This article is part of the supplement: Tenth International Conference on Bioinformatics. First ISCB Asia Joint Conference 2011 (InCoB/ISCB-Asia 2011): Computational Biology

Open Access Proceedings

Liverome: a curated database of liver cancer-related gene signatures with self-contained context information

Langho Lee1, Kai Wang2, Gang Li2, Zhi Xie2, Yuli Wang2, Jiangchun Xu2, Shaoxian Sun2, David Pocalyko2, Jong Bhak3, Chulhong Kim3, Kee-Ho Lee4, Ye Jin Jang5, Young Il Yeom5, Hyang-Sook Yoo6* and Seungwoo Hwang1*

Author Affiliations

1 Korean Bioinformation Center, Korea Research Institute of Bioscience and Biotechnology, Daejeon, Korea

2 Pfizer Global Research and Development, San Diego, CA, USA

3 Theragen BiO Institute, Suwon, Korea

4 Laboratory of Radiation Molecular Cancer, Korea Institute of Radiological and Medical Sciences, Seoul, Korea

5 Medical Genomics Research Center, Korea Research Institute of Bioscience and Biotechnology, Daejeon, Korea

6 Daejeon-KRIBB-FHCRC Research Cooperation Center, Korea Research Institute of Bioscience and Biotechnology, Daejeon, Korea

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BMC Genomics 2011, 12(Suppl 3):S3  doi:10.1186/1471-2164-12-S3-S3

Published: 30 November 2011

Abstract

Background

Hepatocellular carcinoma (HCC) is the fifth most common cancer worldwide. A number of molecular profiling studies have investigated the changes in gene and protein expression that are associated with various clinicopathological characteristics of HCC and generated a wealth of scattered information, usually in the form of gene signature tables. A database of the published HCC gene signatures would be useful to liver cancer researchers seeking to retrieve existing differential expression information on a candidate gene and to make comparisons between signatures for prioritization of common genes. A challenge in constructing such database is that a direct import of the signatures as appeared in articles would lead to a loss or ambiguity of their context information that is essential for a correct biological interpretation of a gene’s expression change. This challenge arises because designation of compared sample groups is most often abbreviated, ad hoc, or even missing from published signature tables. Without manual curation, the context information becomes lost, leading to uninformative database contents. Although several databases of gene signatures are available, none of them contains informative form of signatures nor shows comprehensive coverage on liver cancer. Thus we constructed Liverome, a curated database of liver cancer-related gene signatures with self-contained context information.

Description

Liverome’s data coverage is more than three times larger than any other signature database, consisting of 143 signatures taken from 98 HCC studies, mostly microarray and proteome, and involving 6,927 genes. The signatures were post-processed into an informative and uniform representation and annotated with an itemized summary so that all context information is unambiguously self-contained within the database. The signatures were further informatively named and meaningfully organized according to ten functional categories for guided browsing. Its web interface enables a straightforward retrieval of known differential expression information on a query gene and a comparison of signatures to prioritize common genes. The utility of Liverome-collected data is shown by case studies in which useful biological insights on HCC are produced.

Conclusion

Liverome database provides a comprehensive collection of well-curated HCC gene signatures and straightforward interfaces for gene search and signature comparison as well. Liverome is available at http://liverome.kobic.re.kr webcite.