AIMC Topic: Selection, Genetic

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Evaluation of the efficiency of artificial neural networks for genetic value prediction.

Genetics and molecular research : GMR Mar 28, 2016
Artificial neural networks have shown great potential when applied to breeding programs. In this study, we propose the use of artificial neural networks as a viable alternative to conventional prediction methods. We conduct a thorough evaluation of t...
Genetic Fitness Neural Networks, Computer Models, Genetic Phenotype Breeding Selection, Genetic Animals Genotype
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S/HIC: Robust Identification of Soft and Hard Sweeps Using Machine Learning.

PLoS genetics Mar 15, 2016
Detecting the targets of adaptive natural selection from whole genome sequencing data is a central problem for population genetics. However, to date most methods have shown sub-optimal performance under realistic demographic scenarios. Moreover, over...
Chromosomes, Human, Pair 18 Genetic Drift Selection, Genetic Genetics, Population Humans Haplotypes Genome, Human Machine Learning
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Hierarchical boosting: a machine-learning framework to detect and classify hard selective sweeps in human populations.

Bioinformatics (Oxford, England) Aug 26, 2015
MOTIVATION: Detecting positive selection in genomic regions is a recurrent topic in natural population genetic studies. However, there is little consistency among the regions detected in several genome-wide scans using different tests and/or populati...
Selection, Genetic Demography Genetics, Population Machine Learning Genomics Polymorphism, Genetic Humans
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Artificial neural networks reveal efficiency in genetic value prediction.

Genetics and molecular research : GMR Jun 18, 2015
The objective of this study was to evaluate the efficiency of artificial neural networks (ANNs) for predicting genetic value in experiments carried out in randomized blocks. Sixteen scenarios were simulated with different values of heritability (10, ...
Inheritance Patterns Computer Simulation Reproducibility of Results Animals Breeding Genotype Selection, Genetic Neural Networks, Computer Plants Genetics, Population Phenotype
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DANN: a deep learning approach for annotating the pathogenicity of genetic variants.

Bioinformatics (Oxford, England) Oct 22, 2014
UNLABELLED: Annotating genetic variants, especially non-coding variants, for the purpose of identifying pathogenic variants remains a challenge. Combined annotation-dependent depletion (CADD) is an algorithm designed to annotate both coding and non-c...
Genetic Variation Selection, Genetic Genome, Human Algorithms Molecular Sequence Annotation Support Vector Machine Computer Graphics Humans Neural Networks, Computer Area Under Curve
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Genomic selection: Essence, applications, and prospects.

The plant genome Jun 1, 2025
Genomic selection (GS) emerged as a key part of the solution to ensure the food supply for the growing human population thanks to advances in genotyping and other enabling technologies and improved understanding of the genotype-phenotype relationship...
Phenotype Selection, Genetic Genome, Plant Plant Breeding Genotype Genomics Crops, Agricultural
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Efficient Detection and Characterization of Targets of Natural Selection Using Transfer Learning.

Molecular biology and evolution Apr 30, 2025
Natural selection leaves detectable patterns of altered spatial diversity within genomes, and identifying affected regions is crucial for understanding species evolution. Recently, machine learning approaches applied to raw population genomic data ha...
Machine Learning Selection, Genetic Humans Neural Networks, Computer
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Predicting Fitness-Related Traits Using Gene Expression and Machine Learning.

Genome biology and evolution Feb 3, 2025
Evolution by natural selection occurs at its most basic through the change in frequencies of alleles; connecting those genomic targets to phenotypic selection is an important goal for evolutionary biology in the genomics era. The relative abundance o...
Selection, Genetic Gene Expression Regulation, Plant Genetic Fitness Ipomoea Photosynthesis Machine Learning Phenotype Transcriptome
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Deep learning insights into distinct patterns of polygenic adaptation across human populations.

Nucleic acids research Dec 11, 2024
Response to spatiotemporal variation in selection gradients resulted in signatures of polygenic adaptation in human genomes. We introduce RAISING, a two-stage deep learning framework that optimizes neural network architecture through hyperparameter t...
Neural Networks, Computer Phylogeny Deep Learning Humans Genome, Human Selection, Genetic Adaptation, Physiological Genomics Models, Genetic Multifactorial Inheritance Genetics, Population
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Scalable CNN-based classification of selective sweeps using derived allele frequencies.

Bioinformatics (Oxford, England) Sep 1, 2024
MOTIVATION: Selective sweeps can successfully be distinguished from neutral genetic data using summary statistics and likelihood-based methods that analyze single nucleotide polymorphisms (SNPs). However, these methods are sensitive to confounding fa...
Selection, Genetic Neural Networks, Computer Machine Learning Polymorphism, Single Nucleotide Gene Frequency Algorithms Humans
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