Bengt Persson

Key publications

Östberg, L. J., Persson, B. & Höög, J.-O. (2014) The mammalian alcohol dehydrogenase genome shows several gene duplications and gene losses resulting in a large set of different enzymes including pseudoenzymes. Chem. Biol. Interact. pii: S0009-2797(14)00378-0. doi: 10.1016/j.cbi.2014.11.020. [Epub ahead of print]

Östberg, L. J., Strömberg, P., Hedberg, J. J., Persson, B. & Höög, J.-O. (2013) Analysis of mammalian alcohol dehydrogenase 5 (ADH5): Characterisation of rat ADH5 with comparisons to the corresponding human variant. Chem. Biol. Interact. 202, 97–103.

Persson, B. & Kallberg, Y. (2013) Classification and nomenclature of the superfamily of short-chain dehydrogenases/reductases (SDRs). Chem. Biol. Interact. 202, 111–115.

Lysholm, F., Andersson, B. & Persson, B. (2011) An efficient simulator of 454 data using configurable statistical models. BMC Res. Notes 4, 449.

Lysholm, F., Andersson, B. & Persson, B. (2011) FAAST: Flow-space Assisted Alignment Search Tool. BMC Bioinformatics 12, 293.

Hedlund, J., Jörnvall, H. & Persson, B. (2010) Subdivision of the MDR superfamily of medium-chain dehydrogenases/reductases through iterative hidden Markov model refinement. BMC Bioinformatics 11, 534.

Kallberg, Y., Oppermann, U. and Persson, B. (2010) Classification of the short-chain dehydrogenase/reductase (SDR) super-family using hidden Markov models. FEBS Journal 277, 2375–2386.

Hedlund, J., Johansson, J. & Persson, B. (2009) BRICHOS – A superfamily of multidomain proteins with diverse functions. BMC Res. Notes 2, 180.

Carlsson, J., Soussi, T. & Persson, B. (2009) Investigation and prediction of the severity of p53 mutants using parameters from structural calcuations. FEBS J. 276, 142–155.

Carlsson, B., Lindberg, A.M., Rodrigues-Díaz, J., Hedlund, K.-O., Persson, B. & Svensson, L. (2009) Quasispecies dynamics and molecular evolution of human novovirus capsid P region during chronic infection. J. Gen. Virol. 90, 432–441.

Persson, B., Kallberg, Y., Bray, J.E., Bruford, E., Dellaporta, S.L., Favia, A.D., Duarte, R.G., Jörnvall, H., Kavanagh, K.L., Kedishvili, N., Kisiela, M., Maser, E., Mindnich, R., Orchard, S., Penning, T.M., Thornton, J.M., Adamski, J. and Oppermann, U. (2009) The SDR (short-chain dehydrogenase/reductase and related enzymes) nomenclature initiative. Chem. Biol. Interact. 178, 94–98.

Bresell, A. & Persson, B. (2007) Characterization of oligopeptide patterns in large protein sets. BMC Genomics 8, 346.

Hedlund, J., Cantoni, R., Baltscheffsky, M., Baltscheffsky, H. & Persson, B. (2006) Analysis of ancient sequence motifs in the family of membrane-bound proton-pumping inorganic pyrophosphatases (H+-PPases). FEBS J. 273, 5183–5193.

Robins, T., Carlsson, J., Sunnerhagen, M., Wedell, A. & Persson, B. (2006) Structural model of human CYP21 based on mammalian CYP2C5 shows structural features to correlate with clinical severity of mutations causing congenital adrenal hyperplasia. Mol. Endocrin. 20, 2946–2964.

Kallberg, Y. & Persson, B. (2006) Prediction of coenzyme specificity in dehydrogenases/reductases. A hidden Markov model-based method and its application on complete genomes. FEBS J. 273, 1177–1184.

Research interests

One branch of our research regards development of algorithms and methods in bioinformatics that can be used to answer biomedically interesting problems. Another branch regards studies of gene/protein families, including structural aspects, in order to arrive at knowledge about their function and at the same time contributing to classification of parts of the huge protein world.

One of our ongoing projects regards investigation of differences at the genetic and proteomic levels between the two main types of heart failure (HF) — HF with reduced left ventricular ejection fraction (HFrEF; “the large dilated heart”) and HF with preserved left ventricular ejection fraction (HFpEF; “the small stiff heart”). This is part of the large study PREFERS, where genomics, proteomics, metabolomics and advanced imaging tools are used in an integrative fashion in order to clarify pathophysiologic mechanisms of HFpEF and HFrEF. The project is a collaboration with Cecilia Linde and Hans Persson at Karolinska Institutet and is funded by Astra-Zeneca.

Another project focuses on developing and using structural calculations to investigate mutational effects and for functional characterisation. With structural calculations techniques also considering protein stability in addition to measurements around the active site and analysis of conserved residues, the effect of a mutation can in many cases be predicted with good confidence.

Furthermore, we are working on protein classification, where we use hidden Markov models (HMMs) for functional assignments of protein families. We develop an automated strategy for such sub-classification tasks, making it possible to utilise these methods on large scale analyses. We have an emphasis on the two very large families SDR and MDR (short-chain and medium-chain dehydrogenases/reductases, respectively), which have been shown to be of central metabolic importance for all organisms.

Bengt Persson is also director of the SciLifeLab Bioinformatics Platform and Bioinformatics Short-term Support and Infrastructure (BILS).

Group members

Bengt Persson, prof., bengt.persson@scilifelab.se
Sarbashis Das, post-doc, sarbashis.das@icm.uu.se
Christoffer Frisk, project assistant, christoffer.frisk@icm.uu.se
Linus Östberg, Ph.D. student, linus.ostberg@scilifelab.se

Contact

bengt.persson@scilifelab.se

 

Last updated: 2022-11-30

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