AIMC Topic: Models, Genetic

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WheatGP, a genomic prediction method based on CNN and LSTM.

Briefings in bioinformatics Mar 4, 2025
Wheat plays a crucial role in ensuring food security. However, its complex genetic structure and trait variation pose significant challenges for breeding superior varieties. In this study, a genomic prediction method for wheat (WheatGP) is proposed. ...
Plant Breeding Triticum Genome, Plant Neural Networks, Computer Phenotype Genomics Models, Genetic
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Improvement in genomic prediction of maize with prior gene ontology information depends on traits and environmental conditions.

The plant genome Mar 1, 2025
Classical genomic prediction approaches rely on statistical associations between traits and markers rather than their biological significance. Biologically informed selection of genomic regions can help prioritize polymorphisms by considering underly...
Phenotype Genomics Gene Ontology Environment Genome, Plant Models, Genetic Zea mays Genetic Markers
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An efficient deep learning method for amino acid substitution model selection.

Journal of evolutionary biology Jan 3, 2025
Amino acid substitution models play an important role in studying the evolutionary relationships among species from protein sequences. The amino acid substitution model consists of a large number of parameters; therefore, it is estimated from hundred...
Computer Simulation Likelihood Functions Sequence Alignment Models, Genetic Evolution, Molecular Phylogeny Amino Acid Substitution Deep Learning
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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...
Deep Learning Genomics Models, Genetic Neural Networks, Computer Phylogeny Multifactorial Inheritance Genetics, Population Genome, Human Selection, Genetic Adaptation, Physiological Humans
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KPRR: a novel machine learning approach for effectively capturing nonadditive effects in genomic prediction.

Briefings in bioinformatics Nov 22, 2024
Nonadditive genetic effects pose significant challenges to traditional genomic selection methods for quantitative traits. Machine learning approaches, particularly kernel-based methods, offer promising solutions to overcome these limitations. In this...
Models, Genetic Oryza Data Accuracy Machine Learning Datasets as Topic Animals Genome Epistasis, Genetic
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Sub-sampling graph neural networks for genomic prediction of quantitative phenotypes.

G3 (Bethesda, Md.) Nov 6, 2024
In genomics, use of deep learning (DL) is rapidly growing and DL has successfully demonstrated its ability to uncover complex relationships in large biological and biomedical data sets. With the development of high-throughput sequencing techniques, g...
Genomics Polymorphism, Single Nucleotide Models, Genetic Triticum Phenotype Neural Networks, Computer Quantitative Trait Loci Animals Algorithms Genome-Wide Association Study
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Using Runs of Homozygosity and Machine Learning to Disentangle Sources of Inbreeding and Infer Self-Fertilization Rates.

Genome biology and evolution Jul 3, 2024
Runs of homozygosity (ROHs) are indicative of elevated homozygosity and inbreeding due to mating of closely related individuals. Self-fertilization can be a major source of inbreeding which elevates genome-wide homozygosity and thus should also creat...
Machine Learning Animals Self-Fertilization Models, Genetic Homozygote Genetics, Population Inbreeding
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Computationally Efficient Demographic History Inference from Allele Frequencies with Supervised Machine Learning.

Molecular biology and evolution May 3, 2024
Inferring past demographic history of natural populations from genomic data is of central concern in many studies across research fields. Previously, our group had developed dadi, a widely used demographic history inference method based on the allele...
Gene Frequency Genetics, Population Neural Networks, Computer Models, Genetic Supervised Machine Learning Humans
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Application of Artificial Neural Network and Genetic Algorithm Modeling for In Vitro Regeneration of Seaweed Seedling Production.

Methods in molecular biology (Clifton, N.J.) Jan 1, 2024
Marine macro-algae, commonly known as "seaweed," are used in everyday commodity products worldwide for food, feed, and biostimulant for plants and animals and continue to be one of the conspicuous components of world aquaculture production. However, ...
Seedlings Algorithms Regeneration Seaweed Models, Genetic Neural Networks, Computer Aquaculture Machine Learning
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Epistatic Features and Machine Learning Improve Alzheimer's Disease Risk Prediction Over Polygenic Risk Scores.

Journal of Alzheimer's disease : JAD Jan 1, 2024
BACKGROUND: Polygenic risk scores (PRS) are linear combinations of genetic markers weighted by effect size that are commonly used to predict disease risk. For complex heritable diseases such as late-onset Alzheimer's disease (LOAD), PRS models fail t...
Genetic Risk Score Male Humans Machine Learning Genome-Wide Association Study Polymorphism, Single Nucleotide Apolipoproteins E Female Models, Genetic Epistasis, Genetic Genetic Predisposition to Disease Aged Alzheimer Disease Multifactorial Inheritance
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