1. Introduction to Computational and Systems Biology

About this Video

• Video Title: 1. Introduction to Computational and Systems Biology
• Channel: MIT OpenCourseWare
• Speakers: Professor Chris Burge, Professor David Gifford, Professor Ernest Fraenkel, (and other guest lecturers mentioned)
• Duration: 01:06:11

Introduction

This introductory lecture to Computational and Systems Biology provides an overview of the course content, structure, and mechanics. It also presents a brief, anecdotal history of the field to contextualize the material. The lecture aims to clarify course details and ensure student understanding of the course structure and expectations.

Key Takeaways

• Course Structure: The course is divided into six topics: Genomic Analysis I & II, Modeling Biological Function, Proteomics and Protein Structure, Regulatory Networks, and Computational Genetics. Guest lecturers will contribute to several topics.
• Course Goals: The course aims to develop a foundational understanding of computational biology methods, enabling students to comprehend research literature in the field. Graduate students will also gain research experience through a project component.
• Target Audience: The graduate course targets students with solid biology backgrounds and comfort with quantitative approaches. Undergraduate courses also require a solid biology background and quantitative skills.
• Course Components: The course includes lectures, problem sets (with a flexible grading system allowing for some missed work), recitations (strongly recommended), a project (graduate students only), exams (two non-cumulative exams), and peer review of student presentations.
• Project Component (Graduate Students Only): Graduate students will undertake a research project in teams, progressing through stages with instructor feedback (initial team formation, project proposal, research strategy, final report, and presentation).