residues for a target residue pair. Recently, ultra-deep residual convolutional networks were found to b...

High precision in protein contact prediction using fully convolutional neural networks and minimal sequence features.

Bioinformatics (Oxford, England)
MOTIVATION: In addition to substitution frequency data from protein sequence alignments, many state-of-the-art methods for contact prediction rely on additional sources of information, or features, of protein sequences in order to predict residue-res...

Learned protein embeddings for machine learning.

Bioinformatics (Oxford, England)
MOTIVATION: Machine-learning models trained on protein sequences and their measured functions can infer biological properties of unseen sequences without requiring an understanding of the underlying physical or biological mechanisms. Such models enab...

DeepSol: a deep learning framework for sequence-based protein solubility prediction.

Bioinformatics (Oxford, England)
MOTIVATION: Protein solubility plays a vital role in pharmaceutical research and production yield. For a given protein, the extent of its solubility can represent the quality of its function, and is ultimately defined by its sequence. Thus, it is imp...

ComplexContact: a web server for inter-protein contact prediction using deep learning.

Nucleic acids research
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...

Complex Network Study of the Immune Epitope Database for Parasitic Organisms.

Current topics in medicinal chemistry
BACKGROUND: Complex network approach allows the representation and analysis of complex systems of interacting agents in an ordered and effective manner, thus increasing the probability of discovering significant properties of them. In the present stu...

Prediction of Nitrated Tyrosine Residues in Protein Sequences by Extreme Learning Machine and Feature Selection Methods.

Combinatorial chemistry & high throughput screening
BACKGROUND: Accurately recognizing nitrated tyrosine residues from protein sequences would pave a way for understanding the mechanism of nitration and the screening of the tyrosine residues in sequences.

Prediction of Human Drug Targets and Their Interactions Using Machine Learning Methods: Current and Future Perspectives.

Methods in molecular biology (Clifton, N.J.)
Identification of drug targets and drug target interactions are important steps in the drug-discovery pipeline. Successful computational prediction methods can reduce the cost and time demanded by the experimental methods. Knowledge of putative drug ...