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MCB 536

Tools for Computational Biology

Today's objectives

  • Locate information relevant to the course (lecture materials, assessment, communication streams)
  • Identify range of skills and concepts covered in this course

Communication

Slack Workspace: TFCB_2023

  • #general: course announcements (please turn on notifications for this channel)
  • #lectures-homeworks: questions about course content and help for homework
  • see pinned posts in each channel for quick links and reminders

Today's instructor

  • Rasi Subramaniam
  • Associate Professor in Basic Sciences & Computational Biology @FredHutch
  • Research Area: mRNA Translation
  • http://rasilab.fredhutch.org/

Teaching assistants & office hours

Nashwa Ahmed Sarah Huang
Wed 11AM-12PM Thu 2PM-3PM
Steam Plant Building, Fred Hutch S2-135 (2nd floor)

Zoom (see Slack for link)

Instructors

Melody Campbell Phil Bradley Maggie Russell
Elizabeth Humphries Manu Setty Rasi Subramaniam

Computational Biology & Translational Data Science Programs

Introduce yourself!

  • Name
  • Research interests (type of data, model organism, research questions, etc)
  • Programming background (Python, R, Unix/Bash, etc.)
  • What are you hoping to get out of this course?

Course objectives

By the end of the course, you should be able to:

  • Use VSCode to program in Unix/Bash shell, Python, R using appropriate syntax and code convention

  • Apply good practices for computational research including project and data organization

  • Select appropriate tools to perform specific programming and data analysis tasks

  • Analyze common forms of data generated by molecular biology experiments such as flow cytometry, 96-well plate readers, and high throughput sequencing.

What you won't be able to do

  • Use ALL of the computational tools your research will require

  • Know the best algorithm or analysis method for a specific research question

  • Code with expert-level skills

... but you should be equipped to work towards these goals on your own.

Course website

Syllabus, lectures, homeworks

Rendered materials (prettier/easier to view):
https://fredhutch.github.io/tfcb_2023/

Original GitHub repository: https://github.com/fredhutch/tfcb_2023

Homeworks

Submit through Canvas
MCB 536 A Au 23 Tools For Computational Biology

Eight assignments (10% each) + participation (20%)

Before next class

  • Install all required software and be prepared with questions!