Reconstructing dynamic regulatory networks from time series single cell data
, Carnegie Mellon University (CMU)
Date: Wednesday, May 06, 2020
Time: 11:30 AM to 1:00 PM Note: all times are in the Eastern Time Zone
Location: Zoom Meeting ID 540212779 Password 759321
Event Type: Seminar
Host: Bonnie Berger, CSAIL & Mathematics
Contact: Patrice Macaluso, 617-253-3037, firstname.lastname@example.org
Speaker URL: None
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TALK: Reconstructing dynamic regulatory networks from time series single cell data
Biological processes, including those involved in immune response, disease progression and development, are often dynamic. To fully understand and model regulatory networks that are activated as part of these processes requires the integration of static and times series bulk and single cell data. I will discuss statistical and active learning methods for designing experiments for studying such systems and methods using continuous state hidden Markov models for the analysis and integration of profiled data. An application of these methods for improving protocols for the differentiation of iPSCs to lung cells will be presented.
Created by Patrice Macaluso at Tuesday, April 21, 2020 at 2:54 PM.