02-251 Great Ideas in Computational Biology
02-251 COURSE PROFILE
|Special Permission Required? (If yes, see “Notes:)||No|
|Assessment Structure||Coursework will consist of the following components:
Homework assignments (30% of grade)
Homework assignments will comprise two parts.
Examinations (40% of grade)
The midterms and final exam will test your knowledge of the material from the class. The midterms will be held in class and the final will be held during the university’s scheduled time. The midterm dates are:
The midterms will not be cumulative: midterm 2 will cover material encountered after midterm 1. That having been said, later material in the class builds upon the earlier material, so it is important to know the earlier material.
The final will be comprehensive, i.e., it will cover all the material from the class.
Project (20% of grade)
We want this course to empower you to find your own great ideas in computational biology. Accordingly, you will complete a project analyzing a biological data set. We will provide more details about the project as the course progresses.
The final week of the course will feature in-class presentations at the end of the course. You will be graded on this presentation as well as a write-up describing your work.
Attendance and participation (10% of grade)
Attendance will be taken, and we will have occasional in-class exercises that serve to reinforce the concepts we have covered. These exercises will not be graded, but participation will be expected in order to receive a complete grade for that day.
You are allowed three “dropped” attendance grades without penalty. These can be used for any purpose.
|Most Recent Syllabus||https://www.cs.cmu.edu/~02251/syllabus_251.pdf|
|Course Goals/Objectives||This 12-unit course provides an introduction to many of the great ideas that have formed the foundation for the transformation of the life sciences into a fully-fledged computational discipline. This gateway course is intended as a first exposure to computational biology for first-year undergraduates in the School of Computer Science, although it is open to other quantitatively and computationally capable students who are interested in exploring the field. By completing this course, students will encounter a handful of fundamental algorithmic approaches deriving straight from very widely cited primary literature, much of which has been published in recent years. The course also introduces basic concepts in statistics, mathematics, and machine learning necessary to understand these approaches. Many of the ideas central to modern computational biology have resulted in widely used software that is applied to analyze (often very large) biolog- ical datasets; an important feature of the course is that students will be exposed to this software in the context of compelling biological problems.|
|Learning Resources||Canvas, Gradescope, Piazza|
|Pre-reqs, Cross List, Related||
The most common question we anticipate is, “How much biology do I need to know?” The reason we anticipate this question is that high school biology education is, in most places, boring and outdated. Although taking an introductory biology course concurrently cannot hurt, it is not required for this course, which is first and foremost a computational course.
Because of the course’s heavily quantitative and computational nature, we suggest the following prerequisite courses. We also suggest that students consider taking 15-122 (Principles of Imperative Computation) concurrently to guarantee strength in programming.
|Updated January 2019|