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Genotype

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Association of and gene polymorphisms and ERAP2 protein with the susceptibility and severity of rheumatoid arthritis in the Ukrainian population.

Frontiers in immunology
INTRODUCTION: Rheumatoid arthritis (RA) is a long-term autoimmune disorder that primarily affects joints. Although RA is chiefly associated with HLA class II, nevertheless some HLA class I associations have also been observed. These molecules present...

Noninvasive fetal genotyping using deep neural networks.

Briefings in bioinformatics
Circulating cell-free DNA (cfDNA) is a powerful diagnostics tool that is widely studied in the context of liquid biopsy in oncology and other fields. In obstetrics, maternal plasma cfDNA have already proven its utility, enabling noninvasive prenatal ...

Learning genotype-phenotype associations from gaps in multi-species sequence alignments.

Briefings in bioinformatics
Understanding the genetic basis of phenotypic variation is fundamental to biology. Here we introduce GAP, a novel machine learning framework for predicting binary phenotypes from gaps in multi-species sequence alignments. GAP employs a neural network...

Comparing statistical learning methods for complex trait prediction from gene expression.

PloS one
Accurate prediction of complex traits is an important task in quantitative genetics. Genotypes have been used for trait prediction using a variety of methods such as mixed models, Bayesian methods, penalized regression methods, dimension reduction me...

Multimodal learning for mapping genotype-phenotype dynamics.

Nature computational science
How complex phenotypes emerge from intricate gene expression patterns is a fundamental question in biology. Integrating high-content genotyping approaches such as single-cell RNA sequencing and advanced learning methods such as language models offers...

Analysis of TEM micrographs with deep learning reveals APOE genotype-specific associations between HDL particle diameter and Alzheimer's dementia.

Cell reports methods
High-density lipoprotein (HDL) particle diameter distribution is informative in the diagnosis of many conditions, including Alzheimer's disease (AD). However, obtaining an accurate HDL size measurement is challenging. We demonstrated the utility of m...

Tasselyzer, a machine learning method to quantify maize anther exertion, based on PlantCV.

The Plant journal : for cell and molecular biology
Maize anthers emerge from male-only florets, a process that involves complex genetic programming and is affected by environmental factors. Quantifying anther exertion provides a key indicator of male fertility; however, traditional manual scoring met...

Hepatitis C Virus Saint Petersburg Variant Detection With Machine Learning Methods.

Journal of medical virology
Hepatitis C virus infection is a significant global health concern, affecting millions worldwide. Although direct-acting antivirals achieve over 90% success rate, treatment failures still occur, particularly when pan-genotypic DAAs are unavailable, a...

Optimizing chickpea yield prediction under wilt disease through synergistic integration of biophysical and image parameters using machine learning models.

Scientific reports
Crop health assessment and early yield predictions are highly crucial under biotic stress conditions for crop management and market planning by farmers and policy planners. The objective of this study was, therefore, to assess the impact of different...

Leveraging Automated Machine Learning for Environmental Data-Driven Genetic Analysis and Genomic Prediction in Maize Hybrids.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)
Genotype, environment, and genotype-by-environment (G×E) interactions play a critical role in shaping crop phenotypes. Here, a large-scale, multi-environment hybrid maize dataset is used to construct and validate an automated machine learning framewo...