AIMC Topic: Evolution, Molecular

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Term Matrix: a novel Gene Ontology annotation quality control system based on ontology term co-annotation patterns.

Open biology
Biological processes are accomplished by the coordinated action of gene products. Gene products often participate in multiple processes, and can therefore be annotated to multiple Gene Ontology (GO) terms. Nevertheless, processes that are functionall...

A novel fusion based on the evolutionary features for protein fold recognition using support vector machines.

Scientific reports
Protein fold recognition plays a crucial role in discovering three-dimensional structure of proteins and protein functions. Several approaches have been employed for the prediction of protein folds. Some of these approaches are based on extracting fe...

Genes, the brain, and artificial intelligence in evolution.

Journal of human genetics
Three important systems, genes, the brain, and artificial intelligence (especially deep learning) have similar goals, namely, the maximization of likelihood or minimization of cross-entropy. Animal brains have evolved through predator-prey interactio...

Use Chou's 5-Step Rule to Predict DNA-Binding Proteins with Evolutionary Information.

BioMed research international
The knowledge of DNA-binding proteins would help to understand the functions of proteins better in cellular biological processes. Research on the prediction of DNA-binding proteins can promote the research of drug proteins and computer acidified drug...

Predicting the short-term success of human influenza virus variants with machine learning.

Proceedings. Biological sciences
Seasonal influenza viruses are constantly changing and produce a different set of circulating strains each season. Small genetic changes can accumulate over time and result in antigenically different viruses; this may prevent the body's immune system...

SPOT-Disorder2: Improved Protein Intrinsic Disorder Prediction by Ensembled Deep Learning.

Genomics, proteomics & bioinformatics
Intrinsically disordered or unstructured proteins (or regions in proteins) have been found to be important in a wide range of biological functions and implicated in many diseases. Due to the high cost and low efficiency of experimental determination ...

Using Weighted Extreme Learning Machine Combined With Scale-Invariant Feature Transform to Predict Protein-Protein Interactions From Protein Evolutionary Information.

IEEE/ACM transactions on computational biology and bioinformatics
Protein-Protein Interactions (PPIs) play an irreplaceable role in biological activities of organisms. Although many high-throughput methods are used to identify PPIs from different kinds of organisms, they have some shortcomings, such as high cost an...

Prediction of essential genes in prokaryote based on artificial neural network.

Genes & genomics
BACKGROUND: Rapid identification of new essential genes is necessary to understand biological mechanisms and identify potential targets for antimicrobial drugs. Many computational methods have been proposed.

PolyCRACKER, a robust method for the unsupervised partitioning of polyploid subgenomes by signatures of repetitive DNA evolution.

BMC genomics
BACKGROUND: Our understanding of polyploid genomes is limited by our inability to definitively assign sequences to a specific subgenome without extensive prior knowledge like high resolution genetic maps or genome sequences of diploid progenitors. In...

Coupling dynamics and evolutionary information with structure to identify protein regulatory and functional binding sites.

Proteins
Binding sites in proteins can be either specifically functional binding sites (active sites) that bind specific substrates with high affinity or regulatory binding sites (allosteric sites), that modulate the activity of functional binding sites throu...