Torgeir R. Hvidsten, PhD

Assistant professor in Bioinformatics
Umeå Plant Science Centre
Department of Plant Physiology
Umeå University
SE-901 87 Umeå
Sweden

Computational Life Science Cluster (CLiC)
Umeå University
Sweden

torgeir.hvidsten(at)plantphys.umu.se
Phone: +46 (0)90 786 5248

Classic research papers

The Turing test, Watson-Crick, etc.

Current bioinformatics papers

My CiteULike-list of interesting papers from:
PLoS comp. bio. | Bioinformatics | BMC Bioinformatics | PNAS | Nature | Science | Proteins

Papers using Rosetta and local descriptors of protein structure.

Science cartoons

Research: Machine learning in bioinformatics

The machine learning strategy to experimental biology iteratively uses experiments to provide representative examples and computational models to provide experimentalists with new, testable hypotheses. [more | My introduction to bioinformatics and machine learning]

Gene regulation: We have shown that we can describe the specific mechanism behind the combinatorial nature of gene regulation by constructing IF-THEN rules ... [more]

Protein-ligand interactions: ... this means that models can be generated that span the entire enzyme-ligand space, containing proteins that vary greatly in terms of sequence, structure and function. [more]

Protein structure prediction: We have build a library of recurring local descriptors and show that this library is general enough to allow assembly of unseen protein structures. [more]

Collaborators

Publications

List of publications [Google Scholar | ISI Web of Science]

Latest: K. Wabnik, T. R. Hvidsten, A. Kedzierska, J. Van Leene, G. De Jaeger, G. T. S. Beemster, J. Komorowski and M. T. R. Kuiper. Gene expression trends and protein features effectively complement each other in gene function prediction, Bioinformatics 25 (3):322-330, 2009.

PhD-thesis: T. R. Hvidsten. Predicting function of genes and proteins from sequence, structure and expression data. Department of Information Technology, Uppsala University, 2004. [pdf with papers embedded | comments by reviewer Prof. Anna Tramontano]

Computational tools

FragHMMent | ROSETTA

Press releases and reviews | Teaching | Supervised student thesis