School of Engineering
Department of Computer Science

Undergraduate Focus Area: Bioinformatics

The Bioinformatics Focus Area in the Computer Science Major
Department of Computer Science
Tufts University
Last updated by Lenore Cowen, Soha Hassoun, Mike Hughes, Li-Ping Liu and Donna Slonim, on November 6, 2019

Overview

Bioinformatics applies computer science techniques to analyze and interpret biological data.  At Tufts, bioinformatics research and education span several key topics including computational biology, systems biology, bioengineering, and biomedical informatics. Key underlying techniques include machine learning, statistical science, and algorithms. Built on a strong computer science foundation, this focus area provides breadth and depth in bioinformatics to prepare students for careers or graduate school in fields at the intersection of biology and computer science.  This focus area applies equally well for Arts and Sciences (A&S) and School of Engineering (SoE) students, and for both Computer Science and Data Science majors. 

The Computer Science Core

Common to both Computer Science and Data Science Majors, and most relevant to this focus area. Additional core courses may be required for your major.

  1. Introduction to Computer Science (CS 11)
  2. Data Structures (CS 15)
  3. Machine Structure & Assembly Language Programming (CS 40)
  4. Discrete Mathematics (CS 61)
  5. Algorithms (CS 160)
  6. Probability & Statistics (MATH 162, ES 56, EE24, EE 104, BME 141, BIO 132, PHY 153)

The Bioinformatics Core

  1. Machine Learning (CS 135) (required for DS majors)
  2. Computational Biology (CS 167)
  3. Computational Systems Biology (CS 150-CSB)

Bioinformatics Electives

Pick at least 3 courses from the list below:

  • CS 131 AI
  • CS 136 Statistical Pattern Recognition (required for DS majors)
  • CS 150-BDL Bayesian Deep Learning
  • CS 150-CBP Computing with Biological Parts 
  • CS 150-MLG Machine Learning for Graph Analytics
  • CS 150-CSE Exploration of Computer Science Ethics
  • CS 150-DNN Deep Neural Networks
  • CS 150-EXM Experimental Methods for Computer Scientists
  • CS 150-HPC High Performance Computing
  • CS 150-MMD Mobile Medical Devices and Apps
  • CS 150-NS Network Science
  • CS 150-VA Visual Analytics
  • CS 156-SEN Software Engineering
  • CS 150-NLP Natural Language Processing
  • CS 150-WWC Working with Corpora

Recommended Courses in Other Departments

It is recommended that students take at least 3 courses in either Biology, Biomedical Engineering, or Biological and Biomedical Engineering departments, depending on interest. Some courses offered include: 

  • BIO 13-Organisms and Populations W/Lab
  • BIO 41-General Genetics
  • BIO 132-Biostatistics
  • BIO 133-Ecological Stats & Data W/Lab
  • BIO 105-Molecular Biology
  • BME 62-Molecular Biotechnology

Capstone

To be successful in Bioinformatics in the future (in academia and industry alike), you will need to be able to demonstrate practical hands-on experience with Bioinformatics algorithms and problems. You can fulfill the capstone de facto requirement in our Bioinformatics focus area by either doing a year-long senior capstone project via CS 97 and CS 98 or doing a thesis in Bioinformatics via CS 197. Contact any of the Bioinformatics faculty for further information.