AIMC Topic: Quantitative Trait Loci
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Deep learning enables genetic analysis of the human thoracic aorta.
Nature genetics
Nov 26, 2021
Enlargement or aneurysm of the aorta predisposes to dissection, an important cause of sudden death. We trained a deep learning model to evaluate the dimensions of the ascending and descending thoracic aorta in 4.6 million cardiac magnetic resonance i...
Effective gene expression prediction from sequence by integrating long-range interactions.
Nature methods
Oct 4, 2021
How noncoding DNA determines gene expression in different cell types is a major unsolved problem, and critical downstream applications in human genetics depend on improved solutions. Here, we report substantially improved gene expression prediction a...
Advances in for Abiotic Stress Resilience: From 'Omics' to Artificial Intelligence.
International journal of molecular sciences
Sep 29, 2021
Legumes are a better source of proteins and are richer in diverse micronutrients over the nutritional profile of widely consumed cereals. However, when exposed to a diverse range of abiotic stresses, their overall productivity and quality are hugely ...
Prioritization of disease genes from GWAS using ensemble-based positive-unlabeled learning.
European journal of human genetics : EJHG
Jul 19, 2021
A primary challenge in understanding disease biology from genome-wide association studies (GWAS) arises from the inability to directly implicate causal genes from association data. Integration of multiple-omics data sources potentially provides impor...
Leveraging supervised learning for functionally informed fine-mapping of cis-eQTLs identifies an additional 20,913 putative causal eQTLs.
Nature communications
Jun 7, 2021
The large majority of variants identified by GWAS are non-coding, motivating detailed characterization of the function of non-coding variants. Experimental methods to assess variants' effect on gene expressions in native chromatin context via direct ...
Machine learning approaches reveal genomic regions associated with sugarcane brown rust resistance.
Scientific reports
Nov 18, 2020
Sugarcane is an economically important crop, but its genomic complexity has hindered advances in molecular approaches for genetic breeding. New cultivars are released based on the identification of interesting traits, and for sugarcane, brown rust re...
How Machine Learning Methods Helped Find Putative Rye Wax Genes Among GBS Data.
International journal of molecular sciences
Oct 12, 2020
The standard approach to genetic mapping was supplemented by machine learning (ML) to establish the location of the rye gene associated with epicuticular wax formation (glaucous phenotype). Over 180 plants of the biparental F population were genotype...
lncRNAKB, a knowledgebase of tissue-specific functional annotation and trait association of long noncoding RNA.
Scientific data
Oct 5, 2020
Long non-coding RNA Knowledgebase (lncRNAKB) is an integrated resource for exploring lncRNA biology in the context of tissue-specificity and disease association. A systematic integration of annotations from six independent databases resulted in 77,19...
Sensitivity analysis based on the random forest machine learning algorithm identifies candidate genes for regulation of innate and adaptive immune response of chicken.
Poultry science
Sep 12, 2020
Two categories of immune responses-innate and adaptive immunity-have both polygenic backgrounds and a significant environmental component. The goal of the reported study was to define candidate genes and mutations for the immune traits of interest in...
An enhanced machine learning tool for cis-eQTL mapping with regularization and confounder adjustments.
Genetic epidemiology
Jul 22, 2020
Many expression quantitative trait loci (eQTL) studies have been conducted to investigate the biological effects of variants in gene regulation. However, these eQTL studies may suffer from low or moderate statistical power and overly conservative fal...
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