AIMC Topic: Models, Genetic

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Interaction between maintenance variables of medical ultrasound scanners through multifactor dimensionality reduction.

Expert review of medical devices
BACKGROUND: Proper maintenance of electro-medical devices is crucial for the quality of care to patients and the economic performance of healthcare organizations. This research aims to identify the interaction between Ultrasound scanners (US) mainten...

deepGBLUP: joint deep learning networks and GBLUP framework for accurate genomic prediction of complex traits in Korean native cattle.

Genetics, selection, evolution : GSE
BACKGROUND: Genomic prediction has become widespread as a valuable tool to estimate genetic merit in animal and plant breeding. Here we develop a novel genomic prediction algorithm, called deepGBLUP, which integrates deep learning networks and a geno...

DeepCGP: A Deep Learning Method to Compress Genome-Wide Polymorphisms for Predicting Phenotype of Rice.

IEEE/ACM transactions on computational biology and bioinformatics
Genomic selection (GS) is expected to accelerate plant and animal breeding. During the last decade, genome-wide polymorphism data have increased, which has raised concerns about storage cost and computational time. Several individual studies have att...

Gene-environment interaction analysis via deep learning.

Genetic epidemiology
Gene-environment (G-E) interaction analysis plays an important role in studying complex diseases. Extensive methodological research has been conducted on G-E interaction analysis, and the existing methods are mostly based on regression techniques. In...

Deep learning identified genetic variants for COVID-19-related mortality among 28,097 affected cases in UK Biobank.

Genetic epidemiology
Analysis of host genetic components provides insights into the susceptibility and response to viral infection such as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which causes coronavirus disease 2019 (COVID-19). To reveal genetic de...

Quartet Based Gene Tree Imputation Using Deep Learning Improves Phylogenomic Analyses Despite Missing Data.

Journal of computational biology : a journal of computational molecular cell biology
Species tree estimation is frequently based on phylogenomic approaches that use multiple genes from throughout the genome. However, for a combination of reasons (ranging from sampling biases to more biological causes, as in gene birth and loss), gene...

Experimental exploration of a ribozyme neutral network using evolutionary algorithm and deep learning.

Nature communications
A neutral network connects all genotypes with equivalent phenotypes in a fitness landscape and plays an important role in the mutational robustness and evolvability of biomolecules. In contrast to earlier theoretical works, evidence of large neutral ...

Latent space of a small genetic network: Geometry of dynamics and information.

Proceedings of the National Academy of Sciences of the United States of America
The high-dimensional character of most biological systems presents genuine challenges for modeling and prediction. Here we propose a neural network-based approach for dimensionality reduction and analysis of biological gene expression data, using, as...

Robots as models of evolving systems.

Proceedings of the National Academy of Sciences of the United States of America
Experimental robobiological physics can bring insights into biological evolution. We present a development of hybrid analog/digital autonomous robots with mutable diploid dominant/recessive 6-byte genomes. The robots are capable of death, rebirth, an...

Construction of genetic classification model for coronary atherosclerosis heart disease using three machine learning methods.

BMC cardiovascular disorders
BACKGROUND: Although the diagnostic method for coronary atherosclerosis heart disease (CAD) is constantly innovated, CAD in the early stage is still missed diagnosis for the absence of any symptoms. The gene expression levels varied during disease de...