Kipoi - Seminar

The monthly virtual seminar series is designed as a platform for interested Kipoi users and developers and will host talks on the applications of deep learning on biological data. The seminar is held on every first Wednesday of the month at 5:30 p.m. - 6:30 p.m. CET. We are also happy to share the recordings of the seminar on YouTube.

How to take part

The Virtual Seminar Series takes place via Zoom. To take part in the seminar, you can register for the online Zoom conference. Your personal join link will be valid for all upcoming lectures of the series.


How to apply as a speaker

The seminar is a great opportunity to present your recent work to a large international audience. If you want to apply as a speaker, please use the contact in the registration confirmation email.

Next seminar

Title: Machine learning models of differential gene expression
5 June 2024 5:30 p.m. - 6:30 p.m. Central European Time

Speaker: Sara Mostafavi, University of Washington


Our genomes contain millions of cis-regulatory elements, whose differential activity determines cellular differentiation. The majority of disease causing genetic variants also reside in these regulatory elements, impacting their regulatory function in a subtle and context-dependent manner. In this talk, I’ll present recent work from us and others on applying sequence-based deep learning models for predicting and explaining regulatory function(s) from genomic DNA. I'll describe our efforts in adapting these models for studying how natural genetic variation impacts cellular function, highlighting current challenges. Motivated by these results, I will describe our ongoing work in improving models' causal interpretation of non-coding genetic variation, which is required to accurately predict differential gene expression across individuals. In summary, our work shows that sequence-based deep learning approaches can uncover regulatory mechanisms while providing a powerful in-silico framework to mechanistically probe the relationship between regulatory sequence and its function.

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