AIMC Topic: Evolution, Molecular
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Detecting adaptive introgression in human evolution using convolutional neural networks.
eLife
May 25, 2021
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
May 11, 2021
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
Apr 15, 2021
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...
On the Unfounded Enthusiasm for Soft Selective Sweeps III: The Supervised Machine Learning Algorithm That Isn't.
Genes
Apr 5, 2021
In the last 15 years or so, soft selective sweep mechanisms have been catapulted from a curiosity of little evolutionary importance to a ubiquitous mechanism claimed to explain most adaptive evolution and, in some cases, most evolution. This transfor...
Harnessing machine learning to guide phylogenetic-tree search algorithms.
Nature communications
Mar 31, 2021
Inferring a phylogenetic tree is a fundamental challenge in evolutionary studies. Current paradigms for phylogenetic tree reconstruction rely on performing costly likelihood optimizations. With the aim of making tree inference feasible for problems i...
Trivial and nontrivial error sources account for misidentification of protein partners in mutual information approaches.
Scientific reports
Mar 25, 2021
The problem of finding the correct set of partners for a given pair of interacting protein families based on multi-sequence alignments (MSAs) has received great attention over the years. Recently, the native contacts of two interacting proteins were ...
Integrating structure-based machine learning and co-evolution to investigate specificity in plant sesquiterpene synthases.
PLoS computational biology
Mar 22, 2021
Sesquiterpene synthases (STSs) catalyze the formation of a large class of plant volatiles called sesquiterpenes. While thousands of putative STS sequences from diverse plant species are available, only a small number of them have been functionally ch...
Artificial intelligence in health data analysis: The Darwinian evolution theory suggests an extremely simple and zero-cost large-scale screening tool for prediabetes and type 2 diabetes.
Diabetes research and clinical practice
Feb 27, 2021
AIMS: The effective identification of individuals with early dysglycemia status is key to reduce the incidence of type 2 diabetes. We develop and validate a novel zero-cost tool that significantly simplifies the screening of undiagnosed dysglycemia.
An Elite Gene Guided Reproduction Operator for Many-Objective Optimization.
IEEE transactions on cybernetics
Jan 15, 2021
Traditional reproduction operators in many-objective evolutionary algorithms (MaOEAs) seem to not be so effective to tackle many-objective optimization problems (MaOPs). This is mainly because the population size cannot be set to an arbitrarily large...
Evolution of drug resistance in HIV protease.
BMC bioinformatics
Dec 30, 2020
BACKGROUND: Drug resistance is a critical problem limiting effective antiviral therapy for HIV/AIDS. Computational techniques for predicting drug resistance profiles from genomic data can accelerate the appropriate choice of therapy. These techniques...
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