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 here. 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: Learning cell communication from spatial graphs of cells - Node centric expression models (NCEM)
6 July 2022 5:30 p.m. - 6:30 p.m. Central European TimeSpeaker: Anna Schaar, Helmholtz Zentrum Munich
Abstract:Spatial molecular profiling assays have enabled single-cell genomics to move from studying tissue heterogeneity to tissue organization, providing new avenues to study cellular communication within a tissue. Yet, with the new information comes additional complexity: deriving insights from this data requires a new set of analysis tools. We present a computational method based on graph neural networks which reconciles disentanglement of gene expression variation and cell communication modeling: node-centric expression modeling (NCEM). The NCEM approach is not limited to targeted spatial transcriptomics data, but can be extended to spot transcriptomics if within-cell-type variation can be recovered in deconvolution analyses. The statistical cell–cell dependencies discovered by NCEM are plausible signatures of known molecular processes underlying cell communication. We show that NCEM's cell type coupling analysis workflow and the identification of receiver and sender effects across multiple datasets finds plausible putative dependencies and niche-dependent cell state variation on the example of human lymph nodes, inflamed colon and colorectal cancer in both targeted and spot transcriptomics data.
Upcoming speakers
- 1 June 2022 - Yoshua Bengio, Université de Montréal, Mila – Quebec Artificial Intelligence Institute
Previous speakers
- 1 June 2022 - Yoshua Bengio, Université de Montréal, Mila – Quebec Artificial Intelligence Institute
- 4 May 2022 - Francesco Paolo Casale, Helmholtz Pioneer Campus, Helmholtz Zentrum Munich
- 6 April 2022 - Kyle Farh, Head of Artificial Intelligence Lab, Illumina, San Francisco Bay Area
- 2 March 2022 - Jonathan Frazer & Mafalda Dias, Debora Marks Lab, Harvard Medical School, Boston
- 2 February 2022 - Benjamin Schubert, Helmholtz Zentrum, Munich
- 1 December 2021 - Annalisa Marsico, Helmholtz Zentrum, Munich
- 3 November 2021 - Žiga Avsec, DeepMind, London
- 6 October 2021 - Mohammad Lotfollahi, Helmholtz Zentrum, Munich
- 1 September 2021 - Ansh Kapil, AstraZeneca, Munich
- 4 August 2021 - Christina Leslie, Sloan Kettering Institute, New York
- 7 July 2021 - Qiangfeng Cliff Zhang, Tsinghua University, Beijing
- 2 June 2021 - Johannes Linder, University of Washington, Seattle
- 5 May 2021 - Anshul Kundaje, Stanford University, Stanford
- 7 April 2021 - Yingxin Cao, UC Irvine, Irvine
- 3 March 2021 - Avanti Shrikumar, Stanford University, Stanford
- 3 February 2021 - Uwe Ohler, Max-Delbrück-Center for Molecular Medicine, Berlin
- 2 December 2021 - Ron Schwessinger, Radcliffe Department of Medicine, Oxford
- 4 November 2020 - David Kelley, Calico, San Francisco
- 7 October 2020 - Vikram Agarwal, Calico, San Francisco
The scientific committee
- Julien Gagneur, Technical University Munich, Munich
- Annalisa Marsico, Helmholtz Zentrum Munich, Munich
- Johannes Linder, Stanford University, Stanford
- Laura Martens, Technical University Munich & Helmholtz Zentrum Munich, Munich