Literature DB >> 27273670

MetalPredator: a web server to predict iron-sulfur cluster binding proteomes.

Yana Valasatava1, Antonio Rosato2, Lucia Banci2, Claudia Andreini2.   

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.
AVAILABILITY AND IMPLEMENTATION: The web server is freely available at: http://metalweb.cerm.unifi.it/tools/metalpredator/ CONTACT: andreini@cerm.unifi.it SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
© The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

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Year:  2016        PMID: 27273670     DOI: 10.1093/bioinformatics/btw238

Source DB:  PubMed          Journal:  Bioinformatics        ISSN: 1367-4803            Impact factor:   6.937


  19 in total

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2.  Identification of Iron-Sulfur (Fe-S) Cluster and Zinc (Zn) Binding Sites Within Proteomes Predicted by DeepMind's AlphaFold2 Program Dramatically Expands the Metalloproteome.

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3.  The cellular economy of the Saccharomyces cerevisiae zinc proteome.

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Review 7.  Bioinformatics of Metalloproteins and Metalloproteomes.

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9.  Branched late-steps of the cytosolic iron-sulphur cluster assembly machinery of Trypanosoma brucei.

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10.  The Oxymonad Genome Displays Canonical Eukaryotic Complexity in the Absence of a Mitochondrion.

Authors:  Anna Karnkowska; Sebastian C Treitli; Ondřej Brzoň; Lukáš Novák; Vojtěch Vacek; Petr Soukal; Lael D Barlow; Emily K Herman; Shweta V Pipaliya; Tomáš Pánek; David Žihala; Romana Petrželková; Anzhelika Butenko; Laura Eme; Courtney W Stairs; Andrew J Roger; Marek Eliáš; Joel B Dacks; Vladimír Hampl
Journal:  Mol Biol Evol       Date:  2019-10-01       Impact factor: 16.240

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