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Network and gene ex...
Network and gene expression analyses for understanding protein function
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- Frings, Oliver, 1982- (författare)
- Stockholms universitet,Institutionen för biokemi och biofysik
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- Sonnhammer, Erik, Professor (preses)
- Stockholms universitet,Institutionen för biokemi och biofysik
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- Linding, Rune, Professor (opponent)
- Technical University of Denmark (DTU), Department of Systems Biology
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(creator_code:org_t)
- ISBN 9789174476743
- Stockholm : Department of Biochemistry and Biophysics, Stockholm University, 2013
- Engelska 86 s.
- Relaterad länk:
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https://urn.kb.se/re...
Abstract
Ämnesord
Stäng
- Biological function is the result of a complex network of functional associations between genes or their products. Modeling the dynamics underlying biological networks is one of the big challenges in bioinformatics. A first step towards solving this problem is to predict and study the networks of functional associations underlying various conditions.An improved version of the FunCoup network inference method that features networks for three new species and updated versions of the existing networks is presented. Network clustering, i.e. partitioning networks into highly connected components is an important tool for network analysis. We developed MGclus, a clustering method for biological networks that scores shared network neighbors. We found MGclus to perform favorably compared to other methods popular in the field. Studying sets of experimentally derived genes in the context of biological networks is a common strategy to shed light on their underlying biology. The CrossTalkZ method presented in this work assesses the statistical significance of crosstalk enrichment, i.e. the extent of connectivity between or within groups of functionally coupled genes or proteins in biological networks. We further demonstrate that CrossTalkZ is a valuable method to functionally annotate experimentally derived gene sets.Males and females differ in the expression of an extensive number of genes. The methods developed in the first part of this work were applied to study sex-biased genes in chicken and several network properties related to the molecular mechanisms of sex-biased gene regulation in chicken were deduced. Cancer studies have shown that tumor progression is strongly determined by the tumor microenvironment. We derived a gene expression signature of PDGF-activated fibroblasts that shows a strong prognostic significance in breast cancer in univariate and multivariate survival analyses when compared to established markers for prognosis.
Ämnesord
- NATURVETENSKAP -- Data- och informationsvetenskap -- Bioinformatik (hsv//swe)
- NATURAL SCIENCES -- Computer and Information Sciences -- Bioinformatics (hsv//eng)
Nyckelord
- biological networks
- network inference
- network analysis
- clustering
- network module
- network crosstalk
- expression analysis
- gene signature
- biomarker
- biokemi, inriktning teoretisk kemi
- Biochemistry with Emphasis on Theoretical Chemistry
Publikations- och innehållstyp
- vet (ämneskategori)
- dok (ämneskategori)
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