AIMC Topic: Genetics, Population

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Path Planning of Mobile Robots Based on a Multi-Population Migration Genetic Algorithm.

Sensors (Basel, Switzerland) Oct 17, 2020
In the field of robot path planning, aiming at the problems of the standard genetic algorithm, such as premature maturity, low convergence path quality, poor population diversity, and difficulty in breaking the local optimal solution, this paper prop...
Computer Simulation Robotics Genetics, Population Algorithms
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How Machine Learning Methods Helped Find Putative Rye Wax Genes Among GBS Data.

International journal of molecular sciences Oct 12, 2020
The standard approach to genetic mapping was supplemented by machine learning (ML) to establish the location of the rye gene associated with epicuticular wax formation (glaucous phenotype). Over 180 plants of the biparental F population were genotype...
Machine Learning Phenotype Biomarkers Quantitative Trait Loci Genotype Genes, Plant Genetic Markers Chromosome Mapping Secale Genetics, Population Waxes
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Deep learning for population size history inference: Design, comparison and combination with approximate Bayesian computation.

Molecular ecology resources Jul 25, 2020
For the past decades, simulation-based likelihood-free inference methods have enabled researchers to address numerous population genetics problems. As the richness and amount of simulated and real genetic data keep increasing, the field has a strong ...
Deep Learning Cattle Models, Genetic Population Density Bayes Theorem Computer Simulation Genetics, Population Animals
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Opening the Black Box: Interpretable Machine Learning for Geneticists.

Trends in genetics : TIG Apr 17, 2020
Because of its ability to find complex patterns in high dimensional and heterogeneous data, machine learning (ML) has emerged as a critical tool for making sense of the growing amount of genetic and genomic data available. While the complexity of ML ...
Humans Genome, Human Genetics, Population Machine Learning Computational Biology Genetics, Medical
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Dimensionality reduction reveals fine-scale structure in the Japanese population with consequences for polygenic risk prediction.

Nature communications Mar 26, 2020
The diversity in our genome is crucial to understanding the demographic history of worldwide populations. However, we have yet to know whether subtle genetic differences within a population can be disentangled, or whether they have an impact on compl...
Risk Factors Genetic Predisposition to Disease Principal Component Analysis Asian People Humans Phenotype Multifactor Dimensionality Reduction Multifactorial Inheritance Genetics, Population Biological Specimen Banks Japan Base Sequence
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ImaGene: a convolutional neural network to quantify natural selection from genomic data.

BMC bioinformatics Nov 22, 2019
BACKGROUND: The genetic bases of many complex phenotypes are still largely unknown, mostly due to the polygenic nature of the traits and the small effect of each associated mutation. An alternative approach to classic association studies to determini...
Genetics, Population Software Algorithms Phenotype Alleles Selection, Genetic Genomics Databases, Genetic Humans Neural Networks, Computer
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Estimation of allele-specific fitness effects across human protein-coding sequences and implications for disease.

Genome research Jun 27, 2019
A central challenge in human genomics is to understand the cellular, evolutionary, and clinical significance of genetic variants. Here, we introduce a unified population-genetic and machine-learning model, called inear llele-pecific election nferenc ...
Genetic Fitness Polymorphism, Single Nucleotide Selection, Genetic Proteome Genetics, Population Models, Genetic Inheritance Patterns Machine Learning Base Sequence Alleles Autism Spectrum Disorder Genome, Human Neoplasms Humans Genetic Variation Genomics
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A single nucleotide polymorphism panel for individual identification and ancestry assignment in Caucasians and four East and Southeast Asian populations using a machine learning classifier.

Forensic science, medicine, and pathology Jan 16, 2019
Single nucleotide polymorphism (SNP) profiling is an effective means of individual identification and ancestry inferences in forensic genetics. This study established a SNP panel for the simultaneous individual identification and ancestry assignment ...
Asian People White People Gene Frequency Genetics, Population DNA Fingerprinting Asia Chromosomes, Human, Y Genotype Humans Support Vector Machine DNA, Mitochondrial Machine Learning Chromosomes, Human, X Female Retrospective Studies DNA Degradation, Necrotic Male Polymorphism, Single Nucleotide
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Supervised machine learning reveals introgressed loci in the genomes of Drosophila simulans and D. sechellia.

PLoS genetics Apr 23, 2018
Hybridization and gene flow between species appears to be common. Even though it is clear that hybridization is widespread across all surveyed taxonomic groups, the magnitude and consequences of introgression are still largely unknown. Thus it is cru...
Species Specificity Software Models, Genetic Computer Simulation Supervised Machine Learning Gene Flow Genome, Insect Hybridization, Genetic Drosophila Evolution, Molecular Animals Genetics, Population Genetic Variation Genetic Speciation Haplotypes Drosophila simulans
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Supervised Machine Learning for Population Genetics: A New Paradigm.

Trends in genetics : TIG Jan 10, 2018
As population genomic datasets grow in size, researchers are faced with the daunting task of making sense of a flood of information. To keep pace with this explosion of data, computational methodologies for population genetic inference are rapidly be...
Biological Evolution Datasets as Topic Humans Genetics, Population Genome, Human Supervised Machine Learning Selection, Genetic Data Mining
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