Disputation: Boris Simovski
Doctoral candidate Boris Simovski at the Department of Informatics, Faculty of Mathematics and Natural Sciences, is defending the thesis "Genomic colocalization - an integrative framework for statistical analysis of sets of genomic tracks"for the degree of Philosophiae Doctor.
Trial lecture - time and place
14th of February, 10:15 AM,
"The impact of Next-Generation Sequencing technology on our current understanding of gene regulation”
Genomisk samlokaliseringsanalyse er et generisk rammeverk for statistisk analyse av relasjoner mellom et bredt spekter av egenskaper og prosesser som foregår langs organismers genomer. Kandidaten har utviklet et første rammeverk som omfatter den fulle bredden av aspekter involvert i analyse av genomisk samlokalisering - fra innhenting og integrering av heterogene datasett til avansert statistisk analyse i et brukervennlig grensesnitt.
Main research findings
The two past decades have brought a technological revolution in our ability to efficiently read DNA - the code of life. Consequently, literally millions of datasets DNA sequences of individuals (genomes) have been produced, along with a variety of characteristics of these genomes. Biology has been transformed into an increasingly data-centric discipline, where work in the lab is inevitably followed by downstream analysis using software tools to explore and confirm hypotheses of interest.
While characterizing the DNA sequence is a necessary first step, the really interesting question is how the complex interplay of processes operating on DNA inside our cells are involved in health and disease. Genomic colocalization analysis is a generic framework for integrating and investigating the relationship between a variety of characteristics and events along a genome. The main underlying assumption is that genomic elements that are functionally related will typically will be more proximally located along the genome than one would have expected by chance.
The work presented is a first comprehensive solution that supports integrative colocalization analysis from disparate data sources, with developed statistical methodology and an extensive set of tools for exploratory and confirmatory analysis of large collections of genomic data. The web-based, open-source software system enables researchers to perform streamlined and reproducible data analysis for a variety of biological scenarios, as well as being open to further extension and customization.
Contact information to Department: Pernille Adine Nordby