Published September 15, 2007
| Published
Journal Article
Open
Automated data integration for developmental biological research
- Creators
- Zhong, Weiwei
-
Sternberg, Paul W.
Chicago
Abstract
In an era exploding with genome-scale data, a major challenge for developmental biologists is how to extract significant clues from these publicly available data to benefit our studies of individual genes, and how to use them to improve our understanding of development at a systems level. Several studies have successfully demonstrated new approaches to classic developmental questions by computationally integrating various genome-wide data sets. Such computational approaches have shown great potential for facilitating research: instead of testing 20,000 genes, researchers might test 200 to the same effect. We discuss the nature and state of this art as it applies to developmental research.
Additional Information
© The Company of Biologists Ltd 2007. Many of the model organism databases and the Gene Ontology Consortium that are crucial to data integration are supported by the National Human Genome Research Institute (e.g. WormBase grant HG02223 to P.W.S. and Gene Ontology Consortium grant HG002273 to Judith Blake). We thank Min Han for communicating unpublished results, and Alok Saldanha, Erich Schwarz, Xiaodong Wang and anonymous reviewers for comments on the manuscript. Relevant genetics research in our laboratory is supported by the Howard Hughes Medical Institute, with which P.W.S. is an Investigator and W.Z. an Associate.Attached Files
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Additional details
- Eprint ID
- 12698
- Resolver ID
- CaltechAUTHORS:ZHOdev07
- National Human Genome Research Institute
- HG02223
- National Human Genome Research Institute
- HG002273
- Howard Hughes Medical Institute
- Created
-
2008-12-20Created from EPrint's datestamp field
- Updated
-
2021-11-08Created from EPrint's last_modified field