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PeroxisomeDB: a database for the peroxisomal proteome, functional genomics and disease

Overview of attention for article published in Nucleic Acids Research, January 2007
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PeroxisomeDB: a database for the peroxisomal proteome, functional genomics and disease
Published in
Nucleic Acids Research, January 2007
DOI 10.1093/nar/gkl935
Pubmed ID

A. Schluter, S. Fourcade, E. Domenech-Estevez, T. Gabaldon, J. Huerta-Cepas, G. Berthommier, R. Ripp, R. J. A. Wanders, O. Poch, A. Pujol


Peroxisomes are essential organelles of eukaryotic origin, ubiquitously distributed in cells and organisms, playing key roles in lipid and antioxidant metabolism. Loss or malfunction of peroxisomes causes more than 20 fatal inherited conditions. We have created a peroxisomal database (http://www.peroxisomeDB.org) that includes the complete peroxisomal proteome of Homo sapiens and Saccharomyces cerevisiae, by gathering, updating and integrating the available genetic and functional information on peroxisomal genes. PeroxisomeDB is structured in interrelated sections 'Genes', 'Functions', 'Metabolic pathways' and 'Diseases', that include hyperlinks to selected features of NCBI, ENSEMBL and UCSC databases. We have designed graphical depictions of the main peroxisomal metabolic routes and have included updated flow charts for diagnosis. Precomputed BLAST, PSI-BLAST, multiple sequence alignment (MUSCLE) and phylogenetic trees are provided to assist in direct multispecies comparison to study evolutionary conserved functions and pathways. Highlights of the PeroxisomeDB include new tools developed for facilitating (i) identification of novel peroxisomal proteins, by means of identifying proteins carrying peroxisome targeting signal (PTS) motifs, (ii) detection of peroxisomes in silico, particularly useful for screening the deluge of newly sequenced genomes. PeroxisomeDB should contribute to the systematic characterization of the peroxisomal proteome and facilitate system biology approaches on the organelle.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 73 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Germany 3 4%
Portugal 1 1%
Netherlands 1 1%
France 1 1%
Italy 1 1%
Spain 1 1%
Unknown 65 89%

Demographic breakdown

Readers by professional status Count As %
Researcher 20 27%
Student > Ph. D. Student 20 27%
Student > Master 8 11%
Professor 7 10%
Professor > Associate Professor 3 4%
Other 6 8%
Unknown 9 12%
Readers by discipline Count As %
Agricultural and Biological Sciences 34 47%
Biochemistry, Genetics and Molecular Biology 19 26%
Medicine and Dentistry 3 4%
Pharmacology, Toxicology and Pharmaceutical Science 2 3%
Unspecified 2 3%
Other 3 4%
Unknown 10 14%