AIMC Topic: Genome-Wide Association Study

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Aber-OWL: a framework for ontology-based data access in biology.

BMC bioinformatics Jan 28, 2015
BACKGROUND: Many ontologies have been developed in biology and these ontologies increasingly contain large volumes of formalized knowledge commonly expressed in the Web Ontology Language (OWL). Computational access to the knowledge contained within t...
Models, Genetic Internet Semantics Apoptosis Regulatory Proteins Heart Septal Defects, Ventricular Biological Ontologies Knowledge Language Genome-Wide Association Study Computational Biology Software Phenotype Databases, Factual Humans
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Genome-wide association data classification and SNPs selection using two-stage quality-based Random Forests.

BMC genomics Jan 21, 2015
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 ...
Models, Genetic Algorithms Parkinson Disease Humans Alzheimer Disease Reproducibility of Results Machine Learning Genetic Predisposition to Disease Genome-Wide Association Study Polymorphism, Single Nucleotide Computational Biology
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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...
Muscular Atrophy, Spinal Exons Genetic Code MutL Protein Homolog 1 RNA Splice Sites Introns RNA Splicing Mutation, Missense Child Development Disorders, Pervasive Quantitative Trait Loci Colorectal Neoplasms, Hereditary Nonpolyposis Models, Genetic Genetic Variation Nuclear Proteins Genome-Wide Association Study Molecular Sequence Annotation DNA Humans Adaptor Proteins, Signal Transducing Polymorphism, Single Nucleotide Genetic Markers Artificial Intelligence RNA-Binding Proteins Computer Simulation
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Kernel methods for large-scale genomic data analysis.

Briefings in bioinformatics Jul 22, 2014
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...
Computational Biology Logistic Models Support Vector Machine Genome-Wide Association Study Genomics Polymorphism, Single Nucleotide Models, Statistical Data Interpretation, Statistical Humans Machine Learning
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Genome-wide association study revealed candidate genes associated with egg-laying time traits in layer chicken.

Poultry science Jul 1, 2025
In modern intensive caged laying hen production, variations in egg-laying time (ELT) among layers often increase the workload for egg collection, thereby raising the costs of labor or power and reducing overall efficiency. For management purpose, ear...
Female Polymorphism, Single Nucleotide Animals Chickens Genome-Wide Association Study Reproduction
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From classical approaches to artificial intelligence, old and new tools for PDAC risk stratification and prediction.

Seminars in cancer biology Jul 1, 2025
Pancreatic ductal adenocarcinoma (PDAC) is recognized as one of the most lethal malignancies, characterized by late-stage diagnosis and limited therapeutic options. Risk stratification has traditionally been performed using epidemiological studies an...
Artificial Intelligence Machine Learning Risk Factors Risk Assessment Humans Carcinoma, Pancreatic Ductal Genome-Wide Association Study Genetic Predisposition to Disease Pancreatic Neoplasms
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The predictive power of profiling the DNA methylome in human health and disease.

Epigenomics Jun 1, 2025
Early and accurate diagnosis significantly improves the chances of disease survival. DNA methylation (5mC), the major DNA modification in the human genome, is now recognized as a biomarker of immense clinical potential. This is due to its ability to ...
Epigenome Humans Machine Learning Biomarkers Epigenomics Genome-Wide Association Study DNA Methylation Epigenesis, Genetic
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Meet the author: Hae Kyung Im.

Cell genomics May 14, 2025
Hae Kyung Im's research group focuses on quantitative computational and statistical methods to tackle genomic data analysis and provides methods to translate the vast amount of genomic data for health research. In collaboration with Mengjie Chen's gr...
Deep Learning Humans Genomics Genome-Wide Association Study Transcriptome Computational Biology
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scPrediXcan integrates deep learning methods and single-cell data into a cell-type-specific transcriptome-wide association study framework.

Cell genomics May 14, 2025
Transcriptome-wide association studies (TWASs) help identify disease-causing genes but often fail to pinpoint disease mechanisms at the cellular level because of the limited sample sizes and sparsity of cell-type-specific expression data. Here, we pr...
Diabetes Mellitus, Type 2 Single-Cell Analysis Epigenesis, Genetic Transcriptome Deep Learning Genome-Wide Association Study Lupus Erythematosus, Systemic Humans Gene Expression Profiling
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Identification of biomarkers for endometriosis based on summary-data-based Mendelian randomization and machine learning.

Medicine Apr 4, 2025
Endometriosis (EM) significantly impacts the quality of life, and its diagnosis currently relies on surgery, which carries risks and may miss early lesions. Noninvasive biomarkers are urgently needed for early diagnosis and personalized treatment. Th...
Biomarkers Female Genome-Wide Association Study Humans Mendelian Randomization Analysis Machine Learning Endometriosis
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