Fwd: U1331 Computational Oncology Hybrid Seminar: Pr. Mark GERSTEIN - July 21th 2025

Seminar

Computational Oncology (U1331)

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Mark GERSTEIN, Institute for Foundations of Data Science / Center for
Research Computing - Yale University (USA)

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Monday, July 21th 2025
11:00 am

Centre de Recherche - Paris Amphithéâtre Hélène Martel Massignac – 11
rue Pierre et Marie Curie, Paris 5e

+ Teams (see bottom of invitation

AI approaches for biomedicine: Cancer & Brain disorders

In this talk, I'll go over these two papers. My talk will focus on the
material in:

(1) Emani et al. (2024).

Single-cell genomics is a powerful tool for studying heterogeneous
tissues such as the brain. Yet little is understood about how genetic
variants influence cell-level gene expression. Addressing this, we
uniformly processed single-nuclei, multiomics datasets into a resource
comprising >2.8 millions nuclei from the prefrontal cortex across 388
individuals with various brain-related disorders and controls. Using
this, we built cell–type–specific gene regulatory and cell-to-cell
communication networks and an integrative deep-learning model that
accurately imputes single-cell expression and simulates perturbations.
The model prioritized ~250 disease-risk genes and drug targets with
associated cell types.

(2) Kumar et al. (2020).

I will also focus on the role of non-coding mutations in cancer.
As most know, the overwhelming part of the genome is noncoding, and
there are many somatic mutations in cancer in this region. It is still
debated the degree to which many of these mutations are under positive
selection and whether these mutations could represent either strong or
weak drivers and affect cancer progression

References

Single-cell genomics and regulatory networks for 388 human brains PS
Emani et al. (2024). Science 384: eadi5199.
Passenger Mutations in More Than 2,500 Cancer Genomes: Overall
Molecular Functional Impact and Consequences. S Kumar et al. (2020).
Cell 180: 915


Invited by:

Emmanuel BARILLOT

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eur25



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