AIMC Topic: Polymorphism, Single Nucleotide

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Genome-wide association data classification and SNPs selection using two-stage quality-based Random Forests.

BMC genomics
BACKGROUND: Single-nucleotide polymorphisms (SNPs) selection and identification are the most important tasks in Genome-wide association data analysis. The problem is difficult because genome-wide association data is very high dimensional and a large ...

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...

Kernel methods for large-scale genomic data analysis.

Briefings in bioinformatics
Machine learning, particularly kernel methods, has been demonstrated as a promising new tool to tackle the challenges imposed by today's explosive data growth in genomics. They provide a practical and principled approach to learning how a large numbe...

Dimensionality reduction of genetic data using contrastive learning.

Genetics
We introduce a framework for using contrastive learning for dimensionality reduction on genetic datasets to create principal component analysis (PCA)-like population visualizations. Contrastive learning is a self-supervised deep learning method that ...

Assessment for antibiotic resistance in : A practical and interpretable machine learning model based on genome-wide genetic variation.

Virulence
() antibiotic resistance poses a global health threat. Accurate identification of antibiotic resistant strains is essential for the control of infection. In the present study, our goal is to leverage the whole-genome data of to develop practical an...

Genetic Control of tRNA-Derived Fragments Contributes to Cancer Risk.

Cancer research
UNLABELLED: tRNA-derived fragments (tRF) are a class of small noncoding RNAs that have exhibited several functions in cancer. Recent studies have shown that mutations in tRNA genes can lead to global changes in tRF expression levels and may affect tR...

Mapping QTLs for PHS resistance and development of a deep learning model to measure PHS rate in japonica rice.

The plant genome
Rice (Oryza sativa L.) is a staple food for more than half of the global population. Preharvest sprouting (PHS), which reduces yield and grain quality, presents a major challenge for rice production. The development of PHS-resistant varieties is a ma...

Machine learning-driven GWAS uncovers novel candidate genes for resistance to frosty pod rot and witches' broom disease in cacao.

The plant genome
Cacao (Theobroma cacao), the source of chocolate, is threatened by devastating diseases like frosty pod rot (FPR) and witches' broom disease (WBD), impacting global production and farmer livelihoods. Here, we employ a machine learning-driven genome-w...

The Role of HbA1c in Parkinson's Disease: An Integrative Analysis by Single-Cell, Bulk Transcriptome and Mendelian Randomization.

Molecular neurobiology
Decreased glucose tolerance is recognized as a factor associated with Parkinson's disease (PD) progression, yet the relationship between HbA1c and PD prognosis remains insufficiently explored. Using data from the Integrated Epidemiological Unit (IEU)...