AIMC Topic: Evolution, Molecular

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Accurate prediction of protein torsion angles using evolutionary signatures and recurrent neural network.

Scientific reports Oct 26, 2021
The amino acid sequence of a protein contains all the necessary information to specify its shape, which dictates its biological activities. However, it is challenging and expensive to experimentally determine the three-dimensional structure of protei...
Protein Structure, Secondary Neural Networks, Computer Protein Structure, Tertiary Software Evolution, Molecular Proteins Databases, Protein Predictive Value of Tests
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Revisiting the out of Africa event with a deep-learning approach.

American journal of human genetics Oct 8, 2021
Anatomically modern humans evolved around 300 thousand years ago in Africa. They started to appear in the fossil record outside of Africa as early as 100 thousand years ago, although other hominins existed throughout Eurasia much earlier. Recently, s...
Humans Algorithms Whole Genome Sequencing Genetic Variation Africa Monte Carlo Method Deep Learning Fossils Evolution, Molecular Bayes Theorem
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ECNet is an evolutionary context-integrated deep learning framework for protein engineering.

Nature communications Sep 30, 2021
Machine learning has been increasingly used for protein engineering. However, because the general sequence contexts they capture are not specific to the protein being engineered, the accuracy of existing machine learning algorithms is rather limited....
beta-Lactam Resistance Genetic Fitness Datasets as Topic Protein Engineering Sequence Homology, Amino Acid Deep Learning Evolution, Molecular Mutation Amino Acid Sequence beta-Lactamases High-Throughput Screening Assays
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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 Sep 25, 2021
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...
Machine Learning Algorithms Sequence Alignment Evolution, Molecular Receptors, G-Protein-Coupled Amino Acid Sequence Multigene Family
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Evolutionarily informed machine learning enhances the power of predictive gene-to-phenotype relationships.

Nature communications Sep 24, 2021
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...
Machine Learning Phenotype Transcriptome Species Specificity Genome, Plant Evolution, Molecular Gene Expression Regulation, Plant Zea mays Arabidopsis Nitrogen Genomics Genetic Variation Genotype Models, Genetic
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The lower threshold as a unifying principle between Code Biology and Biosemiotics.

Bio Systems Aug 25, 2021
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...
Genetic Code Animals Systems Biology Evolution, Molecular Humans Robotics Artificial Intelligence
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Accurate Identification of Antioxidant Proteins Based on a Combination of Machine Learning Techniques and Hidden Markov Model Profiles.

Computational and mathematical methods in medicine Aug 7, 2021
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...
Databases, Protein Computational Biology Humans Peroxiredoxins Amino Acids Antioxidants Machine Learning Markov Chains Algorithms Evolution, Molecular Proteins
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Application of the random forest algorithm to Streptococcus pyogenes response regulator allele variation: from machine learning to evolutionary models.

Scientific reports Jun 16, 2021
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 ...
Regulon Genes, Bacterial Bacterial Outer Membrane Proteins Antigens, Bacterial Carrier Proteins Humans Streptococcal Infections Genome, Bacterial Evolution, Molecular Machine Learning Genetic Variation Bacterial Proteins Algorithms Streptococcus pyogenes Alleles
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Machine-learning predicts genomic determinants of meiosis-driven structural variation in a eukaryotic pathogen.

Nature communications Jun 10, 2021
Species harbor extensive structural variation underpinning recent adaptive evolution. However, the causality between genomic features and the induction of new rearrangements is poorly established. Here, we analyze a global set of telomere-to-telomere...
Machine Learning Sequence Inversion Computer Simulation Phylogeny Genome-Wide Association Study Genomics Polymorphism, Single Nucleotide Eukaryota Polymorphism, Genetic Genome Ascomycota INDEL Mutation Pedigree Arabidopsis Models, Genetic Chromosomes Meiosis Retroelements Evolution, Molecular Crossing Over, Genetic Genetic Variation Genes, Duplicate
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Recent Applications of Deep Learning Methods on Evolution- and Contact-Based Protein Structure Prediction.

International journal of molecular sciences Jun 2, 2021
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...
Evolution, Molecular Databases, Protein Amino Acid Sequence Protein Conformation Humans Software Neural Networks, Computer Sequence Alignment Deep Learning Machine Learning Computational Biology
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