Using high content analysis and deep learning to make the most of your microscopy

Jointly hosted with the Center for Computational Biomedicine (CCB)
Seminars are usually made available on YouTube shortly afterwards.

  • Date: Monday, December 11th, 2023
  • Time: 10:00 - 11:00 AM EDT
  • Speaker: Beth Cimini, PhD. Broad Institute, Boston, MA.
  • Topic: Using high content analysis and deep learning to make the most of your microscopy
  • Location: Gordon Hall 106 Waterhouse Conference Room
    • Coffee and cookies available on site
  • Virtual: Zoom link
    • Coffee and cookies is your own responsibility
  • Abstract: In the age of the digital camera, microscopy images constitute a fantastically rich source of quantiative data. Yet, it currently remains difficult for most scientists to mine quantitative data from these images easily such that they can answer their important biological questions. In this talk, we will discuss open source tools that make quantitative image analysis both easier and more reproducible, as well as bioinformatic approaches allowing users to extract novel connections from their data.
  • Bio: Dr. Beth Cimini is the Associate Director for Bioimage Analysis and a CZI Imaging Scientist in the Imaging Platform at the Broad Institute in Cambridge, MA.  She obtained a PhD in Biochemistry and Molecular Biology with Dr. Elizabeth Blackburn at UCSF, studying splicing variants of the telomere master scaffolding protein TIN2.  This work honed her interests in image analysis, leading her to postdoctoral and staff scientist roles with Dr. Anne Carpenter’s lab at the Broad, leading a team collaborating with ~30 outside scientists per year on custom image analysis projects.  The Cimini lab focuses on bioimage analysis tool creation (Piximi) and maintenance (CellProfiler), as well as on applying open source tools to novel biological problems.  She created and directs the Platform’s Postdoctoral Training Program in Bioimage Analysis, and also leads the Broad efforts on community engagement and technology development for the Center for Open Bioimage Analysis (COBA).
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