AIMC Topic: Evolution, Molecular

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Predicting hotspots for disease-causing single nucleotide variants using sequences-based coevolution, network analysis, and machine learning.

PloS one May 14, 2024
To enable personalized medicine, it is important yet highly challenging to accurately predict disease-causing mutations in target proteins at high throughput. Previous computational methods have been developed using evolutionary information in combin...
Computational Biology Evolution, Molecular Proteins Mutation Algorithms Polymorphism, Single Nucleotide Humans Machine Learning
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Deciphering the Coevolutionary Dynamics of L2 β-Lactamases via Deep Learning.

Journal of chemical information and modeling Apr 30, 2024
L2 β-lactamases, serine-based class A β-lactamases expressed by , play a pivotal role in antimicrobial resistance (AMR). However, limited studies have been conducted on these important enzymes. To understand the coevolutionary dynamics of L2 β-lactam...
Protein Conformation Stenotrophomonas maltophilia Deep Learning Evolution, Molecular Molecular Dynamics Simulation beta-Lactamases
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Essentiality, protein-protein interactions and evolutionary properties are key predictors for identifying cancer-associated genes using machine learning.

Scientific reports Apr 22, 2024
The distinctive nature of cancer as a disease prompts an exploration of the special characteristics the genes implicated in cancer exhibit. The identification of cancer-associated genes and their characteristics is crucial to further our understandin...
Humans Machine Learning Neoplasms Computational Biology Evolution, Molecular Protein Interaction Maps Genes, Essential
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Self-replicating artificial neural networks give rise to universal evolutionary dynamics.

PLoS computational biology Mar 28, 2024
In evolutionary models, mutations are exogenously introduced by the modeler, rather than endogenously introduced by the replicator itself. We present a new deep-learning based computational model, the self-replicating artificial neural network (SeRAN...
Evolution, Molecular Mutation Neural Networks, Computer Genotype Mutation Rate Biological Evolution
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Deep learning-powered enzyme efficiency boosting with evolutionary information.

Science bulletin Mar 19, 2024
Deep Learning Evolution, Molecular Enzymes
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The AI-driven Drug Design (AIDD) platform: an interactive multi-parameter optimization system integrating molecular evolution with physiologically based pharmacokinetic simulations.

Journal of computer-aided molecular design Mar 19, 2024
Computer-aided drug design has advanced rapidly in recent years, and multiple instances of in silico designed molecules advancing to the clinic have demonstrated the contribution of this field to medicine. Properly designed and implemented platforms ...
Drug Design Evolution, Molecular Artificial Intelligence Algorithms
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Evolutionary-scale prediction of atomic-level protein structure with a language model.

Science (New York, N.Y.) Mar 16, 2023
Recent advances in machine learning have leveraged evolutionary information in multiple sequence alignments to predict protein structure. We demonstrate direct inference of full atomic-level protein structure from primary sequence using a large langu...
Evolution, Molecular Proteins Protein Conformation Sequence Analysis, Protein Machine Learning Amino Acid Sequence
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Experimental exploration of a ribozyme neutral network using evolutionary algorithm and deep learning.

Nature communications Aug 17, 2022
A neutral network connects all genotypes with equivalent phenotypes in a fitness landscape and plays an important role in the mutational robustness and evolvability of biomolecules. In contrast to earlier theoretical works, evidence of large neutral ...
Deep Learning Genotype Models, Genetic Evolution, Molecular Algorithms RNA, Catalytic Mutation Genetic Fitness
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Evolution and dispersal of mitochondrial DNA haplogroup U5 in Northern Europe: insights from an unsupervised learning approach to phylogeography.

BMC genomics May 7, 2022
BACKGROUND: We combined an unsupervised learning methodology for analyzing mitogenome sequences with maximum likelihood (ML) phylogenetics to make detailed inferences about the evolution and diversification of mitochondrial DNA (mtDNA) haplogroup U5,...
Phylogeny Europe Humans Bayes Theorem Genetics, Population Haplotypes Evolution, Molecular DNA, Mitochondrial Phylogeography Unsupervised Machine Learning
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Re-evaluating Deep Neural Networks for Phylogeny Estimation: The Issue of Taxon Sampling.

Journal of computational biology : a journal of computational molecular cell biology Jan 5, 2022
Deep neural networks (DNNs) have been recently proposed for quartet tree phylogeny estimation. Here, we present a study evaluating recently trained DNNs in comparison to a collection of standard phylogeny estimation methods on a heterogeneous collect...
Classification Computational Biology Databases, Genetic Phylogeny Evolution, Molecular Neural Networks, Computer Deep Learning Amino Acid Sequence Computer Simulation
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