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Project Descriptions
Spring 2025

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Decoding the Role of Long Non-coding RNAs in Stem Cell Pluripotency

Peng He, Professor  
UC San Francisco  

Applications for Spring 2025 are closed for this project.

This project investigates the fascinating world of long non-coding RNAs (lncRNAs) and their crucial role in maintaining stem cell pluripotency. While most RNA molecules are known to encode proteins, lncRNAs represent a mysterious class of RNAs that regulate gene expression through various mechanisms. This research focuses on understanding how specific lncRNAs control the unique properties of embryonic stem cells - their ability to self-renew and develop into any cell type in the body.
Using cutting-edge genomic approaches, our lab has generated comprehensive sequencing data from mouse embryonic stem cells where specific lncRNAs have been knocked out. This project will analyze this data to understand how the loss of these lncRNAs affects cellular identity and differentiation potential, comparing these changes to normal developmental patterns observed in mouse embryo development (gastrulation).

Qualifications: Data Analysis Tasks:

Perform convolution analysis to determine changes in cell population composition
Compare knockout conditions against a published mouse gastrulation atlas
Conduct hierarchical clustering analysis to identify altered gene expression programs
Create comprehensive visualizations of the results
Document analysis workflows and findings

Learning Outcomes:

Master fundamental concepts in stem cell biology and developmental genetics
Gain practical experience in bioinformatics and computational biology
Develop proficiency in analyzing large-scale genomics datasets
Learn to integrate and compare datasets with published scientific literature
Understand the principles of gene regulation and cellular identity
Acquire skills in scientific documentation and data visualization

Required Qualifications
The ideal candidate should possess:
Technical Skills:

Basic programming experience (R or Python)
Familiarity with statistical analysis
Experience with data visualization
Basic understanding of genomic data analysis is a plus

Day-to-day supervisor for this project: Konstantinos Stasinos, Post-Doc

Hours: to be negotiated

Off-Campus Research Site: on site/hybrid/remote work all possible

Related website: https://profiles.ucsf.edu/peng.he
Related website: https://profiles.ucsf.edu/peng.he

 Engineering, Design & Technologies   Biological & Health Sciences

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