Skip Navigation


Bioinformatics Advance Access originally published online on August 7, 2006
Bioinformatics 2006 22(20):2562-2564; doi:10.1093/bioinformatics/btl428
This Article
Right arrow Full Text Freely available
Right arrow FREE Full Text (Print PDF) Freely available
Right arrow All Versions of this Article:
22/20/2562    most recent
btl428v1
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
Right arrow Search for citing articles in:
ISI Web of Science (5)
Right arrowRequest Permissions
Google Scholar
Right arrow Articles by Zhao, Q.
Right arrow Articles by Brown, T. R.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Zhao, Q.
Right arrow Articles by Brown, T. R.
Social Bookmarking
 Add to CiteULike   Add to Connotea   Add to Del.icio.us  
What's this?

© The Author 2006. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org

HiRes—a tool for comprehensive assessment and interpretation of metabolomic data

Qi Zhao 1, Radka Stoyanova 2, Shuyan Du 3, Paul Sajda 3 and Truman R. Brown 1,3,*

1 Hatch Center for MR Research, Department of Radiology, Columbia University New York, NY 10032 USA
2 Department of Radiation Oncology, Fox Chase Cancer Center Philadelphia, PA 19111 USA
3 Department of Biomedical Engineering, Columbia University New York, NY 10027 USA

*To whom correspondence should be addressed.

Summary: The increasing role of metabolomics in system biology is driving the development of tools for comprehensive analysis of high-resolution NMR spectral datasets. This task is quite challenging since unlike the datasets resulting from other ‘omics’, a substantial preprocessing of the data is needed to allow successful identification of spectral patterns associated with relevant biological variability. HiRes is a unique stand-alone software tool that combines standard NMR spectral processing functionalities with techniques for multi-spectral dataset analysis, such as principal component analysis and non-negative matrix factorization. In addition, HiRes contains extensive abilities for data cleansing, such as baseline correction, solvent peak suppression, removal of frequency shifts owing to experimental conditions as well as auxiliary information management. Integration of these components together with multivariate analytical procedures makes HiRes very capable of addressing the challenges for assessment and interpretation of large metabolomic datasets, greatly simplifying this otherwise lengthy and difficult process and assuring optimal information retrieval.

Availability: HiRes is freely available for research purposes at http://hatch.cpmc.columbia.edu/highresmrs.html

Contact: qz2106{at}columbia.edu


Received on April 10, 2006; revised on June 14, 2006; accepted on August 1, 2006

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.