Bio 362 Simulating Life
Spring 2016
MWF 10:00–10:50PM W-2-031
TuTh 10:00am–11:30AM W-2-031
Instructor: Professor Brian White
How to contact me: The best way is by email: brian.white@umb.edu. My office hours are
Wednesdays 1-2, ISC 4450 (4th floor by the front of the atrium). We can also meet by appointment; just send me an email and we can schedule a time.
Pre-requisites
Genetics (252 or 254), Cell Biology (210 or 212), and Population Biology (290) or permission of the instructor.
Texts
None Required. There will be several journal articles that we will read over the semester; these will be posted on the course Blackboard site.
Goals and Objectives
Computer simulation of biological phenomena is an important and growing part of biological research, but students in the life sciences often shy away from using math and computer science as tools to study biology. The goal of Simulation in Biology is to show you how useful simulation is in understanding biology, and to convince you that anyone can learn to do it!
You will be using the graphic programming language StarLogo The Next Generation (SLTNG) to design, construct, and evaluate your own simulations of biological phenomena using autonomous agents. SLTNG allows you to simulate many aspects of biology—agents may be chosen to represent molecules, cells, or organisms—and the model scenario could be virtually anything, including enzyme kinetics, cells growing in culture, cells interacting in an organism, or organisms interacting with each other and their environment. Objectives for the course include:
1. Gain a deep understanding of biological content and the connections among different
fields in biology. To do this, you will be:


Extracting and programming the ‘rules’ of a biological system
Comparing models with peers to find similar ‘rules’ in different systems
2. Gain experience with hypothesis testing and the use of simulation in science. In doing so, you will learn how to:
Page 1 of 11

 Make use of the ‘Simulation Cycle’: hypothesize / collect facts / build model / test
 model / modify model / frame new hypothesis.
Explain and justify the assumptions necessary to build models.
3. Make connections between and find synergy among mathematics, computer science, and
biology.
4. Develop ‘systems thinking’, and understand the ‘emergent phenomena’ that arise when
agents interact.
This is primarily a course designed to get you thinking rigorously and deeply about biology.
You will have to think deeply when you choose a system to simulate (What part(s) should I leave
in? Which should I leave out? How do these relate to my goals in making the simulation?), when you design your agents (How do I get them to behave as I want while using biologically-reasonable
processes?), when you debug your simulation (Is this working? How can I tell? How can I figure
out what's wrong?), and when you use your simulation to explore the phenomenon you're studying. You'll demonstrate this thinking as you talk to me and your fellow students, in your blog posts, and in your final project and paper.
Because each person's project is different, there will be very few exams other than the
“individual midterm” (see later), quizzes during "Boot Camp" and on the scientific articles we will read. This means that the overwhelming majority of your grade will depend on what you do in class. As a result, class attendance and participation are essential and a very large component of your grade.
Simulating Life Structure and Content
General
Although the class is technically has “lecture” and “lab” components, hands on and discussion activities will occur throughout each session. We will be using SLTNG and Dropbox, enabling students to keep their code in one location accessible from any computer (on campus or at home), facilitating group work and work outside of class. During class time, the instructor may present ‘mini-lectures’ to orient you to the software, or to address points that many students are finding difficult. However, most of the classroom time will involve you working together either on tutorials (during the initial ‘boot camp’), or on your own simulation projects. The instructor will circulate, checking on progress and offering suggestions. The instructor will encourage a high level of interaction among students during these sessions to facilitate idea sharing and problem solving.
Boot Camp
After an introduction to the general idea of simulation and the goals of the course, the first few weeks of the class will be structured as a ‘boot camp’ to allow you to learn the SLTNG software. We will begin by following tutorials that are available online
(education.mit.edu/projects/starlogo-tng/learn). The tutorials are structured to start by
Page 2 of 11

building simple software that illustrates a few points at a time, facilitating a gradual build-up of knowledge and competence.
Each Boot Camp session will begin with a short closed-book multiple-choice/fill-in-the-blank quiz based on the previous evening’s homework. Students will first complete the quiz individually and then turn in their responses. Students will then re-take the same quiz collaboratively in their teams and then turn in their team responses. We will then immediately go over the answers to the quiz. Both the individual and team scores will count towards each person’s grade.
Page 3 of 11

Project Abstracts
As you are learning the software, you will also be required to think about what you want to model. Students will work in teams during Boot Camp but on projects individually. Each student will be required to submit a short (1 page) abstract of a system they would like to simulate, and their initial ideas on hypotheses they plan to address with their simulation, as well as the agents and rules they will follow. You should begin with a simple simulation and question, from which you will build larger and more complex systems as you progress through the class. You can choose to simulate basically any aspect of biology; the SLTNG software is extremely scalable and flexible. One or two class sessions will be devoted to brief presentations of these abstracts to the class, followed by feedback from the instructors and peers. Revised abstracts will be posted to the Group Lab Notebook (see below).
The Group Lab Notebook (GLN)
We will keep a group lab notebook on our Blackboard site where students can blog about problems they encountered, attempts to solve the problem (even if they failed), and solutions they discovered. Thus, as the course progresses, students will be both contributing to and benefitting from a “Knowledge Base”, and seeing that problems in seemingly different models can be solved in similar ways. Students will also be required to make regular posts to the GLN after the “Boot Camp” has completed:
 Weekly Check-in – due before class every Monday. A brief plan for your work in the following week. I will go around on Mondays and Tuesdays to check in with people about these posts.
 Code Review – due by 5PM every Friday. Fridays are “Code Review” days – students pair up and explain particularly important, interesting, or challenging parts of their code to their partner. The partner then posts a screenshot of that part of your code with an explanation of how it works (or doesn’t). I will comment on these over the weekend to be sure you are on the right track.
Your posts to the GLN are a significant part of your grade and will be evaluated based on the depth and rigor of your analysis.
Research articles
In order to connect your work in the course to the larger world of scientific applications of simulation, over the course of the class, we will read and discuss research articles involving simulation. These papers will be selected by the instructor, who will lead a discussion on the paper in class. The discussion of each paper will begin with a short open-book quiz on the paper. This quiz will be administered using the same procedure as the Boot Camp quizzes.
Individual Midterm Exam
In order to help you to think deeply and rigorously about your project, at roughly the midpoint of the project work, we will have an “individual take home midterm exam”. I will make
Page 4 of 11

up a single exam question for each of you based on your project. Your answer will be 1-2 pages single spaced and may include figures, code screenshots, etc. I will give these out on a
Thursday so that you can ask me about them on Friday. They will then be due on the following Monday. Your answers will be evaluated on the depth and rigor of your response.
For example, suppose you were studying predator/prey relations. I might ask “Give one of the features of your simulation that has a very large effect on the stability of your populations. Explain how you know that this feature has a larger effect on stability than other features and explain why this makes
(or does not make) biological sense.”
Final Reports
There are three final things that are due at the end of the semester:
1.
Working Simulation You have to have a simulation that works to show at the Open
House on the last day of class. This need not be your most advanced version, but it must work.
2.
Handout This is a 2-sides-of-one-page handout to accompany your simulation at the
Open House. It should include:
1.
Title - short, sweet, and descriptive.
2.
System being simulated - very brief "chemical kinetics", "social hierarchy in clownfish" etc.
3.
Your "story" - what you're telling the audience. This is the main part of the handout.
4.
Other useful information - a key to the agents; result descriptions/graphs, etc.
3.
Final Paper This is a 3-5 page (double-spaced, 12-point, narrow margins) paper describing 1 or 2 (maximum - I'd rather one clear and deep one than two shallow ones) instances where you learned something about biology (or chemistry) from the class. Your paper will be evaluated on the degree to which it represents a deep and rigorous analysis of your topic. Specifically:
1.
What you initially thought.
2.
How building a simulation (or working with someone else) made you realize that was wrong. This is 1/2 of the main part of the paper - I'm really interested in your thought process: the way you figured out that what you initially thought was wrong. What specific results, observations, etc led you to realize you "had it wrong"?
3.
How your (or their) simulation enacted the right model. This is the other 1/2 of the main part of the paper - I'd like to see you compare and contrast the "right" and "wrong" ways to model the particular thing.
4.
What you think now about this.
Simulation Open House
At the end of the course, each student will present the final version of his/her simulation at an
Open House. This presentation will include a live demonstration of the simulation itself, as well as a handout that serves as a stand-alone description of the simulation, instructions on
Page 5 of 11

how to run it, and evaluation of the simulation against ‘real world’ data. The session will be announced publicly to both students and faculty in the Biology Department and thus will serve as celebration of the your work, as well as recruitment for future students.
Page 6 of 11

Evaluation
Learning to program is like learning a foreign language; it’s important to work on it constantly. Thus, points are distributed to reward continuous progress, rather than being too heavily weighted at the end of the class. In the evaluation of the simulations, more weight will be placed on the process of constructing the simulation than on whether it reached any particular complexity.




10% Boot Camp Quizzes
10% Individual Midterm Exam
35% Blog/GLN/Class Participation
5% Research Article Quizzes
 20% Final Paper
 20% Open House Presentation & Handout
Connecting with other project-based biology courses
During the project phase of the course, we will interact with students in Plant Physiology. These students are doing individual independent “wet-lab” research projects involving plant molecular biology. At least once, we will visit their class to have them present and talk with them about their projects; at another time, they will visit us. This will give us practice presenting as well as giving and receiving feedback and criticism.
Accommodations for Students with Disabilities
The University of Massachusetts Boston is committed to providing appropriate academic accommodations for all students with disabilities. If you have a disability and feel you will need accommodations in this course, please contact:
The Ross Center for Disability Services
Campus Center, Upper Level, Room 211 (617-287-7430). http://www.umb.edu/academics/vpass/disability/
After registering with the Ross Center, a student should present and discuss the accommodations with the professor. Although a student can request accommodations at any time, we recommend that students inform the professor of the need for accommodations by the end of the Add/Drop period to ensure that accommodations are available for the entirety of the course.
Academic Honesty
All students are expected to follow the University’s Code of Student Conduct :
Page 7 of 11

http://www.umb.edu/life_on_campus/policies/code?nossl, which gives you details about cheating on exams and written assignments. Any suspected violation of the Code of Conduct will be treated very seriously and investigated fully.
Page 8 of 11

Weekly Schedule (subject to change as the need may arise):


Week 1: Boot Camp I o
Monday: Introduction to simulation
 Introduction to simulation & the course

Homework for Tuesday: o
 Load SLTNG on your home computer from http://education.mit.edu/projects/starlogo-tng (Note that, on Mac OS
X, it may tell you that the file is corrupted. This is not correct; you just need to set your security settings to allow applications from anywhere to be run – there is an explanation of this on the SLTNG Download
 page).
Do tutorial (all tutorials are at http://education.mit.edu/projects/starlogo-tng/learn ) “ Quick Start
Guide ”
Tuesday: Boot Camp 1 o o



Quiz on “Quick Start Guide”
Design Challenge: Walking in a triangle and a circle.
Homework for Wednesday:
 Do tutorials:
 “ How to Navigate in Spaceland ”

“ How to Edit Breeds ”
Wednesday: Boot Camp 2
 Quiz on “How to Navigate in Spaceland “ & “How to Edit Breeds”


Simulation & SLTNG, continued
Homework for Thursday:

Do tutorials:


“ How to Edit Spaceland Terrain ”
“ How to Draw and Color on Spaceland Terrain ”
Thursday: Boot Camp 3



Quiz on “How to Edit Spaceland Terrain” & “How to Draw and Color
Spaceland Terrain” - cancelled
Design Challenge: Maze of Doom (making collisions work)
Homework for Friday:
 Work on the mazes in order to get collisions working as "right as we o can"
Friday: Collisions

Get collisions working right
 Homework for Monday
 Do tutorial “ Complexity Science and Star LOGO TNG ”
Week 2: Boot Camp III o
Monday: Boot Camp 4
 Quiz on “Complexity Science and SLTNG”


Discuss possible projects
Homework for Tuesday:
Page 9 of 11

o o


Do tutorial “ How to Create a Procedure ”
Do tutorial “ Build an Epidemic Model ” parts 1-4
Tuesday
 Quiz on "How to make a procedure"

 bring in and show off your Epidemic models so far
Work on Epidemic Model.
 Homework for Wednesday
 Finish Epidemic Model Tutorial
Wednesday & Thursday
 Quiz on “Build an Epidemic Model”

Design challenge: modifications to the epidemic model
 Homework for Friday:
 Implement "aquired immunity" in epidemic
 if you've been infected and then recovered, you are immune
 and can't be re-infected post code to group lab notebook o
Friday
 Talk about modification to epidemic.

Presentation of some projects from last year
 Homework for Tuesday:
 Read Paper: “Large-Scale Spatial-Transmission Models of Infectious

Disease” Riley 2007
Week 3: Begin Projects o
Monday
 o o o

 Presentation of more projects from last year
Tuesday
Quiz on Riley 2007


Discussion of Riley 2007
Every project presents brief description
Wednesday

Thursday
Further discussion of projects
 Draft abstract due - 1 page max
 Rough description of full simulation
 Rough description of goals &/or hypotheses to test
 Detailed description of "proof of concept prototype"
 What are you simulating?

What are your agents?


What are their behaviors?
How will you know it's working? o

 Post a .pdf on the group lab notebook - BEFORE CLASS
Abstract presentations & discussion - part 1
Friday
 Abstract presentations & discussion - part 2
Week 5: Projects 1
Page 10 of 11



 o o o
Monday
 Final abstracts due - post to group lab notebook BEFORE CLASS
Tuesday & Wednesday: Begin work on projects
Thursday: Group Meeting – each person presents:


One thing that is working that others might need to know about
One thing that isn’t working that you could use some help with o
Friday: Code review.
 Homework for Monday:
 Read Paper: Emergent Sensing of Complex Environments by Mobile Animal
Groups Berdahl (2013)
Week 6: Projects o o
Monday - "check in" due before class
 Quiz on Cousins 2013 paper
 discuss cousins
 work on projects
Tuesday & Wednesday: work on projects o o
Thursday - group meeting
Friday - code review
Week 7-14: Projects o o o o o
Monday - "check in" due before class
Tues & Weds - work on projects
Thurs - group meeting
Friday - code review
** Individual Take-Home Midterm exam
Week 15: Presentations o
Final presentation preparation o o
Final papers due
“Open House”
Page 11 of 11