Computational Biology

Computational biology involves the analysis and discovery of biological phenomena using computational tools, and the algorithmic design and analysis of such tools. The field is widely defined and includes foundations in computer science, applied mathematics, statistics, biochemistry, molecular biology, genetics, ecology, evolution, anatomy, neuroscience, and visualization.

The doctoral program is interdepartmental and the result of a collaboration between the four academic units that comprise the CCMB:  Applied Mathematics, Computer Science, Ecology & Evolutionary Biology, and Molecular Biology, Cell Biology & Biochemistry.

The Undergraduate program offers four possible tracks: computational genomics, biological sciences, molecular modeling and applied mathematics and statistical genomics. The program requires a senior capstone experience that pairs students and faculty in creative research collaborations.

Standard program for the Sc.B. degree

Prerequisites
MATH 0100Introductory Calculus, Part II (or equivalent)1
or MATH 0170 Advanced Placement Calculus
BIOL 0200The Foundation of Living Systems (or equivalent)1
General Core Course Requirements: Biology
BIOL 0470Genetics (prerequisite BIOL 0200 or equivalent)1
BIOL 0280Introductory Biochemistry1
or BIOL 0500 Cell and Molecular Biology
General Core Requirements: Chemisty
CHEM 0330Equilibrium, Rate, and Structure1
General Core Requirements: Computer Science2-4
Introduction to Object-Oriented Programming and Computer Science
   and Introduction to Algorithms and Data Structures
OR
Computer Science: An Integrated Introduction
   and Computer Science: An Integrated Introduction
OR
Accelerated Introduction to Computer Science
   and Computer Science: An Integrated Introduction
   and Introduction to Software Engineering
   and Introduction to Computer Systems
CSCI 0220Introduction to Discrete Structures and Probability1
General Core Requirements: Probability & Statistics
APMA 1650Statistical Inference I1
or CSCI 1450 Introduction to Probability and Computing
or MATH 1610 Probability
General Core Requirements: Computational Biology
CSCI 1810Computational Molecular Biology1
APMA 1080Inference in Genomics and Molecuar Biology1
Capstone Experience1
Directed Research/Independent Study
Individual Independent Study
Six courses in one of the following four tracks:6
Computer Science Track:
Three of the following:
Introduction to Computer Graphics
Database Management Systems
Applied Artificial Intelligence
Probability and Computing: Randomized Algorithms and Probabilistic Analysis
Design and Analysis of Algorithms
or other Computer Science courses approved by the concentration advisor
Three of the following:
Introduction to Computer Systems
   and Introduction to Software Engineering
OR
Algorithmic Foundations of Computational Biology
Statistical Methods in Bioinformatics, I
Statistical Inference II
Computational Theory of Molecular Evolution and Population Genetics
Human Population Genomics
Biological Sciences track
At least four courses comprising a coherent theme in one of the following areas: Biochemistry, Ecology, Evolution, or Neurobiology.
Select two courses from the following:
Algorithmic Foundations of Computational Biology
Statistical Methods in Bioinformatics, I
Statistical Inference II
Computational Theory of Molecular Evolution and Population Genetics
Human Population Genomics
Applied Mathematics & Statistics Track:
At least three courses from the following:
Statistical Inference II
Computational Probability and Statistics
Applied Artificial Intelligence
Methods of Applied Mathematics I, II
   and Methods of Applied Mathematics I, II
OR
Methods of Applied Mathematics I, II
   and Methods of Applied Mathematics I, II
At least three of the following:
Computational Theory of Molecular Evolution and Population Genetics
Algorithmic Foundations of Computational Biology
Statistical Methods in Bioinformatics, I
Quantitative Models of Biological Systems
Human Population Genomics
Total Credits18-20

Honors:

To be a candidate for honors, a student must have a course record judged to be excellent by the concentration advisor and must complete a thesis judged to be outstanding by the faculty member supervising the work.