AIMC Topic: Genotype

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Deep learning-based cross-classifications reveal conserved spatial behaviors within tumor histological images.

Nature communications
Histopathological images are a rich but incompletely explored data type for studying cancer. Manual inspection is time consuming, making it challenging to use for image data mining. Here we show that convolutional neural networks (CNNs) can be system...

Hepatitis C viral load and genotypes among Nigerian subjects with chronic infection and implication for patient management: a retrospective review of data.

The Pan African medical journal
INTRODUCTION: Hepatitis C Virus (HCV) is highly infectious with no currently available vaccine. Prior to treatment, it is recommended to confirm HCV infection with either quantitative or qualitative nucleic acid test. Access to these assays in Nigeri...

Cnngeno: A high-precision deep learning based strategy for the calling of structural variation genotype.

Computational biology and chemistry
Genotype plays a significant role in determining characteristics in an organism and genotype calling has been greatly accelerated by sequencing technologies. Furthermore, most parametric statistical models are unable to effectively call genotype, whi...

Machine learning approaches reveal genomic regions associated with sugarcane brown rust resistance.

Scientific reports
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...

Discrimination of alcohol dependence based on the convolutional neural network.

PloS one
In this paper, a total of 20 sites of single nucleotide polymorphisms (SNPs) on the serotonin 3 receptor A gene (HTR3A) and B gene (HTR3B) are used for feature fusion with age, education and marital status information, and the grid search-support vec...

Application of ensemble learning to genomic selection in chinese simmental beef cattle.

Journal of animal breeding and genetics = Zeitschrift fur Tierzuchtung und Zuchtungsbiologie
Genomic selection (GS) using the whole-genome molecular makers to predict genomic estimated breeding values (GEBVs) is revolutionizing the livestock and plant breeding. Seeking out novel strategies with higher prediction accuracy for GS has been the ...

How Machine Learning Methods Helped Find Putative Rye Wax Genes Among GBS Data.

International journal of molecular sciences
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...

A genotype imputation method for de-identified haplotype reference information by using recurrent neural network.

PLoS computational biology
Genotype imputation estimates the genotypes of unobserved variants using the genotype data of other observed variants based on a collection of haplotypes for thousands of individuals, which is known as a haplotype reference panel. In general, more ac...

Combining mechanistic and machine learning models for predictive engineering and optimization of tryptophan metabolism.

Nature communications
Through advanced mechanistic modeling and the generation of large high-quality datasets, machine learning is becoming an integral part of understanding and engineering living systems. Here we show that mechanistic and machine learning models can be c...

Viral pandemic preparedness: A pluripotent stem cell-based machine-learning platform for simulating SARS-CoV-2 infection to enable drug discovery and repurposing.

Stem cells translational medicine
Infection with the SARS-CoV-2 virus has rapidly become a global pandemic for which we were not prepared. Several clinical trials using previously approved drugs and drug combinations are urgently under way to improve the current situation. A vaccine ...