| URL: | http://bioinfo.matf.bg.ac.rs/disorder |
| Full name: | |
| Description: | A web site Prokaryote Disorder Database has been designed which contains complete results of the analysis of protein disorder performed for 296 prokaryotic completely sequenced genomes. |
| Year founded: | 2011 |
| Last update: | |
| Version: | |
| Accessibility: |
Unaccessible
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| Country/Region: | Serbia and Montenegro |
| Data type: | |
| Data object: | |
| Database category: | |
| Major species: |
NA
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| Keywords: |
| University/Institution: | University of Belgrade |
| Address: | Faculty of Mathematics, University of Belgrade, P.O.B. 550, Studentski trg 16, 11001 Belgrade, Serbia. |
| City: | Belgrade |
| Province/State: | |
| Country/Region: | Serbia and Montenegro |
| Contact name (PI/Team): | Gordana M Pavlović-Lažetić |
| Contact email (PI/Helpdesk): | gordana@matf.bg.ac.rs |
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Bioinformatics analysis of disordered proteins in prokaryotes. [PMID: 21366926]
BACKGROUND: A significant number of proteins have been shown to be intrinsically disordered, meaning that they lack a fixed 3 D structure or contain regions that do not posses a well defined 3 D structure. It has also been proven that a protein's disorder content is related to its function. We have performed an exhaustive analysis and comparison of the disorder content of proteins from prokaryotic organisms (i.e., superkingdoms Archaea and Bacteria) with respect to functional categories they belong to, i.e., Clusters of Orthologous Groups of proteins (COGs) and groups of COGs-Cellular processes (Cp), Information storage and processing (Isp), Metabolism (Me) and Poorly characterized (Pc). We also analyzed the disorder content of proteins with respect to various genomic, metabolic and ecological characteristics of the organism they belong to. We used correlations and association rule mining in order to identify the most confident associations between specific modalities of the characteristics considered and disorder content. |