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Title 

SynechoNET: integrated protein-protein interaction database of a model cyanobacterium Synechocystis sp. PCC 6803

Authors 

Woo-Yeon KimSung Soo KangByoung Chul KimJ OhSeongwoong ChoJong BhakJ S Choi

Publisher 

BioMed Central

Issue Date 

2008

Citation 

BMC Bioinformatics, vol. 9, no. Sup1, pp. S20-S20

Keywords 

bacterial proteinmembrane proteinsignal peptidebacterial geneticsbacterial genomebacterial membranebioinformaticscomputer interfaceinformation retrievalnonhuman

Abstract 

Background: Cyanobacteria are model organisms for studying photosynthesis, carbon and nitrogen assimilation, evolution of plant plastids, and adaptability to environmental stresses. Despite many studies on cyanobacteria, there is no web-based database of their regulatory and signaling protein-protein interaction networks to date. Description: We report a database and website SynechoNET that provides predicted protein-protein interactions. SynechoNET shows cyanobacterial domain-domain interactions as well as their protein-level interactions using the model cyanobacterium, Synechocystis sp. PCC 6803. It predicts the protein-protein interactions using public interaction databases that contain mutually complementary and redundant data. Furthermore, SynechoNET provides information on transmembrane topology, signal peptide, and domain structure in order to support the analysis of regulatory membrane proteins. Such biological information can be queried and visualized in user-friendly web interfaces that include the interactive network viewer and search pages by keyword and functional category. Conclusion: SynechoNET is an integrated protein-protein interaction database designed to analyze regulatory membrane proteins in cyanobacteria. It provides a platform for biologists to extend the genomic data of cyanobacteria by predicting interaction partners, membrane association, and membrane topology of Synechocystis proteins. SynechoNET is freely available at http://synechocystis.org/ or directly at http://bioportal.kobic.kr/SynechoNET/.

ISSN 

1471-2105

Link 

http://dx.doi.org/10.1186/1471-2105-9-S1-S20

Appears in Collections

1. Journal Articles > Journal Articles

Registered Date

2019-05-02


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