Deep Learning for Single Cell Analysis

Project Summary

A team of students led by a computational biologist and a cell biologist will develop methods to identify cell subsets and their developmental, maturation and activation lineage relationships using deep learning approaches. Students will learn to process single cell RNA sequencing data and use the Python programming language and TensorFlow to characterize lung stem cells involved in wound healing. This work will help Duke researchers establish a deep learning pipeline for single cell analysis with applications in immunology, cell biology and cancer.

Themes and Categories
Contact
Paul Bendich
Mathematics
bendich@math.duke.edu

Disciplines Involved: Biology, Biomedical Engineering, PreHealth/PreMed, Biostatistics, all Quantitative STEM

Project Lead: Cliburn Chan

Project Manger: Kuei Yueh Ko

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