Johan Henriksson

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Johan Henriksson2022-08-30T10:53:16+02:00

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Affiliate Group Leader.

Understanding biology by developing new technology. Dancer and tinkerer.

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Johan Henriksson’s research focuses on developing methods such that we can understand gene regulation. This involves a wide take on the topic, including research on the word “understanding” itself.

Johan was born in Dalarna, Sweden, with two parents both running their own companies. He taught himself programming and linear algebra to be able to write games, and spent too much of his childhood on IRC. Later at university he pursued mechanical engineering at Chalmers university to be able to take over the family business. This however derailed into getting a degree in mathematics, taking all the courses in computer science, and running a nuclear reactor in japan while at it. Ironically, after avoiding all courses in biology, he did a PhD studying transcription factors at Karolinska Institutet, developing image analysis tools. However, too impatient for generating enough data using microscopy, he then followed up with a postdoc at the Wellcome Sanger institute, Cambridge, funded by Vetenskapsrådet. There he taught himself how to pipette and developed the first retroviral CRISPR library, and got into single-cell technology.

In 2019, Johan was recruited as a group leader to MIMS, the Nordic EMBL partnership node hosted at Umeå. Having experienced that our cognitive ability and cultural biases are the primary limitations for “finishing” biology as a topic, he has gone back to his systems biology and engineering roots. His program consists of developing methods for massive and systematic data collection, and developing analysis methods that can make the most of the data. The latter includes machine learning and an epistemology based on optimally subjective Bayesian statistics. The primary application is on T cells for immunotherapy, with an autoethnographic twist.

Johan spends his free time mainly dancing and crafting, but otherwise only has one interest: collecting more interests.

Current Projects

  • Improving immunotherapy and CAR T cell resistance to the tumor microenvironment

  • Improving CRISPR screening methods

    with Yuri Schwartz

  • Novel uses of multimodal single-cell data

    with Mattias Forsell

  • Alternative formulations of Variational Autoencoders for single-cell analysis

    with Tommy Lofstedt

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