Motivation: The prediction of the iron-sulfur proteome is highly desirable for biomedical and biological research but a freely available tool to predict iron-sulfur proteins has not been developed yet. Results: We developed a web server to predict iron-sulfur proteins from protein sequence(s). This tool, called MetalPredator, is able to process complete proteomes rapidly with high recall and precision.
MetalPredator: A web server to predict iron-sulfur cluster binding proteomes / Valasatava, Yana; Rosato, Antonio; Banci, Lucia; Andreini, Claudia. - In: BIOINFORMATICS. - ISSN 1367-4803. - STAMPA. - 32:(2016), pp. 2850-2852. [10.1093/bioinformatics/btw238]
MetalPredator: A web server to predict iron-sulfur cluster binding proteomes
VALASATAVA, YANA;ROSATO, ANTONIO;BANCI, LUCIA;ANDREINI, CLAUDIA
2016
Abstract
Motivation: The prediction of the iron-sulfur proteome is highly desirable for biomedical and biological research but a freely available tool to predict iron-sulfur proteins has not been developed yet. Results: We developed a web server to predict iron-sulfur proteins from protein sequence(s). This tool, called MetalPredator, is able to process complete proteomes rapidly with high recall and precision.
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