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Multimodal Single-Cell Data Integration + Q&A
Daniel Burkhardt · Smita Krishnaswamy · Malte Luecken · Debora Marks · Angela Pisco · Bastian Rieck · Jian Tang · Alexander Tong · Fabian Theis · Guy Wolf

Fri Dec 10 03:05 AM -- 03:25 AM (PST) @ None
in Competition Track Day 4: Overviews + Breakout Sessions »
Event URL: https://openproblems.bio/neurips_2021/ »

Scaling from a dozen cells a decade ago to millions of cells today, single-cell measurement technologies are driving a revolution in the life sciences. Recent advances make it possible to measure multiple high-dimensional modalities (e.g. DNA accessibility, RNA, and proteins) simultaneously in the same cell. This data provides, for the first time, a direct and comprehensive view into the layers of gene regulation that drive biological diversity and disease. In this competition, we present three critical tasks on multimodal single-cell data using public datasets and a first-of-its-kind multi-omics benchmarking dataset. Teams will predict one modality from another and learn representations of multiple modalities measured in the same cells. Progress will elucidate how a common genetic blueprint gives rise to distinct cell types and processes, as a foundation for improving human health.

Author Information

Daniel Burkhardt (Yale University)
Smita Krishnaswamy (Yale University)
Malte Luecken (Helmholtz Center Munich)

* Computational biologist * Multimodal single-cell data integration challenge organizer * Single-cell data integration * Benchmarking

Debora Marks
Angela Pisco
Bastian Rieck (Institute of AI for Health, Helmholtz Centre Munich)
Jian Tang (Mila)
Alexander Tong (Yale University; MILA; UdeM)
Fabian Theis (Helmholtz Munich)
Guy Wolf (Université de Motréal; Mila)

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