AIMC Topic: Polymorphism, Single Nucleotide
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Effects of using deep learning to predict the geographic origin of barley genebank accessions on genome-environment association studies.
TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik
Aug 12, 2025
Genome-environment association (GEA) is an approach for identifying adaptive loci by combining genetic variation with environmental parameters, offering potential for improving crop resilience. However, its application to genebank accessions is limit...
Integrated phenotypic analysis, predictive modeling, and identification of novel trait-associated loci in a diverse Theobroma cacao collection.
BMC plant biology
Aug 9, 2025
BACKGROUND: Cacao (Theobroma cacao L.) breeding and improvement rely on understanding germplasm diversity and trait architecture. This study characterized a cacao collection (173 accessions) evaluated in Puerto Rico, examining phenotypic diversity, t...
Whole genome resequencing reveals genetic diversity, population structure, and selection signatures in local duck breeds.
BMC genomics
Aug 8, 2025
BACKGROUND: Shandong's local duck breeds are renowned for their outstanding egg-laying performance and are regarded as valuable assets within China's waterfowl germplasm. Understanding the genetic characteristics of these populations, along with moni...
AdaptiveGS: an explainable genomic selection framework based on adaptive stacking ensemble machine learning.
TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik
Aug 7, 2025
We developed an adaptive and unified stacking genomic selection framework and designed a model interpretation strategy to identify the candidate significant SNPs of target traits. Genomic selection (GS) is an important technique in modern molecular b...
Machine learning in Alzheimer's disease genetics.
Nature communications
Jul 22, 2025
Traditional statistical approaches have advanced our understanding of the genetics of complex diseases, yet are limited to linear additive models. Here we applied machine learning (ML) to genome-wide data from 41,686 individuals in the largest Europe...
Developing a machine-learning model to enable treatment selection for neoadjuvant chemotherapy for esophageal cancer.
Scientific reports
Jul 15, 2025
Although neoadjuvant chemotherapy with docetaxel + cisplatin + 5-fluorouracil (CF) has been the standard treatment for stage II and III esophageal cancers, it is associated with severe adverse events caused by docetaxel. Consequently, this study aime...
Machine learning-based prediction of antimicrobial resistance and identification of AMR-related SNPs in Mycobacterium tuberculosis.
BMC genomic data
Jul 12, 2025
BACKGROUND: Mycobacterium tuberculosis (MTB) is a human-specific pathogen that primarily infects humans, causing tuberculosis (TB). Antimicrobial resistance (AMR) in MTB presents a formidable challenge to global health. The employment of machine lear...
Machine learning using genotype and gene-expression data identifies alterations of genes involved in infection susceptibility, antigen presentation and cytokine signalling as key contributors to JIA risk prediction.
RMD open
Jul 9, 2025
BACKGROUND: Previous genome-wide association studies (GWAS) have identified numerous genetic loci associated with juvenile idiopathic arthritis (JIA). However, the functional impact of these variants-particularly on tissue-specific gene expression-an...
Multi-omics analysis identifies SNP-associated immune-related signatures by integrating Mendelian randomization and machine learning in hepatocellular carcinoma.
Scientific reports
Jul 4, 2025
Hepatocellular carcinoma (HCC) is a leading cause of cancer-related death globally, characterized by high morbidity and poor prognosis. The complex molecular and immune landscape of HCC makes accurate patient stratification and personalized treatment...
Neur-Ally: a deep learning model for regulatory variant prediction based on genomic and epigenomic features in brain and its validation in certain neurological disorders.
NAR genomics and bioinformatics
Jun 13, 2025
Large-scale quantitative studies have identified significant genetic associations for various neurological disorders. Expression quantitative trait locus (eQTL) studies have shown the effect of single-nucleotide polymorphisms (SNPs) on the differenti...
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