Combining Secondary Structure Element Alignment and Profile-Profile Alignment for Fold Recognition

Jan E. Gewehr; Niklas von Öhsen; Ralf Zimmer

Combining Secondary Structure Element Alignment and Profile-Profile Alignment for Fold Recognition

Jan E. Gewehr^*
, Niklas von Öhsen
, Ralf Zimmer

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

3 Scopus citations

Abstract

One of the most intensely studied problems of bioinformatics is the prediction of a protein structure from an amino acid sequence. In fold recognition, one reduces this problem to assigning a protein of unknown structure to one of the known fold classes as defined in the SCOP or CATH classifications. Here, we combine two alignment methods, secondary structure element alignment and log average profile-profile alignment that have been proven to perform well on this task. Our results show that the combination yields remarkably better fold recognition accuracy on well-known benchmark sets obtained from the literature. Especially on a difficult set built by McGuffin and Jones this new approach significantly outperforms other recently proposed fold recognition methods.

Original language	English
Title of host publication	Proceedings of the German Conference on Bioinformatics, GCB 2004
Editors	Robert Giegerich, Jens Stoye
Publisher	Gesellschaft fur Informatik (GI)
Pages	141-148
Number of pages	8
ISBN (Electronic)	3885793822
State	Published - 2004
Externally published	Yes
Event	2004 German Conference on Bioinformatics, GCB 2004 - Bielefeld, Germany Duration: 4 Oct 2004 → 6 Oct 2004

Publication series

Name	Lecture Notes in Informatics (LNI), Proceedings - Series of the Gesellschaft fur Informatik (GI)
Volume	P-53
ISSN (Print)	1617-5468
ISSN (Electronic)	2944-7682

Conference

Conference	2004 German Conference on Bioinformatics, GCB 2004
Country/Territory	Germany
City	Bielefeld
Period	4/10/04 → 6/10/04

Cite this

Gewehr, J. E., von Öhsen, N., & Zimmer, R. (2004). Combining Secondary Structure Element Alignment and Profile-Profile Alignment for Fold Recognition. In R. Giegerich, & J. Stoye (Eds.), Proceedings of the German Conference on Bioinformatics, GCB 2004 (pp. 141-148). (Lecture Notes in Informatics (LNI), Proceedings - Series of the Gesellschaft fur Informatik (GI); Vol. P-53). Gesellschaft fur Informatik (GI).

Gewehr, Jan E. ; von Öhsen, Niklas ; Zimmer, Ralf. / Combining Secondary Structure Element Alignment and Profile-Profile Alignment for Fold Recognition. Proceedings of the German Conference on Bioinformatics, GCB 2004. editor / Robert Giegerich ; Jens Stoye. Gesellschaft fur Informatik (GI), 2004. pp. 141-148 (Lecture Notes in Informatics (LNI), Proceedings - Series of the Gesellschaft fur Informatik (GI)).

@inproceedings{ee39b42b2ea84abda386c4ba45dab734,

title = "Combining Secondary Structure Element Alignment and Profile-Profile Alignment for Fold Recognition",

abstract = "One of the most intensely studied problems of bioinformatics is the prediction of a protein structure from an amino acid sequence. In fold recognition, one reduces this problem to assigning a protein of unknown structure to one of the known fold classes as defined in the SCOP or CATH classifications. Here, we combine two alignment methods, secondary structure element alignment and log average profile-profile alignment that have been proven to perform well on this task. Our results show that the combination yields remarkably better fold recognition accuracy on well-known benchmark sets obtained from the literature. Especially on a difficult set built by McGuffin and Jones this new approach significantly outperforms other recently proposed fold recognition methods.",

author = "Gewehr, \{Jan E.\} and \{von {\"O}hsen\}, Niklas and Ralf Zimmer",

note = "Publisher Copyright: {\textcopyright} 2004 Gesellschaft fur Informatik (GI). All rights reserved.; 2004 German Conference on Bioinformatics, GCB 2004 ; Conference date: 04-10-2004 Through 06-10-2004",

year = "2004",

language = "English",

series = "Lecture Notes in Informatics (LNI), Proceedings - Series of the Gesellschaft fur Informatik (GI)",

publisher = "Gesellschaft fur Informatik (GI)",

pages = "141--148",

editor = "Robert Giegerich and Jens Stoye",

booktitle = "Proceedings of the German Conference on Bioinformatics, GCB 2004",

}

Gewehr, JE, von Öhsen, N & Zimmer, R 2004, Combining Secondary Structure Element Alignment and Profile-Profile Alignment for Fold Recognition. in R Giegerich & J Stoye (eds), Proceedings of the German Conference on Bioinformatics, GCB 2004. Lecture Notes in Informatics (LNI), Proceedings - Series of the Gesellschaft fur Informatik (GI), vol. P-53, Gesellschaft fur Informatik (GI), pp. 141-148, 2004 German Conference on Bioinformatics, GCB 2004, Bielefeld, Germany, 4/10/04.

Combining Secondary Structure Element Alignment and Profile-Profile Alignment for Fold Recognition. / Gewehr, Jan E.; von Öhsen, Niklas; Zimmer, Ralf.
Proceedings of the German Conference on Bioinformatics, GCB 2004. ed. / Robert Giegerich; Jens Stoye. Gesellschaft fur Informatik (GI), 2004. p. 141-148 (Lecture Notes in Informatics (LNI), Proceedings - Series of the Gesellschaft fur Informatik (GI); Vol. P-53).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Combining Secondary Structure Element Alignment and Profile-Profile Alignment for Fold Recognition

AU - Gewehr, Jan E.

AU - von Öhsen, Niklas

AU - Zimmer, Ralf

PY - 2004

Y1 - 2004

N2 - One of the most intensely studied problems of bioinformatics is the prediction of a protein structure from an amino acid sequence. In fold recognition, one reduces this problem to assigning a protein of unknown structure to one of the known fold classes as defined in the SCOP or CATH classifications. Here, we combine two alignment methods, secondary structure element alignment and log average profile-profile alignment that have been proven to perform well on this task. Our results show that the combination yields remarkably better fold recognition accuracy on well-known benchmark sets obtained from the literature. Especially on a difficult set built by McGuffin and Jones this new approach significantly outperforms other recently proposed fold recognition methods.

AB - One of the most intensely studied problems of bioinformatics is the prediction of a protein structure from an amino acid sequence. In fold recognition, one reduces this problem to assigning a protein of unknown structure to one of the known fold classes as defined in the SCOP or CATH classifications. Here, we combine two alignment methods, secondary structure element alignment and log average profile-profile alignment that have been proven to perform well on this task. Our results show that the combination yields remarkably better fold recognition accuracy on well-known benchmark sets obtained from the literature. Especially on a difficult set built by McGuffin and Jones this new approach significantly outperforms other recently proposed fold recognition methods.

UR - https://www.scopus.com/pages/publications/33745165343

M3 - Conference contribution

AN - SCOPUS:33745165343

T3 - Lecture Notes in Informatics (LNI), Proceedings - Series of the Gesellschaft fur Informatik (GI)

SP - 141

EP - 148

BT - Proceedings of the German Conference on Bioinformatics, GCB 2004

A2 - Giegerich, Robert

A2 - Stoye, Jens

PB - Gesellschaft fur Informatik (GI)

T2 - 2004 German Conference on Bioinformatics, GCB 2004

Y2 - 4 October 2004 through 6 October 2004

ER -

Gewehr JE, von Öhsen N, Zimmer R. Combining Secondary Structure Element Alignment and Profile-Profile Alignment for Fold Recognition. In Giegerich R, Stoye J, editors, Proceedings of the German Conference on Bioinformatics, GCB 2004. Gesellschaft fur Informatik (GI). 2004. p. 141-148. (Lecture Notes in Informatics (LNI), Proceedings - Series of the Gesellschaft fur Informatik (GI)).

Combining Secondary Structure Element Alignment and Profile-Profile Alignment for Fold Recognition

Abstract

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