AIMC Topic: Genome-Wide Association Study

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Identification of New Fungal Peroxisomal Matrix Proteins and Revision of the PTS1 Consensus.

Traffic (Copenhagen, Denmark)
The peroxisomal targeting signal type 1 (PTS1) is a seemingly simple peptide sequence at the C-terminal end of most peroxisomal matrix proteins. PTS1 can be described as a tripeptide with the consensus motif [S/A/C] [K/R/H] L. However, this descripti...

Use of a Novel Nonparametric Version of DEPTH to Identify Genomic Regions Associated with Prostate Cancer Risk.

Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology
BACKGROUND: We have developed a genome-wide association study analysis method called DEPTH (DEPendency of association on the number of Top Hits) to identify genomic regions potentially associated with disease by considering overlapping groups of cont...

Random Bits Forest: a Strong Classifier/Regressor for Big Data.

Scientific reports
Efficiency, memory consumption, and robustness are common problems with many popular methods for data analysis. As a solution, we present Random Bits Forest (RBF), a classification and regression algorithm that integrates neural networks (for depth),...

A knowledge-based approach for predicting gene-disease associations.

Bioinformatics (Oxford, England)
MOTIVATION: Recent advances of next-generation sequence technologies have made it possible to rapidly and inexpensively identify gene variations. Knowing the disease association of these gene variations is important for early intervention to treat de...

DanQ: a hybrid convolutional and recurrent deep neural network for quantifying the function of DNA sequences.

Nucleic acids research
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...

Learning Predictive Interactions Using Information Gain and Bayesian Network Scoring.

PloS one
BACKGROUND: The problems of correlation and classification are long-standing in the fields of statistics and machine learning, and techniques have been developed to address these problems. We are now in the era of high-dimensional data, which is data...

Powerful Tests for Multi-Marker Association Analysis Using Ensemble Learning.

PloS one
Multi-marker approaches have received a lot of attention recently in genome wide association studies and can enhance power to detect new associations under certain conditions. Gene-, gene-set- and pathway-based association tests are increasingly bein...

Genome-Wide Detection and Analysis of Multifunctional Genes.

PLoS computational biology
Many genes can play a role in multiple biological processes or molecular functions. Identifying multifunctional genes at the genome-wide level and studying their properties can shed light upon the complexity of molecular events that underpin cellular...