Skip Navigation


Bioinformatics Advance Access originally published online on December 1, 2007
Bioinformatics 2008 24(4):588-590; doi:10.1093/bioinformatics/btm581
This Article
Right arrow Full Text Freely available
Right arrow FREE Full Text (Print PDF) Freely available
Right arrowOA All Versions of this Article:
24/4/588    most recent
btm581v1
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in ISI Web of Science
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Add to My Personal Archive
Right arrow Download to citation manager
Google Scholar
Right arrow Articles by Adler, P.
Right arrow Articles by Vilo, J.
PubMed
Right arrow PubMed Citation
Right arrow Articles by Adler, P.
Right arrow Articles by Vilo, J.
Social Bookmarking
Add to CiteULike   Add to Connotea   Add to Del.icio.us  
What's this?

© 2007 The Author(s)
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.0/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

KEGGanim: pathway animations for high-throughput data

Priit Adler 1,{dagger}, Jüri Reimand 2,{dagger}, Jürgen Jänes 2, Raivo Kolde 3, Hedi Peterson 1,3 and Jaak Vilo 1,2,3,*

1Estonian Biocentre, Riia 23b, 2University of Tartu, Institute of Computer Science, Liivi 2 and 3QureTec Inc. Ülikooli 6a, Tartu, Estonia

*To whom correspondence should be addressed.


  Abstract

Motivation: Gene expression analysis with microarrays has become one of the most widely used high-throughput methods for gathering genome-wide functional data. Emerging -omics fields such as proteomics and interactomics introduce new information sources. With the rise of systems biology, researchers need to concentrate on entire complex pathways that guide individual genes and related processes. Bioinformatics methods are needed to link the existing knowledge about pathways with the growing amounts of experimental data.

Results: We present KEGGanim, a novel web-based tool for visualizing experimental data in biological pathways. KEGGanim produces animations and images of KEGG pathways using public or user uploaded high-throughput data. Pathway members are coloured according to experimental measurements, and animated over experimental conditions. KEGGanim visualization highlights dynamic changes over conditions and allows the user to observe important modules and key genes that influence the pathway. The simple user interface of KEGGanim provides options for filtering genes and experimental conditions. KEGGanim may be used with public or private data for 14 organisms with a large collection of public microarray data readily available. Most common gene and protein identifiers and microarray probesets are accepted for visualization input.

Availability: http://biit.cs.ut.ee/KEGGanim/

Contact: vilo{at}ut.ee

Associate Editor: Olga Troyanskaya

{dagger}The authors wish it to be known that, in their opinion, the first two authors should be regarded as joint First Authors.

Received on August 5, 2007; revised on October 22, 2007; accepted on November 19, 2007

Add to CiteULike CiteULike   Add to Connotea Connotea   Add to Del.icio.us Del.icio.us    What's this?




Disclaimer:
Please note that abstracts for content published before 1996 were created through digital scanning and may therefore not exactly replicate the text of the original print issues. All efforts have been made to ensure accuracy, but the Publisher will not be held responsible for any remaining inaccuracies. If you require any further clarification, please contact our Customer Services Department.