Journal of bioinformatics and computational biology
Sep 16, 2015
Automated assignment of protein function has received considerable attention in recent years for genome-wide study. With the rapid accumulation of genome sequencing data produced by high-throughput experimental techniques, the process of manually pre...
INTRODUCTION: Pleiotropy describes the genetic effect of a single gene on multiple phenotypic traits. Gene variants directly affect the normal processes of a series of physiological and biochemical reactions, and therefore cause a variety of diseases...
Genome-wide association studies (GWAS) have extensively analyzed single SNP effects on a wide variety of common and complex diseases and found many genetic variants associated with diseases. However, there is still a large portion of the genetic vari...
Genome-wide association studies have revealed a vast amount of common loci associated to human complex diseases. Still, a large proportion of heritability remains unexplained. The extent to which rare genetic variants (RVs) are able to explain a rele...
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...
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...
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 ...
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...
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...
Migraine has an assumed polygenic basis, but the genetic risk variants identified in genome-wide association studies only explain a proportion of the heritability. We aimed to develop machine learning models, capturing non-additive and interactive ef...
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