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Jesper Tegnér

Professor, Bioscience and Computer Science

Biological and Environmental Science and Engineering Division


Living Systems Laboratory

Affiliations

Education Profile

  • ​​​​​​​​​Wenner-Gren Postdoctoral Fellow, Center for Biodynamics, Boston, 2001
  • Alfred P Sloan & Wenner-Gren Postdoctoral Fellow, Sloan Center for Computational Neuroscience, Boston, 1998-2000
  • Postdoc, Karolinska Institutet, 1997-1998
  • Ph.D. Medicine/Medicine Doctor, Karolinska Institutet, 1997
  • Advanced Ph.D. courses in pure and computational mathematics (corresponding 2 years full time), Royal Institute for Technology & Stockholm University, 1992-1996
  • B.Sc. Medicine (Med Kand, Physician Program), Karolinska Institutet, 1990
  • B.Sc. Philosophy, Stockholm University, 1990
  • B.Sc. Mathematics, Stockholm University, 1988

Research Interests

Professor Tegnér is interested in decoding molecular circuits of living systems with special reference to collective dynamics of single cells and populations thereof. Our assumption is that adaptive molecular circuits in living systems hold secrets to new properties beyond what is readily apparent from the fundamental equations of matter.
Using T-cells, of fundamental importance for human health, as a model system, Professor Tegnér's team practices an integrative experimental and computational approach, guided by theory, asking:
  • what defines the identity of a cell? 
  • what are rules and dynamical equations governing genomic and cellular circuits? 
  • how are such circuits regulated and to what extent can they be reprogrammed? ​ 

Professor Tegnér and his team are intrigued by the fundamental challenge of discovering principles of natural adaptive computation, essentially protecting living organisms from lapse into atomic chaos. Such algorithms, inspired from living systems, could be harnessed in the design of novel technologies, innovations, medical applications, and ultimately in crafting general reasoning systems.

Selected Publications

  • Venkateshan Kannan, Fredrik Swartz, Narsis A. Kiani, Gilad Silberberg, Giorgos Tsipras, David Gomez-Cabrero, Kristina Alexanderson, and Jesper Tegner, Predictive Disease Transitions from Longitudinal Health Care Cohort Data using Layered Network Construction, Scientific reports, 2016, doi:10.1038/srep26170
  • A.Schmidt, Ming-Mei Shang, Rubin Joshi, Shasina Iqbal, Casper Wahlund, Susanne Gabrielsson, Robert A. Harris and J. Tegnér, Human M2 macrophages induce CD4+Foxp3+ Treg-like cells via TGF-β Immunology and Cell Biology, 10 May 2016
  • Hector Zenil, Narsis, Kiani, Jesper Tegnér, Methods of Algorithmic Information Theory for network biology, Seminars of Developmental and Cell Biology March 51: 32-43, 2016
  • Hill, S. et al.  Empirical assessment of causal network learning through a community-based effort Nature Methods, 13, 310-318, 2016.
  • V. Rodríguez-Cortez, L. Pino-Molina, J. Rodríguez-Ubreva, L. Ciudad, D. Gómez-Cabrero, C. Company, J. Urquiza, J. Tegnér, C. Rodríguez-Gallego, E. López-Granados, E. Ballestar Monozygotic twins discordant for common variable immunodeficiency reveal impaired DNA demethylation during naïve-to-memory B-cell transition Nature Communications 6/17, 2015.