AIMC Topic: Models, Genetic

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A Secure High-Order Gene Interaction Detection Algorithm Based on Deep Neural Network.

IEEE/ACM transactions on computational biology and bioinformatics Aug 9, 2024
Identifying high-order Single Nucleotide Polymorphism (SNP) interactions of additive genetic model is crucial for detecting complex disease gene-type and predicting pathogenic genes of various disorders. We present a novel framework for high-order ge...
Algorithms Deep Learning Polymorphism, Single Nucleotide Humans Neural Networks, Computer Computational Biology Models, Genetic Epistasis, Genetic
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Enhancing schizophrenia phenotype prediction from genotype data through knowledge-driven deep neural network models.

Genomics Aug 5, 2024
This article explores deep learning model design, drawing inspiration from the omnigenic model and genetic heterogeneity concepts, to improve schizophrenia prediction using genotype data. It introduces an innovative three-step approach leveraging neu...
Humans Neural Networks, Computer Phenotype Models, Genetic Schizophrenia Deep Learning Genotype
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Reliable estimation of tree branch lengths using deep neural networks.

PLoS computational biology Aug 5, 2024
A phylogenetic tree represents hypothesized evolutionary history for a set of taxa. Besides the branching patterns (i.e., tree topology), phylogenies contain information about the evolutionary distances (i.e. branch lengths) between all taxa in the t...
Sequence Alignment Evolution, Molecular Likelihood Functions Machine Learning Algorithms Phylogeny Deep Learning Computational Biology Models, Genetic Neural Networks, Computer
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Current genomic deep learning models display decreased performance in cell type-specific accessible regions.

Genome biology Aug 1, 2024
BACKGROUND: A number of deep learning models have been developed to predict epigenetic features such as chromatin accessibility from DNA sequence. Model evaluations commonly report performance genome-wide; however, cis regulatory elements (CREs), whi...
Humans Deep Learning Organ Specificity Regulatory Sequences, Nucleic Acid Chromatin Genomics Epigenesis, Genetic Models, Genetic
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Using machine learning to combine genetic and environmental data for maize grain yield predictions across multi-environment trials.

TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik Jul 23, 2024
Incorporating feature-engineered environmental data into machine learning-based genomic prediction models is an efficient approach to indirectly model genotype-by-environment interactions. Complementing phenotypic traits and molecular markers with hi...
Environment Gene-Environment Interaction Plant Breeding Zea mays Edible Grain Machine Learning Phenotype Genomics Genotype Models, Genetic
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Inferring phylogenetic networks from multifurcating trees via cherry picking and machine learning.

Molecular phylogenetics and evolution Jul 17, 2024
The Hybridization problem asks to reconcile a set of conflicting phylogenetic trees into a single phylogenetic network with the smallest possible number of reticulation nodes. This problem is computationally hard and previous solutions are limited to...
Machine Learning Algorithms Phylogeny Models, Genetic Hybridization, Genetic
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The Prediction of Recombination Hotspot Based on Automated Machine Learning.

Journal of molecular biology Jun 12, 2024
Meiotic recombination plays a pivotal role in genetic evolution. Genetic variation induced by recombination is a crucial factor in generating biodiversity and a driving force for evolution. At present, the development of recombination hotspot predict...
Recombination, Genetic Algorithms Computational Biology Models, Genetic Humans Machine Learning
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Artificial intelligence enables unified analysis of historical and landscape influences on genetic diversity.

Molecular phylogenetics and evolution Jun 12, 2024
While genetic variation in any species is potentially shaped by a range of processes, phylogeography and landscape genetics are largely concerned with inferring how environmental conditions and landscape features impact neutral intraspecific diversit...
Models, Genetic Genetic Variation Anura Phylogeography Genetics, Population Animals Brazil Polymorphism, Single Nucleotide Artificial Intelligence
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Machine learning models for predicting blood pressure phenotypes by combining multiple polygenic risk scores.

Scientific reports May 30, 2024
We construct non-linear machine learning (ML) prediction models for systolic and diastolic blood pressure (SBP, DBP) using demographic and clinical variables and polygenic risk scores (PRSs). We developed a two-model ensemble, consisting of a baselin...
Multifactorial Inheritance Genetic Risk Score Hypertension Blood Pressure Male Middle Aged Genome-Wide Association Study Genetic Predisposition to Disease Models, Genetic Humans Phenotype Machine Learning Female Risk Factors
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Residual networks without pooling layers improve the accuracy of genomic predictions.

TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik May 21, 2024
Residual neural network genomic selection is the first GS algorithm to reach 35 layers, and its prediction accuracy surpasses previous algorithms. With the decrease in DNA sequencing costs and the development of deep learning, phenotype prediction ac...
Gene-Environment Interaction Neural Networks, Computer Genomics Algorithms Models, Genetic Phenotype Selection, Genetic Deep Learning
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