PlantLoc: an accurate web server for predicting plant protein subcellular localization by substantiality motif.
Nucleic Acids Res
; 41(Web Server issue): W441-7, 2013 Jul.
Article
en En
| MEDLINE
| ID: mdl-23729470
Knowledge of subcellular localizations (SCLs) of plant proteins relates to their functions and aids in understanding the regulation of biological processes at the cellular level. We present PlantLoc, a highly accurate and fast webserver for predicting the multi-label SCLs of plant proteins. The PlantLoc server has two innovative characters: building localization motif libraries by a recursive method without alignment and Gene Ontology information; and establishing simple architecture for rapidly and accurately identifying plant protein SCLs without a machine learning algorithm. PlantLoc provides predicted SCLs results, confidence estimates and which is the substantiality motif and where it is located on the sequence. PlantLoc achieved the highest accuracy (overall accuracy of 80.8%) of identification of plant protein SCLs as benchmarked by using a new test dataset compared other plant SCL prediction webservers. The ability of PlantLoc to predict multiple sites was also significantly higher than for any other webserver. The predicted substantiality motifs of queries also have great potential for analysis of relationships with protein functional regions. The PlantLoc server is available at http://cal.tongji.edu.cn/PlantLoc/.
Texto completo:
1
Colección:
01-internacional
Base de datos:
MEDLINE
Asunto principal:
Proteínas de Plantas
/
Programas Informáticos
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Señales de Clasificación de Proteína
Tipo de estudio:
Prognostic_studies
/
Risk_factors_studies
Idioma:
En
Revista:
Nucleic Acids Res
Año:
2013
Tipo del documento:
Article
País de afiliación:
China
Pais de publicación:
Reino Unido