AIMC Topic: Phenotype

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Identification of Type 2 Diabetes Risk Factors Using Phenotypes Consisting of Anthropometry and Triglycerides based on Machine Learning.

IEEE journal of biomedical and health informatics
The hypertriglyceridemic waist (HW) phenotype is strongly associated with type 2 diabetes; however, to date, no study has assessed the predictive power of phenotypes based on individual anthropometric measurements and triglyceride (TG) levels. The ai...

Aber-OWL: a framework for ontology-based data access in biology.

BMC bioinformatics
BACKGROUND: Many ontologies have been developed in biology and these ontologies increasingly contain large volumes of formalized knowledge commonly expressed in the Web Ontology Language (OWL). Computational access to the knowledge contained within t...

UGMDR: a unified conceptual framework for detection of multifactor interactions underlying complex traits.

Heredity
Biological outcomes are governed by multiple genetic and environmental factors that act in concert. Determining multifactor interactions is the primary topic of interest in recent genetics studies but presents enormous statistical and mathematical ch...

Bridging scales in cancer progression: mapping genotype to phenotype using neural networks.

Seminars in cancer biology
In this review we summarise our recent efforts in trying to understand the role of heterogeneity in cancer progression by using neural networks to characterise different aspects of the mapping from a cancer cells genotype and environment to its pheno...

Genomic prediction of feed efficiency in boars by deep learning.

G3 (Bethesda, Md.)
Pork is the most widely consumed meat globally, and the industry has achieved substantial genetic advancements for several traits using genomic selection. However, traditional linear genomic prediction models may be inadequate for predicting complex ...

Dissecting Shared Genetic Architecture of Thoracic Aortic Aneurysm and Aortic Related Traits and Identifying SplA/Ryanodine Receptor Domain and SOCS Box Containing 1 Involved in Smooth Muscle Phenotype Switching and Cell Senescence Through Alternative Splicing.

FASEB journal : official publication of the Federation of American Societies for Experimental Biology
Machine learning was employed to annotate images of the thoracic aorta, resulting in the identification of additional thoracic-related targets. However, genetic evaluation of the associations among thoracic aortic traits and their shared genes is lac...

Exploring the unique characteristics of genes with dual autosomal dominant and recessive inheritance: mechanisms, phenotypes and candidate identification.

Journal of medical genetics
BACKGROUND: Autosomal dominant (AD) inheritance often arises through haploinsufficiency, dominant-negative or gain of function (GoF) effects, while autosomal recessive (AR) inheritance generally results from partial or complete loss of function (LoF)...

Genomic and hyperspectral imaging-based prediction blending enables selection for reduced deoxynivalenol content in wheat grains.

G3 (Bethesda, Md.)
Breeding for low deoxynivalenol (DON) mycotoxin content in wheat is challenging due to the complexity of the trait and phenotyping limitations. Since phenomic prediction relies on nonadditive effects and genomic prediction on additive effects, their ...