DocumentCode
2093706
Title
myMCL: A Web Portal for Protein Complexes Prediction
Author
Cannataro, Mario ; Guzzi, Pietro Hiram ; Veltri, Pierangelo
Author_Institution
Lab. of Bioinf., Univ. Magna Graecia of Catanzaro, Catanzaro
fYear
2008
fDate
17-19 June 2008
Firstpage
179
Lastpage
184
Abstract
Interactomics is the study of the Interactome, i.e. the whole set of macromolecular interactions within a cell. Proteins interact among them and different interactions are represented as graphs named Protein to Protein Interaction (PPI) networks. The interest in analyzing PPI networks is related to the possibility of predicting PPI properties on the basis of global properties of the graph (e.g. verify if homology among species involves PPI similarity), or to find set of protein interactions that has a biological meaning. The prediction of protein complexes has been faced in the last years by using different clustering algorithms. The Markov Clustering algorithm (MCL) is a method that presents one of the best performance but is currently available only as a stand alone application with a simple command-line interface available only on Linux platforms. Following a trend in bioinformatics, we provide a web portal (myMCL) allowing remote users to access MCL functions through the Internet. myMCL enables user to submit a job and stores results in a local database for further processing.
Keywords
Linux; Markov processes; biology computing; pattern clustering; portals; proteins; Linux platforms; Markov clustering algorithm; Web portal; bioinformatics; command-line interface; macromolecular interactions; myMCL; protein complexes prediction; protein interaction networks; Bioinformatics; Clustering algorithms; Databases; Internet; Joining processes; Laboratories; Linux; Portals; Prediction algorithms; Proteins; Clustering; MCL; Protein Complexes; Protein to Protein Interactions;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer-Based Medical Systems, 2008. CBMS '08. 21st IEEE International Symposium on
Conference_Location
Jyvaskyla
ISSN
1063-7125
Print_ISBN
978-0-7695-3165-6
Type
conf
DOI
10.1109/CBMS.2008.113
Filename
4561983
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