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Author, Editor

Author(s):

Sommer, Ingolf
Toppo, Stefano
Sander, Oliver
Lengauer, Thomas
Tosatto, Silvio C. E.

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Not MPG Author(s):

Toppo, Stefano
Tosatto, Silvio C. E.

BibTeX cite key*:

Sommer2006a

Title

Title*:

Improving the quality of protein structure models by selecting from alignment alternatives

Journal

Journal Title*:

BMC Bioinformatics

Journal's URL:


Download URL
for the article:

http://dx.doi.org/10.1186/1471-2105-7-364

Language:

English

Publisher

Publisher's
Name:

BioMed Central

Publisher's URL:


Publisher's
Address:

London, UK

ISSN:


Vol, No, Year, pp.

Volume:

7

Number:


Month:

July

Year*:

2006

Pages:

1-11

Number of VG Pages:

11

Sequence Number:

364

DOI:


Abstract, Links, (C)

Note:


(LaTeX) Abstract:

Background

In the area of protein structure prediction, recently a lot of effort has gone into the development of Model Quality Assessment Programs (MQAPs). MQAPs distinguish high quality protein structure models from inferior models. Here, we propose a new method to use an MQAP to improve the quality of models. With a given target sequence and template structure, we construct a number of different alignments and corresponding models for the sequence. The quality of these models is scored with an MQAP and used to choose the most promising model. An SVM-based selection scheme is suggested for combining MQAP partial potentials, in order to optimize for improved model selection.

Results

The approach has been tested on a representative set of proteins. The ability of the method to improve models was validated by comparing the MQAP-selected structures to the native structures with the model quality evaluation program TM-score. Using the SVM-based model selection, a significant increase in model quality is obtained (as shown with a Wilcoxon signed rank test yielding p-values below 10-15). The average increase in TMscore is 0.016, the maximum observed increase in TM-score is 0.29.

Conclusion

In template-based protein structure prediction alignment is known to be a bottleneck limiting the overall model quality. Here we show that a combination of systematic alignment variation and modern model scoring functions can significantly improve the quality of alignment-based models.


URL for the Abstract:

http://www.biomedcentral.com/1471-2105/7/364/abstract

Categories / Keywords:


HyperLinks / References / URLs:


Copyright Message:


Personal Comments:


Download
Access Level:

Intranet

Correlation

MPG Unit:

Max-Planck-Institut für Informatik



MPG Subunit:

Computational Biology and Applied Algorithmics

Audience:

not specified

Appearance:

MPII WWW Server, MPII FTP Server, MPG publications list, university publications list, working group publication list, Fachbeirat, VG Wort



BibTeX Entry:

@MISC{Sommer2006a,
AUTHOR = {Sommer, Ingolf and Toppo, Stefano and Sander, Oliver and Lengauer, Thomas and Tosatto, Silvio C. E.},
TITLE = {Improving the quality of protein structure models by selecting from alignment alternatives},
JOURNAL = {BMC Bioinformatics},
PUBLISHER = {BioMed Central},
YEAR = {2006},
VOLUME = {7},
PAGES = {1--11},
ADDRESS = {London, UK},
MONTH = {July},
}


Entry last modified by Christine Kiesel, 05/03/2007
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Editor(s)
Ingolf Sommer
Created
11/20/2006 02:50:12 PM
Revisions
3.
2.
1.
0.
Editor(s)
Christine Kiesel
Christine Kiesel
Christine Kiesel
Ingolf Sommer
Edit Dates
03.05.2007 13:43:45
26.02.2007 16:07:57
22.02.2007 08:33:13
11/20/2006 02:50:12 PM