Computer Science

Computational Biology Minor Offered by the Department of Computer Science

Overview: Technological advances in the past 15 years have revolutionized biological sciences, as they have allowed large-scale simulations and high-throughput experiments throughout the Tree of Life. Unarguably, there is a need for computational methods that enable us to efficiently store, analyze and visualize the plethora of biological information available. Scientific methods from many areas of computer science such as machine learning, graph theory, scientific computation, visualization and databases, have been employed to address problems in biological sciences, while projections support that biological-related research in those areas will continue to increase in the next decade.

The minor in Computational Biology (CB) will provide students with engineering, physical or biological majors the foundations necessary to build efficient computational models and algorithms, use state-of-the-art techniques for scientific analysis and create scalable infrastructure environments for biological and biotechnological applications.

Requirements: Students must take a total of 20 upper-division units, with two required courses and three upper­division electives, as specified below. At most one course may be counted toward both the student’s minor and major. A minimum GPA of 2.0 is required for coursework in the minor. Students should note that most of the courses listed below have lower division prerequisites. In particular, the required course ECS 122A has a prerequisite chain of ECS 20, 30, 40, and 60.

Required Courses (2 courses, 8 units):
ECS 122A Algorithm Design and Analysis
ECS 124 Theory and Practice of Bioinformatics

Electives (12 units):
At least one biology course from the following:

MCB 121 Molecular Biology of Eukaryotic Cells EVE 103 Phylogeny and Macroevolution
MCB 124 Macromolecular Structure and Function EVE 104 Community Ecology
MCB 161 Molecular Genetics EVE 131 Human Genetic Variation and Evolution
MCB 182 Principles of Genomics BIS 101 Genes and Gene Expression
EVE 100 Introduction to Evolution BIS 104 Regulation of Cell Function
EVE 101 Introduction to Ecology BIS 122 Population Biology and Ecology
EVE 102 Population and Quantitative Genetics  

At least one computational or statistics course from the following:

ECS 130 Scientific Computation ECS 166 Scientific data Management
ECS 132 Probability and Statistical Modeling for CS ECS 170 Introduction to Artificial Intelligence
ECS 140 Programming Languages ECS 177 Introduction to Visualization
ECS 145 Scripting Languages and Their Applications EVE 175 Computational Genetics
ECS 156 Discrete-Event Simulation STA 141 Statistical Computing
ECS 158 Programming on Parallel Architectures STA 130A Brief Mathematical Statistics
ECS 160 Introduction to Software Engineering BIT 150 Applied Bioinformatics
ECS 165A Database Systems BIS 132 Introduction to Dynamic Models in Biology

At least one computational biology and bioinformatics course from the following:

ECS 129 Computational Structural Biology EVE 175 Computational Genetics
BIS 132 Introduction to Dynamic Models in Biology BIT 150 Applied Bioinformatics
BIM 117 Analysis of Molecular and Cellular Networks