Jonassen group
Pattern discovery in molecular biology data
Our research is focused on development and application of computational methods and tools for the analysis of molecular biology data. Our emphasis is on methods for the discovery of recurring patterns and unexpected correlations that may be of biological significance.
Sequence assembly and analysis
We are developing and applying methods for the assembly of
genomic sequences generated using ultra-high throughput sequencing
methods (pyrosequencing). Projects include assembly of bacterial
genomes and fish genomes (cod in context of
Genofisk).
We are also developing and applying
methods for analysis of meta-genomic data (genomic, transcriptomic)
in collaboration with the
centre for geo-biology. In another project
we are performing analyses of tuberculosis using comparative genomic
and proteomics approaches (in collaboration with
Harald G Wiker at
Gades Institute)
Microarray analysis and integrative bioinformatics
We develop methods for analysis of data from microarray experiments
focusing on expression analysis. We have been central in development of the
J-Express software package and also proposed new methods
for marker gene selection (feature subset selection) and imputation of
missing values. Collaboration with experimental groups have resulted in
a number of papers having microarray analyses as a central component.
We are now working toward integration of databases and tools toward
integrative bioinformatics and systems biology. We are partners in
the EU funded Network of Excellence Embrace
and the eVita funded project
eSysBio
Motif discovery and structure prediction
We are developing algorithmic tools for the automatic discovery
of patterns (motifs) in protein sequences and structures. These
are computationally very challenging problems.Therefore we focus
on developing algorithms able to deal with large data sets efficiently
exploring the space of possible patterns to identify the most significant
motifs. This has so far resulted in the tools Pratt and SPratt for
sequence and structure pattern discovery, respectively. We are currently
taking the structure pattern idea further into structure model evaluation
and structure prediction area.
Future projects and goals:
- Take part in collaborative projects utilising microarray and other high throughput technologies to utilise bioinformatics and statistical methods for data analysis.
- Develop further methods for handling, processing, and analysing functional genomics data.
- Work on methods for the analysis, comparison, and prediction of protein structure.
- Develop fully automated methods for analysis of pyrosequencing data including de-novo sequencing, re-sequencing, expression analysis.
Selected publications:
- Pendino F, Nguyen E, Jonassen I, Dysvik B, Azouz A, Lanotte M, Segal-Bendirdjian E, Lillehaug JR. (2009) Functional involvement of RINF, retinoid-inducible nuclear factor (CXXC5), in normal and tumoral human myelopoiesis. Blood. 2009 Jan 30.
- Eichner C, Frost P, Dysvik B, Jonassen I, Kristiansen B, Nilsen F. (2008) Salmon louse (Lepeophtheirus salmonis) transcriptomes during post molting maturation and egg production, revealed using EST-sequencing and microarray analysis. BMC Genomics. 9:126.
- Taylor WR, Bartlett GJ, Chelliah V, Klose D, Lin K, Sheldon T, Jonassen I. (2009) Prediction of protein structure from ideal forms. Proteins 70(4):1610-9.
- Bø, T. H., Dysvik, B., Jonassen, I. (2004) LSimpute: accurate estimation of missing values in microarray data with least squares methods. Nucl. Acids Res. 32:e34
- Malde, K., Coward, E., Jonassen, I. (2003) Fast Sequence Clustering Using A Suffix Array Algorithm. Bioinformatics 19:1221-1226
- Jonassen, I., Eidhammer, E., Taylor, W.R. (1999) Discovery of Local Packing Motifs in Protein Structures. Proteins: Struct., Funct., and Genet. 34:206-219
- Brazma, A., Jonassen, I., Vilo, J, Ukkonen, E. (1998) Prediction of Regulatory Elements in Silico on a Genomic Scale. Genome Research 8:1202-1215
- Jonassen, I., Collins, J. F., Higgins, D. G. (1995) Finding flexible patterns in unaligned protein sequences. Protein Science 4:1587-1595.
