Computational Stem Cell Biology EN580.447/647

This is the fifth year we have offered this course. In the past, it was designed to provide a mechanistic and systems biology-based understanding of the two defining features of stem cells: multipotency and self-renewal. We explored these concepts across several contexts and perspectives, emphasizing seminal and new studies in development and stem cell biology, and the critical role that computational approaches have played. Now, we are shifting the content to a more equal balance between computational and biological content. We will teach you how to analyze single cell OMICs data, using questions and data from stem cell biology and developmental biology to provide the motivatational background. Upon sucessful completion of this course, you will be a ninja of sc omics analysis.

Topics (in no particular order)

  • History of stem cells

  • Introduction to Python

  • Central dogma & gene regulation

  • Single cell RNA-Seq

  • Cell type identity

  • Stem cell niche

  • Cell-cell interactions

  • Spatial transcriptomics

  • Lineage tracing

  • “Stemness”

  • Trajectory infererence

  • RNA velocity

  • Gene regulatory networks

  • Cell fate engineering

  • Single cell epigenomics

  • Cancer stem cells

  • Stem cell controversies

The Team

  • Instructor

  • TAs

    • Eric Kernfeld (ekernfe1 at jhmi dot edu)

    • Dan Peng (dpeng5 at jhmi dot edu)

Grading

This class is heavily weighted by weekly individual computational homeworks (75%). There is one final team project that has written, coding, and verbal presentiation components (25%).

Prerequisites

Some college-level biology is assumed. Familiarity with Python is preferred, but we will try to teach you enough Python to be dangerous.

Policies

  • Lecture materials

    • Slides posted to Blackboard

    • Videos of lectures posted to Blackboard (see link above)

    • Materials posted to Blackboard are only for registered students (including those auditing)

    • Lectures notes & Jupyter Notebooks are on this site (see navigation bar)

  • Homework:

    • Weekly

    • Posted Friday morning

    • Due following Wed by 11:59pm

    • Submit homeworks via email to compscbio@gmail.com

    • Submit both Jupyter Notebooks and HTML

    • Name your files according to HW number. So your files for homework 1 should be named:

      • lastname_firstname_1.ipynb

      • lastname_firstname_1.html

    • You need to annotate your code to explain your reasoning and interpretation.

    • If expectations are not clear from the assignment, ask the TAs.

    • We only count the top 10 homeworks toward your final grade

  • Collaboration

    • Feel free to discuss homeworks with your classmates. But, the work that you turn in must be your own work. If you collaborate with a classmate(s), please list them in your submission. We define collaborate here to mean to discuss solutions. Searching for answers from prior years or from similar exercises on the web is not allowed.

  • ‘No questions asked’ free days

    • You have a total of 6 ‘grace’ days for your homeworks. What this means is that you can turn in a homework after the due date, as long as you have not expended all of your grace days. If you turn in a homework 1 hour late, you have used one of your grace days. If you turn in a homework after all of your grace days have been expended, you will receive a 0 for that homework. We do not ask for explanations when you use grace days. Grace days do not apply to the final project

  • Extentuating circumstances

    • We live in a new world, and there are circumstances that precipitate despite our best laid plans. If you find yourself a victim of the whims of the universe (e.g. health-related issues), please email the team to get an ‘extenuating circumstances’ extension. No extensions will be granted for the final project

Schedule

Lectures:

Homework