AIMC Topic: Polymorphism, Single Nucleotide
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Deep learning versus parametric and ensemble methods for genomic prediction of complex phenotypes.
Genetics, selection, evolution : GSE
Feb 24, 2020
BACKGROUND: Transforming large amounts of genomic data into valuable knowledge for predicting complex traits has been an important challenge for animal and plant breeders. Prediction of complex traits has not escaped the current excitement on machine...
A genome-wide multiphenotypic association analysis identified candidate genes and gene ontology shared by four common risky behaviors.
Aging
Feb 22, 2020
BACKGROUND: Risky behaviors can lead to huge economic and health losses. However, limited efforts are paid to explore the genetic mechanisms of risky behaviors.
Multimodal Data Analysis of Alzheimer's Disease Based on Clustering Evolutionary Random Forest.
IEEE journal of biomedical and health informatics
Feb 11, 2020
Alzheimer's disease (AD) has become a severe medical challenge. Advances in technologies produced high-dimensional data of different modalities including functional magnetic resonance imaging (fMRI) and single nucleotide polymorphism (SNP). Understan...
Improving genomic prediction accuracy for meat tenderness in Nellore cattle using artificial neural networks.
Journal of animal breeding and genetics = Zeitschrift fur Tierzuchtung und Zuchtungsbiologie
Feb 5, 2020
The goal of this study was to compare the predictive performance of artificial neural networks (ANNs) with Bayesian ridge regression, Bayesian Lasso, Bayes A, Bayes B and Bayes Cπ in estimating genomic breeding values for meat tenderness in Nellore c...
ERAP1 polymorphisms interactions and their association with Behçet's disease susceptibly: Application of Model-Based Multifactor Dimension Reduction Algorithm (MB-MDR).
PloS one
Feb 5, 2020
BACKGROUND: Behçet's disease (BD) is a chronic multi-systemic vasculitis with a considerable prevalence in Asian countries. There are many genes associated with a higher risk of developing BD, one of which is endoplasmic reticulum aminopeptidase-1 (E...
Polymorphism, Single Nucleotide
Genetic Association Studies
Models, Genetic
Entropy
Multifactor Dimensionality Reduction
Iran
Gene Frequency
Gene Regulatory Networks
Aminopeptidases
Humans
Minor Histocompatibility Antigens
Genetic Predisposition to Disease
Behcet Syndrome
Algorithms
Female
Adult
Male
DeepWAS: Multivariate genotype-phenotype associations by directly integrating regulatory information using deep learning.
PLoS computational biology
Feb 3, 2020
Genome-wide association studies (GWAS) identify genetic variants associated with traits or diseases. GWAS never directly link variants to regulatory mechanisms. Instead, the functional annotation of variants is typically inferred by post hoc analyses...
Deep learning models predict regulatory variants in pancreatic islets and refine type 2 diabetes association signals.
eLife
Jan 27, 2020
Genome-wide association analyses have uncovered multiple genomic regions associated with T2D, but identification of the causal variants at these remains a challenge. There is growing interest in the potential of deep learning models - which predict e...
Single-cell ATAC-Seq in human pancreatic islets and deep learning upscaling of rare cells reveals cell-specific type 2 diabetes regulatory signatures.
Molecular metabolism
Dec 20, 2019
OBJECTIVE: Type 2 diabetes (T2D) is a complex disease characterized by pancreatic islet dysfunction, insulin resistance, and disruption of blood glucose levels. Genome-wide association studies (GWAS) have identified > 400 independent signals that enc...
Machine learning approach to single nucleotide polymorphism-based asthma prediction.
PloS one
Dec 4, 2019
Machine learning (ML) is poised as a transformational approach uniquely positioned to discover the hidden biological interactions for better prediction and diagnosis of complex diseases. In this work, we integrated ML-based models for feature selecti...
TSLRF: Two-Stage Algorithm Based on Least Angle Regression and Random Forest in genome-wide association studies.
Scientific reports
Dec 2, 2019
One of the most important tasks in genome-wide association analysis (GWAS) is the detection of single-nucleotide polymorphisms (SNPs) which are related to target traits. With the development of sequencing technology, traditional statistical methods a...
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