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Identification and Analysis of Important Proteins in Protein Interaction Networks Using Functional and Topological Information
University of Skövde, School of Life Sciences.
2008 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

Studying protein interaction networks using functional and topological information is important for understanding cellular organization and functionality. This study deals with identifying important proteins in protein interaction networks using SWEMODE (Lubovac, et al, 2006) and analyzing topological and functional properties of these proteins with the help of information derived from modular organization in protein interaction networks as well as information available in public resources, in this case, annotation sources describing the functionality of proteins. Multi-modular proteins are short-listed from the modules generated by SWEMODE. Properties of these short-listed proteins are then analyzed using functional information from SGD Gene Ontology(GO) (Dwight, et al., 2002) and MIPS functional categories (Ruepp, et al., 2004). Topological features such as lethality and centrality of these proteins are also investigated, using graph theoretic properties and information on lethal genes from Yeast Hub (Kei-Hoi, et al., 2005). The findings of the study based on GO terms reveal that these important proteins are mostly involved in the biological process of “organelle organization and biogenesis” and a majority of these proteins belong to MIPS “cellular organization” and “transcription” functional categories. A study of lethality reveals that multi-modular proteins are more likely to be lethal than proteins present only in a single module. An examination of centrality (degree of connectivity of proteins) in the network reveals that the ratio of number of important proteins to number of hubs at different hub sizes increases with the hub size (degree).

Place, publisher, year, edition, pages
2008. , p. 40
Keywords [en]
Module Based Protein Interaction Networks
National Category
Bioinformatics and Computational Biology
Identifiers
URN: urn:nbn:se:his:diva-2395OAI: oai:DiVA.org:his-2395DiVA, id: diva2:127089
Presentation
(Arabic)
Uppsok
Life Earth Science
Supervisors
Examiners
Available from: 2008-12-02 Created: 2008-11-30 Last updated: 2025-02-07Bibliographically approved

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CiteExportLink to record
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Citation style
  • apa
  • apa-cv
  • ieee
  • modern-language-association-8th-edition
  • vancouver
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More styles
Language
  • de-DE
  • en-GB
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  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
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