AIMC Topic: Multifactorial Inheritance

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Yield prediction through integration of genetic, environment, and management data through deep learning.

G3 (Bethesda, Md.) Apr 11, 2023
Accurate prediction of the phenotypic outcomes produced by different combinations of genotypes, environments, and management interventions remains a key goal in biology with direct applications to agriculture, research, and conservation. The past dec...
Deep Learning Genotype Multifactorial Inheritance Neural Networks, Computer Machine Learning
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A comprehensive investigation of statistical and machine learning approaches for predicting complex human diseases on genomic variants.

Briefings in bioinformatics Jan 19, 2023
Quantifying an individual's risk for common diseases is an important goal of precision health. The polygenic risk score (PRS), which aggregates multiple risk alleles of candidate diseases, has emerged as a standard approach for identifying high-risk ...
Humans Genome-Wide Association Study Genomics Machine Learning Genetic Predisposition to Disease Multifactorial Inheritance Risk Factors
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Identifying Digenic Disease Genes with Machine Learning.

American journal of medical genetics. Part A Jan 1, 2022
Humans Multifactorial Inheritance Machine Learning
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Discriminating Heterogeneous Trajectories of Resilience and Depression After Major Life Stressors Using Polygenic Scores.

JAMA psychiatry Jul 1, 2021
IMPORTANCE: Major life stressors, such as loss and trauma, increase the risk of depression. It is known that individuals show heterogeneous trajectories of depressive symptoms following major life stressors, including chronic depression, recovery, an...
Female Aged Male Humans Resilience, Psychological Stress, Psychological Genome-Wide Association Study Middle Aged Deep Learning Multifactorial Inheritance Longitudinal Studies Supervised Machine Learning Depressive Disorder Genetic Predisposition to Disease United States
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Epistasis Analysis: Classification Through Machine Learning Methods.

Methods in molecular biology (Clifton, N.J.) Jan 1, 2021
Complex disease is different from Mendelian disorders. Its development usually involves the interaction of multiple genes or the interaction between genes and the environment (i.e. epistasis). Although the high-throughput sequencing technologies for ...
Epistasis, Genetic Humans Multifactor Dimensionality Reduction Polymorphism, Single Nucleotide Datasets as Topic Machine Learning Computational Biology Multifactorial Inheritance Models, Genetic Software
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A Belief Degree-Associated Fuzzy Multifactor Dimensionality Reduction Framework for Epistasis Detection.

Methods in molecular biology (Clifton, N.J.) Jan 1, 2021
Epistasis is a challenge in prediction, classification, and suspicion of human genetic diseases. Many technologies, methods, and tools have been developed for epistasis detection. Multifactor dimensionality reduction (MDR) is the method commonly used...
Multifactorial Inheritance Coronary Artery Disease Datasets as Topic Uncertainty Multifactor Dimensionality Reduction Epistasis, Genetic Models, Genetic Databases, Genetic Fuzzy Logic Algorithms Polymorphism, Single Nucleotide Humans Software
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Genome-wide prediction for complex traits under the presence of dominance effects in simulated populations using GBLUP and machine learning methods.

Journal of animal science Jun 1, 2020
The aim of this study was to compare the predictive performance of the Genomic Best Linear Unbiased Predictor (GBLUP) and machine learning methods (Random Forest, RF; Support Vector Machine, SVM; Artificial Neural Network, ANN) in simulated populatio...
Breeding Genome Genes, Dominant Multifactorial Inheritance Male Machine Learning Genomics Phenotype Genotype Computer Simulation Female Animals
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Multivariate Pattern Analysis of Genotype-Phenotype Relationships in Schizophrenia.

Schizophrenia bulletin Aug 20, 2018
Genetic risk variants for schizophrenia have been linked to many related clinical and biological phenotypes with the hopes of delineating how individual variation across thousands of variants corresponds to the clinical and etiologic heterogeneity wi...
United States Registries Schizophrenia Young Adult Polymorphism, Single Nucleotide Phenotype Endophenotypes Humans Adult Middle Aged Genotype Multifactorial Inheritance Female Cognitive Dysfunction Machine Learning Sweden Male
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