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Bachelor of Science in Systems Biology

Systems biology is a rapidly emerging area of research activity at the interface of mathematics, computer science, and the biological sciences. Many modern areas of biology research (e.g., biochemical, neural, behavioral, and ecosystem networks) require the mastery of advanced quantitative and computational skills. The systems biology Bachelor of Sscience degree program is intended to provide the quantitative and multidisciplinary understanding that is necessary for work in these areas. This skill set is different from that produced by traditional undergraduate programs in biology. Consequently, the Systems Biology BS program includes a specialized four-course core curriculum (different from the three-course core used in the Biology BA and BS programs), as well as foundation courses from computer science and advanced mathematics.

Undergraduate research is recommended (as BIOL 388S Undergraduate Research – SAGES Capstone and BIOL 390 Advanced Undergraduate Research), but is not required.

Systems Biology core courses
BIOL 250 Introduction to Cell and Molecular Biology Systems 3
BIOL 251 Introduction to Organismal and Population Systems 3
BIOL 300 Dynamics of Biological Systems: A Quantitative Introduction to Biology 3
BIOL 306 Dynamics of Biological Systems II: Tools for Mathematical Biology 3
Approved subspecialty sequence (choose one of the following four sequences) 6
Neuroscience (two courses)
BIOL 373
Introduction to Neurobiology
One other neuroscience course
BIOL 374
Neurobiology of Behavior
BIOL 376
Neurobiology Laboratory
BIOL 378
Computational Neuroscience
or MATH 378
Computational Neuroscience
BIOL 382
Drugs, Brain, and Behavior
Genetics (any two courses)
BIOL 301
Biotechnology Laboratory: Genes and Genetic Engineering
BIOL 326
BIOL 328
Plant Genomics and Proteomics
EECS 359
Bioinformatics in Practice
Evolutionary biology (two courses)
BIOL 364
Research Methods in Evolutionary Biology
One other evolution/ecology course
BIOL 225
BIOL 307
Evolutionary Biology of the Invertebrates
BIOL 336
Aquatic Biology
BIOL 345
Mammal Diversity and Evolution
BIOL 351
Principles of Ecology
BIOL 358
Animal Behavior
BIOL 365
Evo-Devo: Evolution of Body Plans
BIOL 366
Genes, Embryos and Fossils
BIOL 368
Topics in Evolutionary Biology
Cellular and molecular biology (any two courses)
BIOL 325
Cell Biology
BIOL 343
BIOL 362
Principles of Developmental Biology
BIOL 382
Drugs, Brain, and Behavior
BIOL Electives (excluding 100-level courses, BIOL 214, BIOL 215, BIOL 216, and BIOL 240) 12
(Undergraduate research recommended)
& BIOL 390
Undergraduate Research – SAGES Capstone
and Advanced Undergraduate Research
Mathematics and statistics core courses
MATH 121 Calculus for Science and Engineering I 4
MATH 122 Calculus for Science and Engineering II 4
or MATH 124 Calculus II
MATH 223 Calculus for Science and Engineering III 3
or MATH 227 Calculus III
MATH 224 Elementary Differential Equations 3
or MATH 228 Differential Equations
STAT 312 Basic Statistics for Engineering and Science 3
Chemistry core courses
CHEM 105 Principles of Chemistry I 3
CHEM 106 Principles of Chemistry II 3
CHEM 113 Principles of Chemistry Laboratory 2
Physics core courses
PHYS 121 General Physics I – Mechanics 4
or PHYS 123 Physics and Frontiers I – Mechanics
PHYS 122 General Physics II – Electricity and Magnetism 4
or PHYS 124 Physics and Frontiers II – Electricity and Magnetism
Computer science core courses
EECS 132 Introduction to Programming in Java 3
EECS 233 Introduction to Data Structures 4
EECS 302 Discrete Mathematics 3
or MATH 304 Discrete Mathematics
Systems Electives (any two of the following) 6
Largely computer science
EECS 313
Signal Processing
EECS 324
Simulation Techniques in Engineering
EECS 340
Algorithms and Data Structures
EECS 341
Introduction to Database Systems
EECS 365
Complex Systems Biology
Largely mathematical
EECS 246
Signals and Systems
BIOL 304
Fitting Models to Data: Maximum Likelihood Methods and Model Selection
BIOL 319
Applied Probability and Stochastic Processes for Biology
MATH 201
Introduction to Linear Algebra
BIOL 378
Computational Neuroscience
or MATH 378
Computational Neuroscience
OPRE 411
Optimization Modeling
Total Units 79