AIMC Topic: Genome-Wide Association Study

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Revealing Alzheimer's disease genes spectrum in the whole-genome by machine learning.

BMC neurology Jan 10, 2018
BACKGROUND: Alzheimer's disease (AD) is an important, progressive neurodegenerative disease, with a complex genetic architecture. A key goal of biomedical research is to seek out disease risk genes, and to elucidate the function of these risk genes i...
Humans ROC Curve Area Under Curve Alzheimer Disease Machine Learning Sensitivity and Specificity Genome-Wide Association Study
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Stable solution to l -based robust inductive matrix completion and its application in linking long noncoding RNAs to human diseases.

BMC medical genomics Dec 28, 2017
BACKGROUNDS: A large number of long intergenic non-coding RNAs (lincRNAs) are linked to a broad spectrum of human diseases. The disease association with many other lincRNAs still remain as puzzle. Validation of such links between the two entities thr...
Disease Humans Genome-Wide Association Study Algorithms Computational Biology RNA, Long Noncoding
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Imbalance-Aware Machine Learning for Predicting Rare and Common Disease-Associated Non-Coding Variants.

Scientific reports Jun 7, 2017
Disease and trait-associated variants represent a tiny minority of all known genetic variation, and therefore there is necessarily an imbalance between the small set of available disease-associated and the much larger set of non-deleterious genomic v...
Genetic Variation RNA, Untranslated Genetic Predisposition to Disease Humans Models, Genetic Machine Learning Mutation Software Algorithms Reproducibility of Results Genome-Wide Association Study
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Multiple Trait Covariance Association Test Identifies Gene Ontology Categories Associated with Chill Coma Recovery Time in Drosophila melanogaster.

Scientific reports May 25, 2017
The genomic best linear unbiased prediction (GBLUP) model has proven to be useful for prediction of complex traits as well as estimation of population genetic parameters. Improved inference and prediction accuracy of GBLUP may be achieved by identify...
Algorithms Models, Statistical Models, Biological Genetic Variation Computer Simulation Animals Genome-Wide Association Study Quantitative Trait, Heritable Drosophila melanogaster Inheritance Patterns Gene Ontology Coma Quantitative Trait Loci
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A large-scale benchmark of gene prioritization methods.

Scientific reports Apr 21, 2017
In order to maximize the use of results from high-throughput experimental studies, e.g. GWAS, for identification and diagnostics of new disease-associated genes, it is important to have properly analyzed and benchmarked gene prioritization tools. Whi...
Computational Biology Gene Ontology Algorithms Genome-Wide Association Study Gene Regulatory Networks Software
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Computer vision and machine learning for robust phenotyping in genome-wide studies.

Scientific reports Mar 8, 2017
Traditional evaluation of crop biotic and abiotic stresses are time-consuming and labor-intensive limiting the ability to dissect the genetic basis of quantitative traits. A machine learning (ML)-enabled image-phenotyping pipeline for the genetic stu...
Genome-Wide Association Study Image Processing, Computer-Assisted Stress, Physiological Glycine max Quantitative Trait Loci Artificial Intelligence Machine Learning Phenotype
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Computational methods using genome-wide association studies to predict radiotherapy complications and to identify correlative molecular processes.

Scientific reports Feb 24, 2017
The biological cause of clinically observed variability of normal tissue damage following radiotherapy is poorly understood. We hypothesized that machine/statistical learning methods using single nucleotide polymorphism (SNP)-based genome-wide associ...
Middle Aged Genome-Wide Association Study Cohort Studies Polymorphism, Single Nucleotide Gene Expression Regulation, Neoplastic Radiation Tolerance Signal Transduction Gamma Rays Aged Humans Biomarkers, Tumor Machine Learning Rectum Male Prognosis Hemorrhage Neoplasm Proteins Prostatic Neoplasms Erectile Dysfunction Prostate
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Multi-Instance Metric Transfer Learning for Genome-Wide Protein Function Prediction.

Scientific reports Feb 6, 2017
Multi-Instance (MI) learning has been proven to be effective for the genome-wide protein function prediction problems where each training example is associated with multiple instances. Many studies in this literature attempted to find an appropriate ...
Proteins Genome Machine Learning Algorithms Genome-Wide Association Study Genomics
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Bosco: Boosting Corrections for Genome-Wide Association Studies With Imbalanced Samples.

IEEE transactions on nanobioscience Jan 27, 2017
In genome-wide association studies (GWAS), the acquired sequential data may exhibit imbalance structure: abundant control vs. limited case samples. Such sample imbalance issue is particularly serious when investigating rare diseases or common disease...
Humans Machine Learning Genome-Wide Association Study Software Databases, Factual Computational Biology Computer Simulation Stomach Neoplasms
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Robust differential expression analysis by learning discriminant boundary in multi-dimensional space of statistical attributes.

BMC bioinformatics Dec 19, 2016
BACKGROUND: Performing statistical tests is an important step in analyzing genome-wide datasets for detecting genomic features differentially expressed between conditions. Each type of statistical test has its own advantages in characterizing certain...
Models, Statistical Discriminant Analysis Normal Distribution Humans Algorithms Machine Learning Gene Expression Profiling Genome-Wide Association Study
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