Nothing Special   »   [go: up one dir, main page]

skip to main content
10.1145/1066677.1066728acmconferencesArticle/Chapter ViewAbstractPublication PagessacConference Proceedingsconference-collections
Article

Text-based summarization and visualization of gene clusters

Published: 13 March 2005 Publication History

Abstract

We present a system named MedSummarizer which uses biomedical literature information to assign biological meaning to a cluster of genes. Using relevant PubMed citations, it creates a ranked list of important biological concepts that describes the gene list. Further, based on the assigned concepts, it computes similarity between each pair of genes and displays this using a graph based visualization technique. The system allows use of human curated index (e.g. Mesh terms) as well as automatic annotations derived from free-text. We compare the results obtained using these two types of terms.

References

[1]
H. Shaktay, S. Edwards, J. Wilbur, and M. Boguski. Genes, Themes and Microarrays: Using Information Retrieval for large-scale Gene analysis. In the Proceedings of ISMB, 1999.
[2]
L. Tanabe, U. Schref, L. Smith, and J. Lee et al. MedMiner: An Internet Text-Mining tool for Biomedical information with application to Gene Expression Profiling. Bio Techniques, 27:1210--1217, 1999.
[3]
L. V. Subramaniam, S. Mukherjea, P. Kankar, B. Srivastava, V. Batra, P. Kamesam and R. Kothari. Information Extraction from Biomedical Literature: Methodology, Evaluation and an Application. In the Proceedings of the CIKM conference, New Orleans, LA. November, 2003.
[4]
MeSH - http://www.nlm.nih.gov/mesh/meshhome.html
[5]
- http://www.ncbi.nlm.nih.gov/

Cited By

View all
  • (2009)Text Mining for Bioinformatics: State of the Art Review2009 2nd IEEE International Conference on Computer Science and Information Technology10.1109/ICCSIT.2009.5234922(398-401)Online publication date: Aug-2009

Recommendations

Comments

Please enable JavaScript to view thecomments powered by Disqus.

Information & Contributors

Information

Published In

cover image ACM Conferences
SAC '05: Proceedings of the 2005 ACM symposium on Applied computing
March 2005
1814 pages
ISBN:1581139640
DOI:10.1145/1066677
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

Sponsors

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 13 March 2005

Permissions

Request permissions for this article.

Check for updates

Author Tags

  1. biological text mining
  2. gene cluster summarization
  3. gene similarity visualization
  4. microarray analysis

Qualifiers

  • Article

Conference

SAC05
Sponsor:
SAC05: The 2005 ACM Symposium on Applied Computing
March 13 - 17, 2005
New Mexico, Santa Fe

Acceptance Rates

Overall Acceptance Rate 1,650 of 6,669 submissions, 25%

Contributors

Other Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

  • Downloads (Last 12 months)1
  • Downloads (Last 6 weeks)0
Reflects downloads up to 02 Oct 2024

Other Metrics

Citations

Cited By

View all
  • (2009)Text Mining for Bioinformatics: State of the Art Review2009 2nd IEEE International Conference on Computer Science and Information Technology10.1109/ICCSIT.2009.5234922(398-401)Online publication date: Aug-2009

View Options

Get Access

Login options

View options

PDF

View or Download as a PDF file.

PDF

eReader

View online with eReader.

eReader

Media

Figures

Other

Tables

Share

Share

Share this Publication link

Share on social media