Detection of Conserved Domains in Protein Sequences Using a Maximum-Density Subgraph Algorithm
Summary :
In this paper, we propose a method for detecting conserved domains from a set of amino acid sequences that belong to a protein family. This method detects the domains as follows: first, generate fixed-length subsequences from the sequences; second, construct a weighted graph that connects any two of the subsequences (vertices) having higher similarity than a pre-defined threshold; third, search for the maximum-density subgraph for each connected component of the graph; finally, explore conserved domains in the sequences by combining the results of the previous step. From the performance results obtained by applying the method to several protein families that have complex conserved domains, we found that our method was able to detect those domains even though some domains were weakly conserved.
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- IEICE TRANSACTIONS on Fundamentals Vol.E83-A No.4 pp.713-721
- Publication Date
- 2000/04/25
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- Special Section PAPER (Special Section on Discrete Mathematics and Its Applications)
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Hideo MATSUDA, "Detection of Conserved Domains in Protein Sequences Using a Maximum-Density Subgraph Algorithm" in IEICE TRANSACTIONS on Fundamentals,
vol. E83-A, no. 4, pp. 713-721, April 2000, doi: .
Abstract: In this paper, we propose a method for detecting conserved domains from a set of amino acid sequences that belong to a protein family. This method detects the domains as follows: first, generate fixed-length subsequences from the sequences; second, construct a weighted graph that connects any two of the subsequences (vertices) having higher similarity than a pre-defined threshold; third, search for the maximum-density subgraph for each connected component of the graph; finally, explore conserved domains in the sequences by combining the results of the previous step. From the performance results obtained by applying the method to several protein families that have complex conserved domains, we found that our method was able to detect those domains even though some domains were weakly conserved.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/e83-a_4_713/_p
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@ARTICLE{e83-a_4_713,
author={Hideo MATSUDA, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={Detection of Conserved Domains in Protein Sequences Using a Maximum-Density Subgraph Algorithm},
year={2000},
volume={E83-A},
number={4},
pages={713-721},
abstract={In this paper, we propose a method for detecting conserved domains from a set of amino acid sequences that belong to a protein family. This method detects the domains as follows: first, generate fixed-length subsequences from the sequences; second, construct a weighted graph that connects any two of the subsequences (vertices) having higher similarity than a pre-defined threshold; third, search for the maximum-density subgraph for each connected component of the graph; finally, explore conserved domains in the sequences by combining the results of the previous step. From the performance results obtained by applying the method to several protein families that have complex conserved domains, we found that our method was able to detect those domains even though some domains were weakly conserved.},
keywords={},
doi={},
ISSN={},
month={April},}
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TY - JOUR
TI - Detection of Conserved Domains in Protein Sequences Using a Maximum-Density Subgraph Algorithm
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 713
EP - 721
AU - Hideo MATSUDA
PY - 2000
DO -
JO - IEICE TRANSACTIONS on Fundamentals
SN -
VL - E83-A
IS - 4
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - April 2000
AB - In this paper, we propose a method for detecting conserved domains from a set of amino acid sequences that belong to a protein family. This method detects the domains as follows: first, generate fixed-length subsequences from the sequences; second, construct a weighted graph that connects any two of the subsequences (vertices) having higher similarity than a pre-defined threshold; third, search for the maximum-density subgraph for each connected component of the graph; finally, explore conserved domains in the sequences by combining the results of the previous step. From the performance results obtained by applying the method to several protein families that have complex conserved domains, we found that our method was able to detect those domains even though some domains were weakly conserved.
ER -
English
