BIOL/CMSC B115 Computing Through Biology: An Introduction

Spring 2016

General Information


Joshua Shapiro
Douglas Blank

Meeting times and locations

Monday & Wednesday 2:40-4:00PM, Park 337
Open Lab: Thursday 9:00-11:00AM, Park 231

Office hours

Joshua Shapiro: Tuesday 9:30-11:00AM, and by appointment
Doug Blank: Monday & Tuesday 10:00-11:00AM, and by appointment

Jupyter Login

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 and solving problems 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.
  • Understand the ideas behind computation, including the limits, requirements, and performance of different algorithms.
  • Model biological systems in a computational framework, and gain biological insights from those models in areas such as genetics, evolution, and ecology.
  • Understand common models of biological evolution and population genetics and explore their application to optimizing computational problems.

Textbook and Readings

For the computer science topics of the course, we will be using Python Programming, Second Edition 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 cover image

Readings on biological topics will be taken from a variety of sources, with all readings posted on the course website.

Tentative Schedule

Week Date Topic Reading (Zelle)
1 Jan 20 Modeling life through simulations Chapter 1
2 Jan 26 Simple programs - Python simulation Chapter 2, 7.1-7.3
Jan 28 Stochastic simulation, Random & pseudorandom numbers
3 Feb 1 DNA sequence analysis: GC content - math, strings, functions Chapter 3, 5.1-5.2, 6
Feb 3 GC content variation across genomes & species - lists, graphics Chapter 4, 11.1-11.3
4 Feb 8 DNA Translation - files, dictionaries Chapter 5.3-5.10, 11.1-11.3, 11.6
Feb 10 Debugging & testing
5 Feb 14 DNA mutations, types & effects - modular arithmetic Chapter 7
Feb 16 Sorting & analysis
6 Feb 22 Evolving digital organisms
Feb 24 Evolving digital organisms
7 Feb 29 Review for exam
Mar 2 Exam I
8 Mar 7 Spring Break
9 Mar 14 Population genetics: Random Genetic Drift - arrays, random Chapter 8
Mar 16 Genetic drift with mutations: infinite vs finite sites - program design Chapter 9
10 Mar 21 Haploids, diploids & mating - classes & objects Chapter 10
Mar 23 Additivity & dominance in evolution
11 Mar 28 Project Brainstorming & Design
Mar 30 Learning Systems & Plasticity
12 Apr 4 Training a neural network
Apr 6 Algorithm design & efficiency Chapter 13
13 Apr 11 Recursion
Apr 13 Sequence alignment
14 Apr 18 Broader applications
Apr 20 Project Presentations
15 Apr 25 Project Presentations
Apr 27 Review for final

Course Policies


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).


All computing will be done on the Athena cluster through your own computer's web browser. We will be using the Jupyter Notebook system with Python 3.

You can login to the Jupyter server at Accounts will be provided.


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.


Final grades will be determined according to the following weightings:

40% Assignments
15% Exam 1
20% Exam 2
15% Group Project
10% Participation

Late assignments will incur a 10% penalty per day unless arrangements are made for an extension at least 24 hours prior to the due date. Extensions will only be granted in the case of verifiable medical excuses or other similarly dire circumstances. All exams and projects are required; failure to complete any component will result in failure in the course.

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 or contact Rachel Heiser, Academic Support and Learning Resources Specialist in the Dean’s Office, with questions: (, 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 (, 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.