The protein folding problem ... no longer a problem? January 27, 2021, KBM, NMBU.
 A brief account of my sabbatical at University of California, Davis. November 4, 2020, KBM, NMBU.
 Regulatory evolution after whole genome duplication. TriLab meeting, December 13, 2019, UC Davis, USA.
 Gene co-expression network connectivity is an important determinant of selective constraint.
Integrative Genetics & Genomics Graduate Seminar, October 21, 2019, UC Davis, USA.
 Fish ’n’ Chips: Comparative methods for the analysis of gene expression evolution.
Genome Center Faculty Seminars, October 9, 2019, UC Davis, USA.
 Gene co-expression network connectivity is an important determinant of selective constraint. Max Planck Institute of Molecular Plant Physiology, February 7, 2019, Golm, Germany.
 Regulatory evolution after whole genome duplication. Third annual conference of NORBIS, November 8-10, 2017, Sommarøy, Tromsø.
 The transcriptome of wood formation. 50 Years Plant Science in Umeå Symposium, Agust 21-23, 2017, Umeå, Sweden.
 Gene co-expression network connectivity is an important determinant of selective constraint. Evolution, June 23-27, 2017, Portland, USA.
 Computational methods for studying the evolution of gene regulation. PhD/Post Doc workshop at Klækken, September 9-10, 2016, Klækken, Norway.
 Comparative regulomics: computational approaches to reveal the evolution of transcriptional regulation. Next Generation Sequencing Symposium, December 10-11, 2015, Helsinki, Finland.
 Seeing the forest for the trees in omics data; examples from aspen and spruce genomics projects. Norwegian Biochemical Society seminar series, April 9, 2015, NMBU, Norway.
 Comparative network analysis of gene regulation in conifers. 2nd Conifer Genome Summit, 16-18 June 2014, Quebec, Canada.
 Comparative Analysis of Gene Regulatory Networks in Plants. Swedish University of Agricultural Sciences. March 28th, 2014, Uppsala, Sweden.
 Comparative Analysis of Gene Regulatory Networks in Plants. Plant & Animal Genome XXII Conference. January 11-15, 2014, San Diego, USA.
 Systems analysis of the Picea abies transcriptome. The 2013 Conifer Genome Sequencing Summit, Björkliden, June 14 - 17, 2013, Lapland, Sweden.
 Comparative analysis of gene regulatory network in plants. Computational Life Science (CLS) seminar, University of Oslo, May 5th, 2013, Oslo, Norway.
 Comparative analysis of gene regulatory network in plants. Symposium: The evolving landscape of bioinformatics, Uppsala University, April 5th, 2013, Uppsala, Sweden.
 Comparative analysis of gene regulatory network in plants. Computational Biology Group at the Faculty of Mathematics, Informatics and Mechanics, University of Warsaw, February 27th, 2013, Warsaw, Poland.
 Comparative network analysis of Arabidopsis, Rice and Populus. CIGENE seminar series, Norwegian University of Life Sciences, December 12, 2012, Ås, Norway.
 Is biology more than stamp collecting? Trial lecture for appointment as a docent, Umeå University, March 30th, 2012.
 Complexity and conservation of regulatory networks in plants. The 4th UPSC-INRA (UPRA) bilateral meeting, March 26 – 28th, 2012, Umeå, Sweden.
 The systems biology of aspen wood development, International Conference on Metabolomics & Systems Biology, February 20-22th, 2012,San Francisco, USA.
 Complexity and conservation of regulatory networks in plants; a systems biology approach, Merced University, February 17th, 2012, Merced, USA.
 A systems biology view to the regulatory genomes of plants, Max Planck Institute of Molecular Plant Physiology, September 13th, 2011, Golm-Potsdam, Germany.
 The regulatory network of trees: a comparison of traditional bioinformatics approaches and systems biology, Institute of Biotechnology, April 30, 2010, Vilnius, Lithuania.
 A systems biology approach to model the transcriptional network in trees. Third UPRA Meeting on Plant Integrative Biology, UPRA (European Open Laboratory UPSC and INRA), November 25 – 27, 2009, INRA Nancy Research Centre, Champenoux, France.
 A systems biology approach to model the transcriptional and metabolic network in Populus, 3rd Joint meeting Riken, Golm, UPSC, September 16-18, 2009, Umeå, Sweden.
 Local descriptors of protein structure: A universal approach to protein structure representation, Stockholm Bioinformatics Centre (SBC), September 10th, 2009, Stockholm, Sweden.
 A systems biology approach to model the transcriptional network in trees, Seminar on novel approaches in physical biology and bioinformatics, May 20, 2009, Warsaw, Poland.
 Predicting gene function from gene expression trends, protein features and cis-regulatory information –A rough set modeling approach, IGK Workshop: Data driven modelling and optimization, December 15-16, 2008, Warsaw, Poland.
 Dissecting regulatory control in Yeast using rule-based learning, Invited talk at the Norwegian University of science and technology, Bioinformatics seminar series, March 6th, 2008, Trondheim, Norway.
 Towards computational inference of cellular interaction networks, Invited talk at the Umeå Plant Science Centre, December 4th, 2007, Umeå, Sweden.
 From sequence to structure to function: towards new approaches to protein function prediction, Invited talk at the Biotech Centre of Oslo, June, 2006, Oslo, Norway.
 Predicting molecular function from local descriptors of protein structure, 5th Swedish Bioinformatics Workshop for PhD students and Postdocs, November 26-27, 2004, Lund, Sweden.
 Discovering regulatory binding site modules using rule-based learning, Workshop: Regulatory Sequence Motif Discovery, May 6-7, 2004, Uppsala, Sweden.
 A novel approach to fold recognition using sequence-derived properties from sets of structurally similar local fragments of proteins, European Conference on Computational Biology, September 27-30, 2003, Paris, France.
 Protein fold prediction using sequence based features from local structures, 3rd Annual Workshop in Bioinformatics for PhD Students and PostDocs, November 22-23, 2002, Stockholm, Sweden.
 Studying Bioinformatics, Inauguration Day of The Linnaeus Centre for Bioinformatics, November 6th, 2002.
 A Method Based on Rough Set Supervised Learning used to Predict the Biological Function of Unknown Genes from DNA Microarray Gene Expression Data, Seminar in Medical Technology, May 10, 2001, Trondheim, Norway.
 A framework for learning gene functions from microarray data, NBS Vintermøte 2001 - 37. Norwegian Biochemical Society’s Wintermeeting, Beitostølen.
 Predicting Gene Function from Gene Expressions and Ontologies, First annual workshop for PhD students and postdocs in Bioinformatics, November 16, 2000, Uppsala, Sweden.
 A Methodology for Knowledge Discovery from Gene Expressions, Workshop 3: Knowledge Discovery in Biology, The Fourth European Conference on Principles of Data Mining and Knowledge Discovery (PKDD'2000), September 13, Lyon, France.