AIMC Topic: 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 Genotype Models, Genetic Genomics
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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...
Phylogeny Models, Genetic Hybridization, Genetic Machine Learning Algorithms
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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...
Humans Computational Biology Machine Learning Models, Genetic Algorithms Recombination, Genetic
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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...
Brazil Polymorphism, Single Nucleotide Models, Genetic Artificial Intelligence Animals Phylogeography Genetics, Population Genetic Variation Anura
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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 Humans Machine Learning Genome-Wide Association Study Phenotype Hypertension Genetic Predisposition to Disease Risk Factors Models, Genetic Female Blood Pressure Male Middle Aged
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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...
Deep Learning Genomics Selection, Genetic Gene-Environment Interaction Models, Genetic Neural Networks, Computer Algorithms Phenotype
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Applications of machine learning in phylogenetics.

Molecular phylogenetics and evolution Mar 31, 2024
Machine learning has increasingly been applied to a wide range of questions in phylogenetic inference. Supervised machine learning approaches that rely on simulated training data have been used to infer tree topologies and branch lengths, to select s...
Phylogeny Models, Genetic Supervised Machine Learning Machine Learning
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[Development of prognostic clinical and genetic models of the risk of low bone mineral density using neural network training].

Problemy endokrinologii Jan 24, 2024
BACKGROUND: Osteoporosis is a common age-related disease with disabling consequences, the early diagnosis of which is difficult due to its long and hidden course, which often leads to diagnosis only after a fracture. In this regard, great expectation...
Bone Density Models, Genetic Osteoporosis Male Humans Aged Machine Learning Female Middle Aged Neural Networks, Computer Adult Prognosis
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Using machine learning and partial dependence to evaluate robustness of best linear unbiased prediction (BLUP) for phenotypic values.

Journal of applied genetics Jan 3, 2024
Best linear unbiased prediction (BLUP) is widely used in plant research to address experimental variation. For phenotypic values, BLUP accuracy is largely dependent on properly controlled experimental repetition and how variable components are outlin...
Models, Genetic Linear Models Phenotype Genotype Machine Learning
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Hold out the genome: a roadmap to solving the cis-regulatory code.

Nature Dec 13, 2023
Gene expression is regulated by transcription factors that work together to read cis-regulatory DNA sequences. The 'cis-regulatory code' - how cells interpret DNA sequences to determine when, where and how much genes should be expressed - has proven ...
Machine Learning DNA Models, Genetic Regulatory Sequences, Nucleic Acid Genomics Transcription Factors
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