AIMC Topic: Evolution, Molecular

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Development and validation of multiple machine learning algorithms for the classification of G-protein-coupled receptors using molecular evolution model-based feature extraction strategy.

Amino acids
Machine learning is one of the most potential ways to realize the function prediction of the incremental large-scale G-protein-coupled receptors (GPCR). Prior research reveals that the key to determining the overall classification accuracy of GPCR is...

Evolutionarily informed machine learning enhances the power of predictive gene-to-phenotype relationships.

Nature communications
Inferring phenotypic outcomes from genomic features is both a promise and challenge for systems biology. Using gene expression data to predict phenotypic outcomes, and functionally validating the genes with predictive powers are two challenges we add...

The lower threshold as a unifying principle between Code Biology and Biosemiotics.

Bio Systems
Whether we emphasize the notion of 'sign' or the notion of 'code', either way the main interest of biosemiotics and Code Biology is the same, and we argue that the idea of the lower threshold is what still unifies these two groups. Code Biology conce...

Accurate Identification of Antioxidant Proteins Based on a Combination of Machine Learning Techniques and Hidden Markov Model Profiles.

Computational and mathematical methods in medicine
Antioxidant proteins (AOPs) play important roles in the management and prevention of several human diseases due to their ability to neutralize excess free radicals. However, the identification of AOPs by using wet-lab experimental techniques is often...

Application of the random forest algorithm to Streptococcus pyogenes response regulator allele variation: from machine learning to evolutionary models.

Scientific reports
Group A Streptococcus (GAS) is a globally significant bacterial pathogen. The GAS genotyping gold standard characterises the nucleotide variation of emm, which encodes a surface-exposed protein that is recombinogenic and under immune-based selection ...

Recent Applications of Deep Learning Methods on Evolution- and Contact-Based Protein Structure Prediction.

International journal of molecular sciences
The new advances in deep learning methods have influenced many aspects of scientific research, including the study of the protein system. The prediction of proteins' 3D structural components is now heavily dependent on machine learning techniques tha...

Detecting adaptive introgression in human evolution using convolutional neural networks.

eLife
Studies in a variety of species have shown evidence for positively selected variants introduced into a population via introgression from another, distantly related population-a process known as adaptive introgression. However, there are few explicit ...

Cross-Predicting Essential Genes between Two Model Eukaryotic Species Using Machine Learning.

International journal of molecular sciences
Experimental studies of and have contributed substantially to our understanding of molecular and cellular processes in metazoans at large. Since the publication of their genomes, functional genomic investigations have identified genes that are esse...

Automatic Search-and-Replace From Examples With Coevolutionary Genetic Programming.

IEEE transactions on cybernetics
We describe the design and implementation of a system for executing search-and-replace text processing tasks automatically, based only on examples of the desired behavior. The examples consist of pairs describing the original string and the desired m...