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Activity Number: 535 - Contributed Poster Presentations: Section on Statistics in Genomics and Genetics
Type: Contributed
Date/Time: Wednesday, August 1, 2018 : 10:30 AM to 12:20 PM
Sponsor: Section on Statistics in Genomics and Genetics
Abstract #330171
Title: Single Cell Data Mining of Live Cell Epigenetic Modifications
Author(s): Chris Bryan*
Companies:
Keywords: Machine ; learning; epigenetics; image; analysis; cell
Abstract:

Epigenetics is the study of heritable changes in cells that do not involve DNA sequence, and aberrant changes are often associated with diseases. These modifications can be quantified in live cells using fluorescent probes. Using image analysis software, visual measurements of the cell such as nucleus area and intensity can be taken and analyzed using statistical software. We hope to devise a statistical model using machine learning algorithms that can accurately identify cell phenotypes using image analysis. This document is based upon work supported by the National Science Foundation under Grant No. 1246818.


Authors who are presenting talks have a * after their name.

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