Defining the protein interaction network of human malaria parasite Plasmodium falciparum

Handle URI:
http://hdl.handle.net/10754/565967
Title:
Defining the protein interaction network of human malaria parasite Plasmodium falciparum
Authors:
Ramaprasad, Abhinay ( 0000-0001-9372-5526 ) ; Pain, Arnab ( 0000-0002-1755-2819 ) ; Ravasi, Timothy ( 0000-0002-9950-465X )
Abstract:
Malaria, caused by the protozoan parasite Plasmodium falciparum, affects around 225. million people yearly and a huge international effort is directed towards combating this grave threat to world health and economic development. Considerable advances have been made in malaria research triggered by the sequencing of its genome in 2002, followed by several high-throughput studies defining the malaria transcriptome and proteome. A protein-protein interaction (PPI) network seeks to trace the dynamic interactions between proteins, thereby elucidating their local and global functional relationships. Experimentally derived PPI network from high-throughput methods such as yeast two hybrid (Y2H) screens are inherently noisy, but combining these independent datasets by computational methods tends to give a greater accuracy and coverage. This review aims to discuss the computational approaches used till date to construct a malaria protein interaction network and to catalog the functional predictions and biological inferences made from analysis of the PPI network. © 2011 Elsevier Inc.
KAUST Department:
Biological and Environmental Sciences and Engineering (BESE) Division; Applied Mathematics and Computational Science Program; Computational Bioscience Research Center (CBRC)
Publisher:
Elsevier BV
Journal:
Genomics
Issue Date:
Feb-2012
DOI:
10.1016/j.ygeno.2011.11.006
PubMed ID:
22178265
Type:
Article
ISSN:
08887543
Sponsors:
This work was funded by King Abdullah University of Science and Technology, Thuwal, Kingdom of Saudi Arabia.
Appears in Collections:
Articles; Applied Mathematics and Computational Science Program; Computational Bioscience Research Center (CBRC); Biological and Environmental Sciences and Engineering (BESE) Division

Full metadata record

DC FieldValue Language
dc.contributor.authorRamaprasad, Abhinayen
dc.contributor.authorPain, Arnaben
dc.contributor.authorRavasi, Timothyen
dc.date.accessioned2015-08-12T08:57:18Zen
dc.date.available2015-08-12T08:57:18Zen
dc.date.issued2012-02en
dc.identifier.issn08887543en
dc.identifier.pmid22178265en
dc.identifier.doi10.1016/j.ygeno.2011.11.006en
dc.identifier.urihttp://hdl.handle.net/10754/565967en
dc.description.abstractMalaria, caused by the protozoan parasite Plasmodium falciparum, affects around 225. million people yearly and a huge international effort is directed towards combating this grave threat to world health and economic development. Considerable advances have been made in malaria research triggered by the sequencing of its genome in 2002, followed by several high-throughput studies defining the malaria transcriptome and proteome. A protein-protein interaction (PPI) network seeks to trace the dynamic interactions between proteins, thereby elucidating their local and global functional relationships. Experimentally derived PPI network from high-throughput methods such as yeast two hybrid (Y2H) screens are inherently noisy, but combining these independent datasets by computational methods tends to give a greater accuracy and coverage. This review aims to discuss the computational approaches used till date to construct a malaria protein interaction network and to catalog the functional predictions and biological inferences made from analysis of the PPI network. © 2011 Elsevier Inc.en
dc.description.sponsorshipThis work was funded by King Abdullah University of Science and Technology, Thuwal, Kingdom of Saudi Arabia.en
dc.publisherElsevier BVen
dc.subjectMalariaen
dc.subjectNetwork biologyen
dc.subjectPlasmodium falciparumen
dc.subjectProtein-protein interactionen
dc.titleDefining the protein interaction network of human malaria parasite Plasmodium falciparumen
dc.typeArticleen
dc.contributor.departmentBiological and Environmental Sciences and Engineering (BESE) Divisionen
dc.contributor.departmentApplied Mathematics and Computational Science Programen
dc.contributor.departmentComputational Bioscience Research Center (CBRC)en
dc.identifier.journalGenomicsen
dc.contributor.institutionDivision of Medical Genetics, Department of Medicine, University of California, San Diego, 9500 Gilman Drive, La Jolla, CA 92093, United Statesen
kaust.authorRamaprasad, Abhinayen
kaust.authorPain, Arnaben
kaust.authorRavasi, Timothyen

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