Genome Research

Home Help [Feedback] [For Subscribers] [Archive] [Search] [Contents]
 QUICK SEARCH:   [advanced]


     


This Article
Right arrow Full Text
Right arrow Full Text (PDF)
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Right arrow Citation Map
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Download to citation manager
Right arrow reprints & permissions
Citing Articles
Right arrow Citing Articles via HighWire
Right arrow Citing Articles via Google Scholar
Google Scholar
Right arrow Articles by Kuehl, P. M.
Right arrow Articles by Boguski, M. S.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Kuehl, P. M.
Right arrow Articles by Boguski, M. S.
Social Bookmarking
 Add to CiteULike   Add to Connotea   Add to Del.icio.us   Add to Digg   Add to Reddit   Add to Technorati  
What's this?

Vol. 9, Issue 2, 189-194, February 1999

RESOURCE
An Effective Approach for Analyzing "Prefinished" Genomic Sequence Data

Peter M. Kuehl,1,2,3 Jane M. Weisemann,3 Jeffrey W. Touchman,2 Eric D. Green,2 and Mark S. Boguski3,4

1 University of Maryland, Department of Molecular and Cellular Biology, Baltimore, Maryland 21201; 2 Genome Technology Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland 20892; 3 National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, Maryland 20894 USA

Ongoing efforts to sequence the human genome are already generating large amounts of data, with substantial increases anticipated over the next few years. In most cases, a shotgun sequencing strategy is being used, which rapidly yields most of the primary sequence in incompletely assembled sequence contigs ("prefinished" sequence) and more slowly produces the final, completely assembled sequence ("finished" sequence). Thus, in general, prefinished sequence is produced in excess of finished sequence, and this trend is certain to continue and even accelerate over the next few years. Even at a prefinished stage, genomic sequence represents a rich source of important biological information that is of great interest to many investigators. However, analyzing such data is a challenging and daunting task, both because of its sheer volume and because it can change on a day-by-day basis. To facilitate the discovery and characterization of genes and other important elements within prefinished sequence, we have developed an analytical strategy and system that uses readily available software tools in new combinations. Implementation of this strategy for the analysis of prefinished sequence data from human chromosome 7 has demonstrated that this is a convenient, inexpensive, and extensible solution to the problem of analyzing the large amounts of preliminary data being produced by large-scale sequencing efforts. Our approach is accessible to any investigator who wishes to assimilate additional information about particular sequence data en route to developing richer annotations of a finished sequence.

[Our software system is available via an extensive web supplement to this article at http://www.ncbi.nlm.nih.gov/Kuehl/prefinished.]


4   Corresponding author.


9:189-194 ©1999 by Cold Spring Harbor Laboratory Press  ISSN 1088-9051/99 $5.00

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


This article has been cited by other articles:


Home page
Nucleic Acids ResHome page
M. D. Wilson, C. Riemer, D. W. Martindale, P. Schnupf, A. P. Boright, T. L. Cheung, D. M. Hardy, S. Schwartz, S. W. Scherer, L.-C. Tsui, et al.
Comparative analysis of the gene-dense ACHE/TFR2 region on human chromosome 7q22 with the orthologous region on mouse chromosome 5
Nucleic Acids Res., March 15, 2001; 29(6): 1352 - 1365.
[Abstract] [Full Text] [PDF]




Home Help [Feedback] [For Subscribers] [Archive] [Search] [Contents]
Genes Dev. Learn. Mem.
Protein Science RNA Genome Res.