Network theory to understand microarray studies of complex diseases.

↓ Direkt till sidans innehåll
↓ Direkt till sidans sekundära innehåll (sidomenyn)

Search: WFRF:(Benson Mikael 1954 ) > (2005-2009) > Network theory to u...

Details
MARC

Benson, Mikael,1954Gothenburg University,Göteborgs universitet,Institutionen för kliniska vetenskaper,Institute of Clinical Sciences,Department of Pediatrics, Queen Silvia Children's Hospital, Gothenburg, Sweden (author)

Network theory to understand microarray studies of complex diseases.

Article/chapterEnglish2006

Publisher, publication year, extent ...

Bentham Science Publishers,2006

Numbers

LIBRIS-ID:oai:gup.ub.gu.se/120009
https://gup.ub.gu.se/publication/120009URI
https://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-99937URI
https://doi.org/10.2174/156652406778195044DOI

Supplementary language notes

Language:English

Part of subdatabase

SwePubSwePub

Classification

Subject category:ref swepub-contenttype
Subject category:art swepub-publicationtype

Notes

Complex diseases, such as allergy, diabetes and obesity depend on altered interactions between multiple genes, rather than changes in a single causal gene. DNA microarray studies of a complex disease often implicate hundreds of genes in the pathogenesis. This indicates that many different mechanisms and pathways are involved. How can we understand such complexity? How can hypotheses be formulated and tested? One approach is to organize the data in network models and to analyze these in a top-down manner. Globally, networks in nature are often characterized by a small number of highly connected nodes, while the majority of nodes have few connections. The highly connected nodes serve as hubs that affect many other nodes. Such hubs have key roles in the network. In yeast cells, for example, deletion of highly connected proteins is associated with increased lethality, compared to deletion of less connected proteins. This suggests the biological relevance of networks. Moving down in the network structure, there may be sub-networks or modules with specific functions. These modules may be further dissected to analyze individual nodes. In the context of DNA microarray studies of complex diseases, gene-interaction networks may contain modules of co-regulated or interacting genes that have distinct biological functions. Such modules may be linked to specific gene polymorphisms, transcription factors, cellular functions and disease mechanisms. Genes that are reliably active only in the context of their modules can be considered markers for the activity of the modules and may thus be promising candidates for biomarkers or therapeutic targets. This review aims to give an introduction to network theory and how it can be applied to microarray studies of complex diseases.

Subject headings and genre

Humans
Models
Biological
Oligonucleotide Array Sequence Analysis
Research Design
Systems Biology
DNA microarray; Gene A; Repressor Molecule Z; co-expression; hub proteins

Added entries (persons, corporate bodies, meetings, titles ...)

Breitling, RainerGroningen Bioinformatics Centre, University of Groningen, The Netherlands (author)
Göteborgs universitetInstitutionen för kliniska vetenskaper (creator_code:org_t)

Related titles

In:Current molecular medicine: Bentham Science Publishers6:6, s. 695-7011566-52401875-5666

Internet link

Find in a library

Current molecular medicine (Search for host publication in LIBRIS)

To the university's database

Find more in SwePub

By the author/editor: Benson, Mikael, ...; Breitling, Raine ...

Articles in the publication: Current molecula ...

By the university: University of Gothenburg; Linköping University

Search outside SwePub

Extend your search to:: Google; Google Book Search; Google Scholar

Kungliga biblioteket hanterar dina personuppgifter i enlighet med EU:s dataskyddsförordning (2018), GDPR. Läs mer om hur det funkar här.
Så här hanterar KB dina uppgifter vid användning av denna tjänst.

LIBRIS.kb.se