AIMC Topic: Quantitative Trait Loci

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Genomics-assisted breeding for designing salinity-smart future crops.

Plant biotechnology journal Aug 1, 2025
Climate change induces many abiotic stresses, including soil salinity, significantly challenging global agriculture. Salinity stress tolerance (SST) is a complex trait, both physiologically and genetically, and is conferred at various levels of plant...
Genomics Crops, Agricultural Salinity Genome, Plant Plant Breeding Quantitative Trait Loci Salt Tolerance
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Environment ensemble models for genomic prediction in common bean (Phaseolus vulgaris L.).

The plant genome Jun 1, 2025
For important food crops such as the common bean (Phaseolus vulgaris, L.), global demand continues to outpace the rate of genetic gain for quantitative traits. In this study, we leveraged the multi-environment trial (MET) dataset from the cooperative...
Genomics Quantitative Trait Loci Phenotype Polymorphism, Single Nucleotide Gene-Environment Interaction Models, Genetic Genotype Plant Breeding Phaseolus Genome, Plant
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Integration of machine learning and genome-wide association study to explore the genomic prediction accuracy of agronomic trait in oats (Avena sativa L.).

The plant genome Mar 1, 2025
Machine learning (ML) has garnered significant attention for its potential to enhance the accuracy of genomic predictions (GPs) in various economic crops with the use of complete genomic information. Genome-wide association studies (GWAS) are widely ...
Genomics Polymorphism, Single Nucleotide Crops, Agricultural Machine Learning Phenotype Genome-Wide Association Study Plant Breeding Avena Genome, Plant Quantitative Trait Loci
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Assessing the performance of generative artificial intelligence in retrieving information against manually curated genetic and genomic data.

Database : the journal of biological databases and curation Feb 17, 2025
Curated resources at centralized repositories provide high-value service to users by enhancing data veracity. Curation, however, comes with a cost, as it requires dedicated time and effort from personnel with deep domain knowledge. In this paper, we ...
Quantitative Trait Loci Databases, Genetic Triticum Data Mining Artificial Intelligence Hordeum Genomics Humans Data Curation Generative Artificial Intelligence Genome, Plant
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Deep learning-based classifier for carcinoma of unknown primary using methylation quantitative trait loci.

Journal of neuropathology and experimental neurology Feb 1, 2025
Cancer of unknown primary (CUP) constitutes between 2% and 5% of human malignancies and is among the most common causes of cancer death in the United States. Brain metastases are often the first clinical presentation of CUP; despite extensive patholo...
Male Middle Aged Deep Learning DNA Methylation Quantitative Trait Loci Retrospective Studies Neoplasms, Unknown Primary Female Aged Humans
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scTWAS Atlas: an integrative knowledgebase of single-cell transcriptome-wide association studies.

Nucleic acids research Jan 6, 2025
Single-cell transcriptome-wide association studies (scTWAS) is a new method for conducting TWAS analysis at the cellular level to identify gene-trait associations with higher precision. This approach helps overcome the challenge of interpreting cell-...
Gene Expression Profiling Transcriptome Genome-Wide Association Study Single-Cell Analysis Gene Regulatory Networks Databases, Genetic Humans Software Knowledge Bases Quantitative Trait Loci
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Leveraging molecular-QTL co-association to predict novel disease-associated genetic loci using a graph convolutional neural network.

PloS one Jan 1, 2025
Genome-wide association studies (GWAS) have successfully uncovered numerous associations between genetic variants and disease traits to date. Yet, identifying significantly associated loci remains a considerable challenge due to the concomitant multi...
Humans Neural Networks, Computer Quantitative Trait Loci Polymorphism, Single Nucleotide Convolutional Neural Networks DNA Methylation Genome-Wide Association Study CpG Islands Genetic Predisposition to Disease
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Sub-sampling graph neural networks for genomic prediction of quantitative phenotypes.

G3 (Bethesda, Md.) Nov 6, 2024
In genomics, use of deep learning (DL) is rapidly growing and DL has successfully demonstrated its ability to uncover complex relationships in large biological and biomedical data sets. With the development of high-throughput sequencing techniques, g...
Neural Networks, Computer Quantitative Trait Loci Genome-Wide Association Study Models, Genetic Algorithms Genomics Triticum Phenotype Polymorphism, Single Nucleotide Animals
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DeLIVR: a deep learning approach to IV regression for testing nonlinear causal effects in transcriptome-wide association studies.

Biostatistics (Oxford, England) Apr 15, 2024
Transcriptome-wide association studies (TWAS) have been increasingly applied to identify (putative) causal genes for complex traits and diseases. TWAS can be regarded as a two-sample two-stage least squares method for instrumental variable (IV) regre...
Cholesterol Quantitative Trait Loci Humans Genome-Wide Association Study Phenotype Genetic Predisposition to Disease Transcriptome Polymorphism, Single Nucleotide Deep Learning
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DeepPerVar: a multi-modal deep learning framework for functional interpretation of genetic variants in personal genome.

Bioinformatics (Oxford, England) Dec 13, 2022
MOTIVATION: Understanding the functional consequence of genetic variants, especially the non-coding ones, is important but particularly challenging. Genome-wide association studies (GWAS) or quantitative trait locus analyses may be subject to limited...
Quantitative Trait Loci Genome-Wide Association Study Humans Linkage Disequilibrium Genomics Deep Learning Polymorphism, Single Nucleotide
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