AIMC Topic: Quantitative Trait Loci
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phenoSeeder - A Robot System for Automated Handling and Phenotyping of Individual Seeds.
Plant physiology
Sep 23, 2016
The enormous diversity of seed traits is an intriguing feature and critical for the overwhelming success of higher plants. In particular, seed mass is generally regarded to be key for seedling development but is mostly approximated by using scanning ...
Genomic Prediction for Quantitative Traits Is Improved by Mapping Variants to Gene Ontology Categories in Drosophila melanogaster.
Genetics
May 27, 2016
Predicting individual quantitative trait phenotypes from high-resolution genomic polymorphism data is important for personalized medicine in humans, plant and animal breeding, and adaptive evolution. However, this is difficult for populations of unre...
DanQ: a hybrid convolutional and recurrent deep neural network for quantifying the function of DNA sequences.
Nucleic acids research
Apr 15, 2016
Modeling the properties and functions of DNA sequences is an important, but challenging task in the broad field of genomics. This task is particularly difficult for non-coding DNA, the vast majority of which is still poorly understood in terms of fun...
Identification of active transcriptional regulatory elements from GRO-seq data.
Nature methods
Mar 23, 2015
Modifications to the global run-on and sequencing (GRO-seq) protocol that enrich for 5'-capped RNAs can be used to reveal active transcriptional regulatory elements (TREs) with high accuracy. Here, we introduce discriminative regulatory-element detec...
RNA splicing. The human splicing code reveals new insights into the genetic determinants of disease.
Science (New York, N.Y.)
Dec 18, 2014
To facilitate precision medicine and whole-genome annotation, we developed a machine-learning technique that scores how strongly genetic variants affect RNA splicing, whose alteration contributes to many diseases. Analysis of more than 650,000 intron...
Child Development Disorders, Pervasive
Nuclear Proteins
Mutation, Missense
Genetic Code
Genome-Wide Association Study
Humans
Quantitative Trait Loci
Genetic Markers
Adaptor Proteins, Signal Transducing
MutL Protein Homolog 1
Colorectal Neoplasms, Hereditary Nonpolyposis
RNA Splicing
DNA
Polymorphism, Single Nucleotide
Muscular Atrophy, Spinal
RNA Splice Sites
Exons
RNA-Binding Proteins
Models, Genetic
Genetic Variation
Molecular Sequence Annotation
Introns
Artificial Intelligence
Computer Simulation
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...
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 ...
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 ...
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...
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-...
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