Principal Computational Researcher

Jonathan Desponds

Cancer Immunology

“I am passionate about bringing innovative therapeutic solutions to patients using advanced methods in applied mathematics, computational biology and machine learning.”

Your role at Institut Roche and brief presentation of your professional background:

I joined Institut Roche in 2021 as a postdoctoral researcher in computational biomedicine. In 2022, I joined the cancer immunology group at Genentech as a principal computational researcher. My role is to create computational tools that help develop new immune therapies for cancer patients and improve existing treatments.

My Focus at Institut Roche:

At Institut Roche, through my affiliation with Genentech, I strive to improve our understanding of T cell function in their interaction with cancer neoantigens. More specifically, I design computational tools to infer or predict how strong of an immune response a T cell receptor peptide-MHC pair triggers.

  1. Desponds, J., et al (2021). “Population dynamics of immune repertoires” in Mathematical, computational and experimental T cell immunology, Springer
  2. Desponds, J., et al. (2020). “A mechanism for hunchback promoters to readout morphogenetic positional information in less than a minute.” Elife 9.
  3. Gaimann, M. U., et al. (2020). “Early life imprints the hierarchy of T cell clone sizes.” Elife
  4. Carballo-Pacheco, M., et al. (2019). “Receptor crosstalk improves concentration sensing of multiple ligands.” Phys Rev E 99(2-1): 022423.
  5. Tran, H., et al. (2018). “Precision in a rush: Trade-offs between reproducibility and steepness of the hunchback expression pattern.” PLoS Comput Biol 14(10): e1006513.
  6. Desponds, J., et al. (2016). “Fluctuating fitness shapes the clone-size distribution of immune repertoires.” Proc Natl Acad Sci U S A 113(2): 274-279.
  7. Ferraro, T., et al. (2016). “New methods to image transcription in living fly embryos: the insights so far, and the prospects.” Wiley Interdiscip Rev Dev Biol 5(3): 296-310.
  8. Desponds, J., et al. (2016). “Precision of Readout at the hunchback Gene: Analyzing Short Transcription Time Traces in Living Fly Embryos.” PLoS Comput Biol 12(12): e1005256.
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