The Biological Data Sciences concentration tackles a diverse set of biological questions–ranging from medicine, to genomics, to physiology, to pharmacology, to neuroscience, to ecology, and evolution–using recent tools and advances in mathematics and computation–specifically machine learning, statistical data sciences, and informatics. This concentration leverages new and developing courses within CaSB and across UCLA and will greatly aid students aiming to go directly into industry–biotech, pharmaceuticals, and more–as well as computational biology graduate school. This concentration has a strong focus and deep integration with life sciences.
Concentration Curriculum
1. COM SCI CM121: Introduction to Bioinformatics (4)
2. COM SCI 180: Introduction to Algorithms and Complexity (4)
3. COM SCI M146: Introduction to Machine Learning (4) OR STATS 161: Introduction to Pattern Recognition and Machine Learning (4) OR STATS 101C: Introduction to Statistical Models and Data Mining (4)
4 & 5. Two elective courses chosen from list below:
| C&S BIO M175/CHEM M186 |
Stochastic Processes in Biochemical Systems (4) |
| C&S BIO M186/COM SCI CM186/COM SCI CM286/BIOENGR CM186/BIOENGR CM286/EE BIOL M178 OR COM SCI/BIOENGR M182 | Computational Systems Biology: Modeling and Simulation of Biological Systems (5) OR Dynamic Biosystem Modeling and Simulation Methodology (4) |
| COM SCI 111 | Operating Systems Principles (5) |
| COM SCI 112 | Modeling Uncertainty in Information Systems (4) |
| COM SCI 117 | Computer Networks: Physical Layer (4) |
| COM SCI 118 | Computer Network Fundamentals (4) |
| COM SCI CM122/COM SCI CM222/CHEM CM160B/CHEM CM260B/BIOINFO M222 | Algorithms in Bioinformatics (4) |
| COM SCI CM124/COM SCI CM224/HUM GEN CM124/HUM GEN CM224/BIOINFO M225 | Machine Learning Applications in Genetics (4) |
| COM SCI 130 | Software Engineering (4) |
| COM SCI 131 | Programming Languages (4) |
| COM SCI 132 | Compiler Construction (4) |
| COM SCI 133 | Parallel and Distributed Computing (4) |
| COM SCI 143 | Database Systems (4) |
| COM SCI 145 | Introduction to Data Mining (4) |
| COM SCI M151B/EC ENGR M116C | Computer Systems Architecture (4) |
| COM SCI 152B | Digital Design Project Laboratory (4) |
| COM SCI 161 | Fundamentals of Artificial Intelligence (4) |
| COM SCI 168 | Computational Methods for Medical Imaging (4) |
| COM SCI 170A | Mathematical Modeling and Methods for Computer Science (4) |
| COM SCI 174A | Introduction to Computer Graphics (4) |
| COM SCI 181 | Introduction to Formal Languages and Automata Theory (4) |
| MATH 151B | Applied Numerical Methods (4) |
| MATH 184 | Enumerative Combinatorics (4) |
| EE BIOL C172/C202 | Advanced Statistics in Ecology and Evolutionary Biology (4) |
| STATS 101A | Introduction to Data Analysis and Regression (4) |
| STATS 101B | Introduction to Design and Analysis of Experiment (4) |
| STATS 101C | Introduction to Statistical Models and Data Mining (4) |
| STATS 102A | Introduction to Computational Statistics with R (4) |
| STATS 130 | Getting Up to Speed with SPSS, Strata, SAS, and R (4) |
| STATS 131 | Python and Other Technologies for Data Analysis (4) |
| STATS 201A | Research Design, Sampling, and Analysis (4) |
| STATS 201B | Statistical Modeling and Learning (4) |
| STATS 201C | Advanced Modeling and Inference (4) |
Students in the Biological Data Sciences concentration must also complete:
- Computer Science 32
Concentration Course Planning
When planning major coursework, students must be mindful of pre-requisites. Some courses for the Biological Data Sciences concentration have additional pre-requisites that are not part of the CaSB major or pre-major curriculum. The flowcharts below are meant to help students plan out concentration coursework by depicting the requisites for each requirement. These flowcharts were last updated September 2021. Always check the Registrar’s Course Descriptions for updated requisites. Additionally, students must be mindful of when classes are offered (i.e., which quarters). Students should check the Schedule of Classes for updated course offerings.
It is recommended that students meet with their Departmental Counselor regularly to plan out major coursework.
Other Important Information
All major courses must be taken for a letter grade, C or better.
^CaSB made a temporary exception allowing pre-major courses taken between Spring 2020 and Summer 2021 to be taken for a Pass grade. More details on this exception can be found here.
Students must have a minimum 2.0 GPA in upper-division major coursework to graduate.
Students who receive a C- or below in a major course must either repeat the course or petition to have the lower grade count for the major. More information on petitioning can be found here.
Students are subject to any requirement changes in the major, including concentrations, until they are officially admitted to the major.
