Bioinformatics. 2014 Jun 17. pii: btu383. [Epub ahead of print]
Literome: PubMed-Scale Genomic Knowledge Base in the Cloud.
Abstract
MOTIVATION:
Advances in sequencing technology have led to an exponential growth of genomics data, yet it remains a formidable challenge to interpret such data for identifying disease genes and drug targets. There has been increasing interest in adopting a systems approach that incorporates prior knowledge such as gene networks and genotype-phenotype associations. The majority of such knowledge resides in text such as journal publications, which has been undergoing its own exponential growth. It has thus become a significant bottleneck to identify relevant knowledge for genomic interpretation as well as to keep up with new genomics findings.
RESULTS:
In the Literome project, we have developed an automatic curation system to extract genomic knowledge from PubMed articles and made this knowledge available in the cloud with a website to facilitate browsing, searching, and reasoning. Currently, Literome focuses on two types of knowledge most pertinent to genomic medicine: directed genic interactions such as pathways and genotype-phenotype associations. Users can search for interacting genes and the nature of the interactions, as well as diseases and drugs associated with a SNP or gene. Users can also search for indirect connections between two entities, e.g., a gene and a disease might be linked because an interacting gene is associated with a related disease. Availability: Literome is freely available at literome.azurewebsites.net. Download for non-commercial use is available via web services.
CONTACT:
hoifung@microsoft.com.
© The Author (2014). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.
- PMID:
- 24939151
- [PubMed - as supplied by publisher]
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