AIMC Topic: Evolution, Molecular

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Computed structures of core eukaryotic protein complexes.

Science (New York, N.Y.) Dec 10, 2021
Protein-protein interactions play critical roles in biology, but the structures of many eukaryotic protein complexes are unknown, and there are likely many interactions not yet identified. We take advantage of advances in proteome-wide amino acid coe...
Ubiquitin Protein Interaction Mapping Saccharomyces cerevisiae Proteins DNA Repair Models, Molecular Protein Conformation Saccharomyces cerevisiae Acyltransferases Homologous Recombination Chromosome Segregation Ligases Protein Biosynthesis Computer Simulation Ribosomes Deep Learning Multiprotein Complexes Protein Interaction Maps Membrane Proteins Evolution, Molecular Computational Biology Proteome
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Co-evolution based machine-learning for predicting functional interactions between human genes.

Nature communications Nov 9, 2021
Over the next decade, more than a million eukaryotic species are expected to be fully sequenced. This has the potential to improve our understanding of genotype and phenotype crosstalk, gene function and interactions, and answer evolutionary question...
Sequence Analysis, DNA Evolution, Molecular DNA Repair Humans Machine Learning Phylogeny
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TwinCons: Conservation score for uncovering deep sequence similarity and divergence.

PLoS computational biology Oct 29, 2021
We have developed the program TwinCons, to detect noisy signals of deep ancestry of proteins or nucleic acids. As input, the program uses a composite alignment containing pre-defined groups, and mathematically determines a 'cost' of transforming one ...
Sequence Analysis, Protein Deep Learning Metagenomics Archaeal Proteins Sequence Alignment Evolution, Molecular RNA, Ribosomal Conserved Sequence Bacterial Proteins
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Disease variant prediction with deep generative models of evolutionary data.

Nature Oct 27, 2021
Quantifying the pathogenicity of protein variants in human disease-related genes would have a marked effect on clinical decisions, yet the overwhelming majority (over 98%) of these variants still have unknown consequences. In principle, computational...
Selection, Genetic Genetic Fitness Biological Assay Genetic Variation Disease Unsupervised Machine Learning Models, Molecular Bayes Theorem Humans Evolution, Molecular Proteins Phenotype Genetic Predisposition to Disease
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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...
Predictive Value of Tests Protein Structure, Secondary Protein Structure, Tertiary Neural Networks, Computer Proteins Databases, Protein Software Evolution, Molecular
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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 Africa Whole Genome Sequencing Genetic Variation Monte Carlo Method Fossils Deep Learning 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 beta-Lactamases Mutation Evolution, Molecular High-Throughput Screening Assays Amino Acid Sequence
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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 Amino Acid Sequence Sequence Alignment Evolution, Molecular Multigene Family Receptors, G-Protein-Coupled
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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...
Zea mays Nitrogen Genetic Variation Gene Expression Regulation, Plant Arabidopsis Machine Learning Genotype Species Specificity Phenotype Models, Genetic Genome, Plant Transcriptome Evolution, Molecular Genomics
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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...
Systems Biology Genetic Code Humans Evolution, Molecular Artificial Intelligence Robotics Animals
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