Learning From Large-Scale (Single-Cell) ‘Omics’

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United States Simons Institute for the Theory of Computing
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Published on ● Video Link: https://www.youtube.com/watch?v=mLqq-DsYi04


Duration: 33:36
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5

Lior Pachter (Caltech)
https://simons.berkeley.edu/talks/tbd-457
Computational Challenges in Very Large-Scale 'Omics'

I will discuss several computational challenges that must be addressed in order to learn biophysically meaningful representations of cells from large-scale single-cell ‘omics’ data. I will discuss some progress we have made in attempting to address the challenges by way of developing a commons cell atlas framework for large-scale (isoform) resolved single-cell analysis, and explain how analysis of large-scale data can inform biophysical models of cells.



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Tags:
Simons Institute
theoretical computer science
UC Berkeley
Computer Science
Theory of Computation
Theory of Computing
Computational Challenges in Very Large-Scale 'Omics'
Lior Pachter