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Big data networks and orthology analysis

Persson, Emma, 1991- (author)
Stockholms universitet,Institutionen för biokemi och biofysik
Sonnhammer, Erik, Professor (thesis advisor)
Stockholms universitet,Institutionen för biokemi och biofysik
Barabási, Albert László, Professor (opponent)
Center for complex network research, Northeastern university, Boston, United States
 (creator_code:org_t)
ISBN 9789180145480
Stockholm : Department of Biochemistry and Biophysics, Stockholm University, 2023
English 67 s.
  • Doctoral thesis (other academic/artistic)
Abstract Subject headings
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  • Understanding biological systems in complex organisms is important in life science in order to comprehend the interplay of genes, proteins, and compounds causing complex diseases. As biological systems are intricate, bioinformatics tools, models, and algorithms are of the utmost importance to understand the bigger picture and decipher biological meaning from the vast amounts of information available from biological experiments and predictions. Bioinformatics programs and algorithms do not only depend on information from experiments, but also on information generated from other tools in order to draw accurate conclusions and make predictions. Prediction of orthologs, genes having a common ancestry, separated by a speciation event, are important building blocks for a wide variety of tools and analysis pipelines, as they can be used to transfer gene function between species. Orthologs can for example be used to map genes of model organisms to genes in humans in studies of drug targets. They are extensively used in functional association networks in order to transfer information between species. Functional association networks are models of associations between genes or proteins, where associations can be derived from experimental evidence of different types, from the species itself, or transferred from other species using orthologs. The networks can be used to explore the context and neighbors of a gene, but also for a variety of higher-level analyses, e.g. network-based pathway enrichment analysis. In pathway enrichment analysis the networks can be utilized to contextualize experimental gene sets and annotate them with biological functions. As these tools depend on each other, it is of great importance that the networks used in pathway enrichment analysis are comprehensive and accurate, and that the orthologs used in the networks are relevant and significant. In this thesis, the development and improvement of five bioinformatics tools within three areas of bioinformatics are presented. Despite the tools residing within slightly different areas, they all rely on each other, and can all on different levels improve our understanding of biological functions and biological meaning, from the level of orthology analysis to functional association networks to pathway enrichment analysis.

Subject headings

NATURVETENSKAP  -- Biologi -- Bioinformatik och systembiologi (hsv//swe)
NATURAL SCIENCES  -- Biological Sciences -- Bioinformatics and Systems Biology (hsv//eng)

Keyword

Ortholog
protein domain
functional association network
pathway enrichment analysis
biokemi med inriktning mot bioinformatik
Biochemistry towards Bioinformatics

Publication and Content Type

vet (subject category)
dok (subject category)

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