Analyzing genomic data: understanding the genome

Authors:
Xosé M. Fernández-Suárez
Affiliations:
EMBL-European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, UK
Venue:
Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery
Year:
2012

Citing 8
Cited 0

FatiGO: a web tool for finding significant associations of Gene Ontology terms with groups of genes

Bioinformatics
Large-scale analysis of non-synonymous coding region single nucleotide polymorphisms

Bioinformatics
Bigtable: a distributed storage system for structured data

OSDI '06 Proceedings of the 7th USENIX Symposium on Operating Systems Design and Implementation - Volume 7
Dynamo: amazon's highly available key-value store

Proceedings of twenty-first ACM SIGOPS symposium on Operating systems principles
Text processing through Web services

Bioinformatics
The Unreasonable Effectiveness of Data

IEEE Intelligent Systems
SNVMix

Bioinformatics
Deriving the consequences of genomic variants with the Ensembl API and SNP Effect Predictor

Bioinformatics

Quantified Score

Hi-index	0.00

Visualization

Abstract

The effort that led to the sequencing of the human genome ushered life sciences into a new era. One of the largest international scientific endeavors of the time delivered the genetic makeup of our species to the research community. Further international consortia (HapMap, ENCODE, International Human Epigenome Consortium, 1000 Genomes Project) are shaping our understanding of the genomic landscape. Current high-throughput sequencing technologies can deliver a whole human genome in a matter of days. The subsequent data avalanche is stored in public repositories (including individual genomes). Such developments emphasize the need for data mining approaches. In this contribution, several tools and strategies to access these data are presented. © 2012 Wiley Periodicals, Inc. © 2012 Wiley Periodicals, Inc.