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Evolution, Molecular

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A new approach to the automatic identification of organism evolution using neural networks.

Bio Systems
Automatic identification of organism evolution still remains a challenging task, which is especially exiting, when the evolution of human is considered. The main aim of this work is to present a new idea to allow organism evolution analysis using neu...

Protein folds recognized by an intelligent predictor based-on evolutionary and structural information.

Journal of computational chemistry
Protein fold recognition is an important and essential step in determining tertiary structure of a protein in biological science. In this study, a model termed NiRecor is developed for recognizing protein folds based on artificial neural networks inc...

Systematic Analysis and Prediction of In Situ Cross Talk of O-GlcNAcylation and Phosphorylation.

BioMed research international
Reversible posttranslational modification (PTM) plays a very important role in biological process by changing properties of proteins. As many proteins are multiply modified by PTMs, cross talk of PTMs is becoming an intriguing topic and draws much at...

Protein contact prediction by integrating joint evolutionary coupling analysis and supervised learning.

Bioinformatics (Oxford, England)
MOTIVATION: Protein contact prediction is important for protein structure and functional study. Both evolutionary coupling (EC) analysis and supervised machine learning methods have been developed, making use of different information sources. However...

Better prediction of functional effects for sequence variants.

BMC genomics
Elucidating the effects of naturally occurring genetic variation is one of the major challenges for personalized health and personalized medicine. Here, we introduce SNAP2, a novel neural network based classifier that improves over the state-of-the-a...

Toll-like receptor signaling in vertebrates: testing the integration of protein, complex, and pathway data in the protein ontology framework.

PloS one
The Protein Ontology (PRO) provides terms for and supports annotation of species-specific protein complexes in an ontology framework that relates them both to their components and to species-independent families of complexes. Comprehensive curation o...

Bridging scales in cancer progression: mapping genotype to phenotype using neural networks.

Seminars in cancer biology
In this review we summarise our recent efforts in trying to understand the role of heterogeneity in cancer progression by using neural networks to characterise different aspects of the mapping from a cancer cells genotype and environment to its pheno...

Phyloformer: Fast, Accurate, and Versatile Phylogenetic Reconstruction with Deep Neural Networks.

Molecular biology and evolution
Phylogenetic inference aims at reconstructing the tree describing the evolution of a set of sequences descending from a common ancestor. The high computational cost of state-of-the-art maximum likelihood and Bayesian inference methods limits their us...

Using minor variant genomes and machine learning to study the genome biology of SARS-CoV-2 over time.

Nucleic acids research
In infected individuals, viruses are present as a population consisting of dominant and minor variant genomes. Most databases contain information on the dominant genome sequence. Since the emergence of SARS-CoV-2 in late 2019, variants have been sele...

An efficient deep learning method for amino acid substitution model selection.

Journal of evolutionary biology
Amino acid substitution models play an important role in studying the evolutionary relationships among species from protein sequences. The amino acid substitution model consists of a large number of parameters; therefore, it is estimated from hundred...