# BIOL B1XX/CSMC B1XX: Computing Through Biology ### Spring 2016 ### Instructors: Joshua Shapiro & Douglas Blank ## Course Description This course is an introduction to biology through computer science, or an introduction to computer science through biology. The course will examine biological systems through the use of computer science, exploring concepts from bioinformatics, evolution, ecology, and molecular biology through the practice of writing and modifying code in the Python programming language. The course will introduce students to the subject matter and branches of computer science as an academic discipline, and the nature, development, coding, testing, documenting and analysis of the efficiency and limitations of algorithms. ### Learning objectives The goal of this course is to introduce concepts from computer science and biology in an integrated approach, while drawing connections between these two fields of study. Specifically, students completing the course should be able to: * Read, write, and modify computer code in the Python language utilizing programming constructs such as variables, functions, loops, conditional statements, and objects. * Design, implement, and debug programs to perform computational tasks. * Model biological systems in a computational framework, and gain biological insights from those models. * Understand common models of biological evolution and population genetics and explore their application to optimizing computational problems. * Understand the ideas behind computation, including the limits, requirements, and performance of different algorithms. ## Tentative Schedule Week | Date | Topic | Reading (Zelle) | -----:|--------|--------------------------------|------------- | 1 | Jan 19 | Modeling Life through simulations | Chapter 1 | | Jan 21 | Foraging and energy models | | 2 | Jan 27 | Simple programs - Python simulation | Chapter 2, 7.1-7.3 | | Jan 19 | Stochastic simulation, Random & pseudorandom numbers | | 3 | Feb 2 | DNA sequence analysis: GC content - math, strings, functions | Chapter 3, 5.1-5.2, 6 | | Feb 4 | GC content variation across genomes & species - lists, graphics | Chapter 4, 11.1-11.3 | 4 | Feb 9 | DNA Translation - files, dictionaries | Chapter 5.3-5.10, 11.1-11.3, 11.6 | | Feb 11 | Debugging & testing | | 5 | Feb 15 | DNA mutations, types & effects - modular arithmetic | Chapter 7 | | Feb 17 | Sorting and analysis | | 6 | Feb 23 | *Community Day of Learning* | | | Feb 25 | Evolving digital organisms | | 7 | Mar 1 | Review for exam | | | Mar 3 | **Exam I** | | 8 | Mar 7 | *Spring Break* | | 9 | Mar 15 | Population genetics: Random Genetic Drift - arrays, random | Chapter 8 | | Mar 17 | Genetic drift with mutations: infinite vs finite sites - program design | Chapter 9 | 10 | Mar 22 | Haploids, diploids & mating - classes & objects | Chapter 10 | | Mar 24 | Additivity & dominance in evolution | | 11 | Mar 29 | Project Brainstorming & Design | | | Mar 31 | Learning Systems & Plasticity | | 12 | Apr 5 | Training a neural network | | | Apr 7 | Algorithm design & efficiency | Chapter 13 | 13 | Apr 12 | Recursion | | | Apr 14 | Sequence alignment | | 14 | Apr 19 | Broader applications | | | Apr 21 | Project Presentations | | 15 | Apr 26 | Project Presentations | | | Apr 28 | Review for final | | ### Textbook and Readings For the computer science topics of the course, we will be using [Python Programming, Second Edition](http://mcsp.wartburg.edu/zelle/python/ppics2/index.html) by John Zelle. Be sure to get the second edition, as it covers Python 3, which is the version of the language that we will be using. ![Python Programming, second edition](http://mcsp.wartburg.edu/zelle/python/ppics2/cover.png) Readings on biological topics will be taken from a variety of sources, with all readings posted on the course website. ## Course Policies ### Assignments There will be approximately ten assignments, consisting of programming problems and explorations of biological questions through computational approaches. Assignments will be submitted through Jupyter (below). ### Computing All computing will be done on the [Athena cluster](https://athena.brynmawr.edu/) through your own computer's web browser. We will be using the [Jupyter Notebook](https://jupyter.org) system with Python 3. Accounts will be provided. ### Exams There will be two exams in the course, one mid-semester and the other during finals period. The exams will cover material from lectures, homeworks, and assigned readings (including topics not discussed in class). Both exams will be closed-book and closed-notes. ### Group Project During the second half of the semester, students will work in small (2-3 person) groups on an independent programming project that explores an area of biology through computation. Topics may include simulations of genetic regulatory systems, modeling of population dynamics or epidemiology, bioinformatic data analysis, or any other topic of interest in biology. Groups will present their work in an oral presentation to the class, and through a Jupyter notebook that clearly describes both the biological questions being addressed and the computational approaches taken. ### Support Services and Accommodations Bryn Mawr offers a variety of resources to help students thrive in their academic endeavors while managing stress and maintaining mental health. For further information on those services, consult the [Support Services website](http://www.brynmawr.edu/academicsupport/StudentSupportServices.html) or contact Rachel Heiser, Academic Support and Learning Resources Specialist in the Dean’s Office, with questions: ([rheiser@brynmawr.edu](mailto:rheiser@brynmawr.edu), 610-526-5275) Students who think they may need accommodations in this course due to the impact of a learning, physical, or psychological disability are encouraged to meet with me privately early in the semester to discuss their concerns.  Students should also contact Deb Alder, Student Access Coordinator ([dalder@brynmawr.edu](mailto:rdalder@brynmawr.edu), 610–526–7351), as soon as possible, to verify their eligibility for reasonable academic accommodations. Early contact will help to avoid unnecessary inconvenience and delays.