Abstract
It is widely recognized that much of the information for determining the final subcellular localization of proteins is found in their amino acid sequences. Thus the prediction of protein localization sites is of both theoretical and practical interest. In most cases, the prediction has been attempted in two ways: one is based on the knowledge of experimentally characterized targeting signals, while the other utilizes the statistical differences of general sequence characteristics, such as amino acid composition, between localization sites. Both approaches have limitations, and it is recommended to check the results of various prediction methods based on different principles as well as training data. Recently, increased proteomic analyses of localization sites have provided new data to assess the current status of predictive methods. In this chapter we discuss these issues and close with an example illustrating the use of the WoLF PSORT web server for localization prediction.
| Original language | English |
|---|---|
| Title of host publication | Protein Targeting Protocols, Second Edition |
| Pages | 429-466 |
| Number of pages | 38 |
| DOIs | |
| Publication status | Published - 2007 May 21 |
Publication series
| Name | Methods in Molecular Biology |
|---|---|
| Volume | 390 |
| ISSN (Print) | 1064-3745 |
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All Science Journal Classification (ASJC) codes
- Molecular Biology
- Genetics
Cite this
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Computational prediction of subcellular localization. / Nakai, Kenta; Paul, Brice Horton Ii.
Protein Targeting Protocols, Second Edition. 2007. p. 429-466 (Methods in Molecular Biology; Vol. 390).Research output: Chapter in Book/Report/Conference proceeding › Chapter
TY - CHAP
T1 - Computational prediction of subcellular localization
AU - Nakai, Kenta
AU - Paul, Brice Horton Ii
PY - 2007/5/21
Y1 - 2007/5/21
N2 - It is widely recognized that much of the information for determining the final subcellular localization of proteins is found in their amino acid sequences. Thus the prediction of protein localization sites is of both theoretical and practical interest. In most cases, the prediction has been attempted in two ways: one is based on the knowledge of experimentally characterized targeting signals, while the other utilizes the statistical differences of general sequence characteristics, such as amino acid composition, between localization sites. Both approaches have limitations, and it is recommended to check the results of various prediction methods based on different principles as well as training data. Recently, increased proteomic analyses of localization sites have provided new data to assess the current status of predictive methods. In this chapter we discuss these issues and close with an example illustrating the use of the WoLF PSORT web server for localization prediction.
AB - It is widely recognized that much of the information for determining the final subcellular localization of proteins is found in their amino acid sequences. Thus the prediction of protein localization sites is of both theoretical and practical interest. In most cases, the prediction has been attempted in two ways: one is based on the knowledge of experimentally characterized targeting signals, while the other utilizes the statistical differences of general sequence characteristics, such as amino acid composition, between localization sites. Both approaches have limitations, and it is recommended to check the results of various prediction methods based on different principles as well as training data. Recently, increased proteomic analyses of localization sites have provided new data to assess the current status of predictive methods. In this chapter we discuss these issues and close with an example illustrating the use of the WoLF PSORT web server for localization prediction.
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UR - http://www.scopus.com/inward/citedby.url?scp=36549082406&partnerID=8YFLogxK
U2 - 10.1385/1-59745-466-4:429
DO - 10.1385/1-59745-466-4:429
M3 - Chapter
C2 - 17951705
AN - SCOPUS:36549082406
SN - 1597454664
SN - 9781597454667
T3 - Methods in Molecular Biology
SP - 429
EP - 466
BT - Protein Targeting Protocols, Second Edition
ER -