Computational Biology, BAS
The BAS in Computational Biology is an interdisciplinary area that crosses between the biological sciences, math, and computer science. More specifically, it requires that students augment a basic computer science curriculum with courses in biology, chemistry, genetics and statistics. The program is intended to train students in key areas of Computational Biology and is also designed so that a student may focus on those areas of biology in which he or she wishes to specialize. A broad background in computer science, from programming to algorithms to database systems, is also required. This program has a year-long capstone course in computational biology that is co-taught by faculty in computer science, biology and genetics. The development of Computational Biology has been influenced by various factors. One main influence derives from the need to solve problems associated with the assimilation, storage, retrieval and analysis of data arising from the Human Genome Project and similar projects that involve massive data sets containing bibliographic information, DNA sequence information and testing methods and results. The analysis of such data involves the development and use of complex information modeling techniques, languages, visualization techniques, and computational methods. The second broad area of biology in which computational methods have for some time been used is in evolution and ecology. Many evolutionary processes when viewed from the genetic point of view involve equations of such complexity that ordinary algebraic and calculus methods are simply insufficient to solve them, and numerical methods entailing the use of a computer are necessary. The construction of phylogenetic trees of evolution has for a long time been carried out by computational as opposed to mathematical methods. Many ecological processes similarly involve such complexities that computer methods offer the only way forward. Computational Biology is a field of current interest and is essential to train computer scientists with enough knowledge of biology to be able to understand the problems and computational opportunities in this domain. Employment opportunities are excellent at major pharmaceutical companies, biotech companies and research labs.
For more information: https://www.seas.upenn.edu/prospective-students/undergrad/majors/bachelor-of-applied-science/
Computational Biology (ASCB) Major Requirements
40 course units are required. Read more about the Undergraduate Student Handbook.
| Code | Title | Course Units |
|---|---|---|
| Engineering | ||
| CIS 110 | Introduction to Computer Programming | 1 |
| CIS 120 | Programming Languages and Techniques I | 1 |
| CIS 121 | Programming Languages and Techniques II | 1 |
| CIS 240 | Introduction to Computer Systems | 1 |
| CIS 320 | Introduction to Algorithms | 1 |
| CIS Electives 1 | 2 | |
| CIS Project Electives 2 | 2 | |
| Engineering Electives | 2 | |
| EAS 499 | Senior Capstone Project | 1 |
| Math | ||
| MATH 114 | Calculus, Part II | 1 |
| CIS 160 | Mathematical Foundations of Computer Science | 1 |
| CIS 262 | Automata, Computability, and Complexity | 1 |
| BIOL 446 | Statistics for Biologists | 1 |
| Math Elective | 1 | |
| Natural Science | ||
| BIOL 121 | Introduction to Biology - The Molecular Biology of Life | 1 |
| BIOL 102 | Introduction to Biology B | 1.5 |
| BIOL 221 | Molecular Biology and Genetics | 1 |
| CHEM 101 | General Chemistry I | 1 |
| CHEM 053 | General Chemistry Laboratory I | 0.5 |
| Concentration | ||
| Select 7-8 course units | 7-8 | |
| Social Sciences and Humanities 3 | ||
| EAS 203 | Engineering Ethics | 1 |
| Select 2 Social Science courses | 2 | |
| Select 2 Humanities courses | 2 | |
| Select 2 Social Science or Humanities or Technology in Business and Society courses | 2 | |
| Free Elective | ||
| Select 2.5-3.5 course units of free electives | 2.5-3.5 | |
| Total Course Units | 40 | |
| 1 | A CIS elective is a CIS or NETS engineering course. The SEAS handbook defines all CIS and NETS classes numbered 1xx-5xx as engineering courses, with the following exceptions that cannot be used: CIS 105 Computational Data Exploration, CIS 106 Visualizing the Past., CIS 125 Technology and Policy, CIS 160 Mathematical Foundations of Computer Science, CIS 261 Discrete Probability, Stochastic Processes, and Statistical Inference, CIS 262 Automata, Computability, and Complexity. ESE 350 Embedded Systems/Microcontroller Laboratory can also be used to satisfy the CIS elective requirement. |
| 2 | Select one from the following list: CIS 341 Compilers and Interpreters, CIS 371 Computer Organization and Design, CIS 380 Computer Operating Systems, CIS 455 Internet and Web Systems, CIS 460 Interactive Computer Graphics, CIS 553 Networked Systems, or ESE 350 Embedded Systems/Microcontroller Laboratory. |
| 3 | The Social Science & Humanities Depth, Writing & Ethics Requirement can be satisfied with the 7 total course units. |
Concentration
Department approval is required.
| Code | Title | Course Units |
|---|---|---|
| BIOL 437 | Introduction to Computational Biology & Biological Modeling | 1 |
| BIOL 537 | Advanced Computational Biology | 1 |
| Select two of the following: | ||
| Principles of Physics I: Mechanics and Wave Motion | ||
| General Chemistry II | ||
| Vertebrate Physiology | ||
or BIOL 251 | Molecular and Cellular Neurobiology | |
| Evolutionary Biology | ||
or BIOL 231 | The Evolution of Animal Behavior | |
or BIOL 240 | Ecology: From individuals to ecosystems | |
| CHEM 054 | General Chemistry Laboratory II (if applicable) | 0.5 |
| Select remaining 3 courses from the following: | ||
Any CIS course | ||
Any 200 level Biology course | ||
| Advanced Evolution | ||
| Evolutionary Ecology | ||
| Molecular Genetics | ||
| Biochemistry and Molecular Genetics Superlab | ||
| Genome Science and Genomic Medicine | ||
| Advanced Cell Biology | ||
| The RNA World: A functional and computational analysis | ||
| Physical Models of Biological Systems | ||
| Theoretical and Computational Neuroscience | ||
| Ordinary Differential Equations | ||
| Partial Differential Equations | ||
| Stochastic Processes | ||
The degree and major requirements displayed are intended as a guide for students entering in the Fall of 2018 and later. Students should consult with their academic program regarding final certifications and requirements for graduation.