Skip Navigation

This Article
Right arrow FREE Full Text (Print PDF) Freely available
Right arrow Comments: Submit a response
Right arrow Alert me when this article is cited
Right arrow Alert me when Comments are posted
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 (11)
Right arrowRequest Permissions
Google Scholar
Right arrow Articles by Grundy, W. N.
Right arrow Articles by Bailey, T. L.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Grundy, W. N.
Right arrow Articles by Bailey, T. L.
Social Bookmarking
Add to CiteULike   Add to Connotea   Add to Del.icio.us  
What's this?

Bioinformatics, Vol 15, 463-470, Copyright © 1999 by Oxford University Press

ARTICLES

Family pairwise search with embedded motif models

WN Grundy and TL Bailey
Department of Computer Science, University of California, Santa Cruz, CA 95064 and NPACI/SDSC, MC 0505, 9500 Gilman Drive, Bldg 109, La Jolla, CA 92093-0505, USA. bgrundy@cse.ucsc.edu

MOTIVATION: Statistical models of protein families, such as position- specific scoring matrices, profiles and hidden Markov models, have been used effectively to find remote homologs when given a set of known protein family members. Unfortunately, training these models typically requires a relatively large set of training sequences. Recent work (Grundy, J. Comput. Biol., 5,<479-492, 1998) has shown that, when only a few family members are known, several theoretically justified statistical modeling techniques fail to provide homology detection performance on a par with Family Pairwise Search (FPS), an algorithm that combines scores from a pairwise sequence similarity algorithm such as BLAST. RESULTS: The present paper provides a model-based algorithm that improves FPS by incorporating hybrid motif-based models of the form generated by Cobbler (Henikoff and Henikoff, Protein Sci., 6, 698- 705, 1997). For the 73 protein families investigated here, this cobbled FPS algorithm provides better homology detection performance than either Cobbler or FPS alone. This improvement is maintained when BLAST is replaced with the full Smith-Waterman algorithm. AVAILABILITY: http://fps.sdsc.edu
Add to CiteULike CiteULike   Add to Connotea Connotea   Add to Del.icio.us Del.icio.us    What's this?


This article has been cited by other articles:


Home page
 Proc. Natl. Acad. Sci. USAHome page
J. Hou, S.-R. Jun, C. Zhang, and S.-H. Kim
From The Cover: Global mapping of the protein structure space and application in structure-based inference of protein function
PNAS, March 8, 2005; 102(10): 3651 - 3656.
[Abstract] [Full Text] [PDF]

Home page
 J. Biol. Chem.Home page
B. J. Mans, A. I. Louw, and A. W. H. Neitz
Savignygrin, a Platelet Aggregation Inhibitor from the Soft Tick Ornithodoros savignyi, Presents the RGD Integrin Recognition Motif on the Kunitz-BPTI Fold
J. Biol. Chem., June 7, 2002; 277(24): 21371 - 21378.
[Abstract] [Full Text] [PDF]


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.