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What’s in a Cell? Discovering Disease Mechanisms with Single-cell Transcriptomics
Maarten de Vries
Maarten de Vries
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What’s in a Cell? Discovering Disease Mechanisms with Single-cell Transcriptomics

Analyze single-cell transcriptomics data using Python and machine learning techniques to uncover novel disease mechanisms.

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Apply now
Tuesdays
 at
6:00
P.M.
 ET /
3:00
P.M.
PT
8 weeks, 2-3 hours per week
Intermediate
No experience required
No experience required
Some experience required
Degree and experience required

Description

Single-cell genomics is revolutionizing computational biology and drug development by providing detailed insights into cellular functions. Increasingly large mountains of transcriptomic data have been generated over the past few years, and its secrets are waiting to be unlocked!

In this Build Project, you'll assume the role of a Computational Biologist, analyzing single-cell transcriptomics data to identify novel disease mechanisms. Under the guidance of an industry expert, you will retrieve, clean, and process omics data, apply machine learning models for data analysis, and produce scientific figures. You will gain hands-on experience with tools and methodologies commonly used in the field, all within a simulated professional environment.

Session timeline

  • Applications open
    September 5, 2024
  • Application deadline
    September 19, 2024
  • Project start date
    Week of July 8, 2024
    Week of
    October 7, 2024
  • Project end date
    Week of

What you will learn

  • Retrieve and process publicly available single-cell omics data using Scanpy.
  • Perform data analysis using Python and machine learning techniques.
  • Create visualizations and reproducible scientific figures.
  • Develop a comprehensive analysis pipeline in Jupyter Notebooks.
  • Present findings in a professional scientific format.
Build Projects are 8-week experiences that operate on a rolling basis. Selected participants engage in weekly live workshops with a Build Fellow and 2-15 other students.

Project workshops

1
Introductions & Setup
2
Data Retrieval and Cleaning
3
Dimensionality Reduction and Visualization
4
Clustering and Annotation
5
Compositional Analysis
6
Batch Effect Correction
7
Differential Gene Expression
8
Present deliverables and reflect

Prerequisites

  • Basic Python programming (classes, functions)
  • Experience running interactive code notebooks (e.g. Jupyter, R Markdown)
  • Basic understanding of cell biology (first-year college level).
  • Experience with reading scientific papers.

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About the expert

Hi! I am Maarten, and I am a computational biologist working in a biotech company. I graduated from Harvard with a degree in Statistics. In my free time, I like programming and weightlifting.

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