Summary of 1. Introduction to Computational and Systems Biology

Summary of "Introduction to Computational and Systems Biology"

Main Ideas and Concepts

• Course Structure and Instructors:
  • The course covers computational and Systems Biology, with various undergraduate (7.36, 20.390, 6.802) and graduate (7.91, 20.490, HST, 6.874) versions.
  • Instructors include Professors Chris Burge, Fraenkel, Gifford, and guest lecturers such as George Church and Ron Weiss.
• Target Audience:
  • Graduate students with a solid biology background and comfort with quantitative approaches.
  • Upper-level undergraduates with similar backgrounds.
• Course Goals:
  • Develop foundational methods in Computational Biology to understand research literature.
  • Gain exposure to Computational Biology research through projects.
• Course Content Overview:
  • The course will include topics such as genomic analysis, modeling biological function, proteomics, regulatory networks, and computational genetics.
• Methodological Distinctions:
  • The course distinguishes between Computational Biology (using tools) and Bioinformatics (building tools).
  • It is not solely focused on Systems Biology or algorithm design.
• Historical Context:
  • The video outlines the evolution of Computational Biology from the 1970s to the present, highlighting key developments in sequence analysis, genome sequencing, and Bioinformatics algorithms.
• Motivating Questions:
  • Key questions include understanding genetic instructions, predicting gene expression, reconstructing evolutionary history, and discovering disease mechanisms.
• Project Component:
  • Graduate students will work in teams on research projects, developing ideas related to computational and Systems Biology.
• Exams and Grading:
  • Two non-cumulative exams will assess understanding, along with homework and project components contributing to the final grade.
• Resources:
  • A textbook is recommended but not required, and a probability and statistics primer is available for foundational support.

Instructions and Methodology

• Course Mechanics:
  • Familiarize yourself with the syllabus and due dates.
  • Engage in recitation sessions for additional support.
• Project Guidelines:
  • Form teams based on interests and backgrounds.
  • Submit project ideas, specific aims, and a final report detailing contributions from each member.
• Homework Policy:
  • Five problem sets will be assigned, and students can miss one without penalty.
  • Collaboration is encouraged, but solutions must be written independently.
• Examination Structure:
  • Exams will cover specific topics, with grading criteria outlined for both undergraduate and graduate versions.

Speakers and Sources

• Instructors:
  • Professor Chris Burge
  • Professor Fraenkel
  • Professor Gifford
• Guest Lecturers:
  • George Church
  • Ron Weiss
• Additional Contributors:
  • TAs: Peter Freese, Colette Picard, Tahin
  • Historical context references include Hallam Stevens for the history of Bioinformatics.

Notable Quotes

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Category

Educational

Video