AMATH 410:

Introduction to Computational Biology and Chemistry


SLN 18334, MTWF 8:30-9:20

LOCATION: MWF, GUG 218. ***Tues, Room B022 of ICL lab ** .


Instructor:

Prof. Eric Shea-Brown
Guggenheim 414F
etsb@amath.washington.edu
office hours: M 1:15-3:15, Guggenheim 415F


Description and Objectives Textbook and Notes Syllabus Schedule and Homework

Description and Objectives

In AMATH 410, you will learn about models that arise in biology in chemistry and how they're analyzed using modern mathematical and computational techniques. We will cover statistical models, discrete- and continuous- time dynamical models, and stochastic models. Applications will sample a wide range of scales, from biomolecules to population dynamics, with an emphasis on common mathematical concepts and computational techniques. Throughout, our themes will include interpretation of existing data and predictions for new experiments.

MATLAB will be used for numerical computation, visualization, and data analysis -- and mathematical tools taught in parallel with their computational implementation.

This course is designed for students in a wide variety of departments and with backgrounds across the sciences. A working knowledge of calculus is assumed, together with a desire to learn more about the underlying science, mathematics, or both.

Textbooks, Notes, and Course Resources

The required text for this course is "Dynamic Models in Biology," by Stephen Ellner and John Guckenhiemer (called EG below). A few chapters (including CHAPTER 1) are available free online, here. The text should be in the bookstore, is available on Amazon, and is on reserve in the library.

The "Lab Manual" for this course is also required reading. Freely available from the webpage here, this manual introduces MATLAB and computational methods -- and how to use them to solve and analyze the models and problems in the main text.

OTHER COURSE RESOURCES -- Mathematical models and analysis

These useful texts are also on course reserve in the library:

A course in Mathematical Biology, by de Vries, Hillen, Lewis, Muller, Schonfisch

Mathematical Models in Biology, by Leah Edelstein-Keshet

OTHER COURSE RESOURCES -- Computational methods and MATLAB

The notes of Prof. Nathan Kutz for AMATH 301 are a valuable course reference. Prof. Kutz has provided them online here: (.pdf)

There are a variety of MATLAB resource books available at the library. An excellent one is "Matlab Guide," by Desmond and Nicholas Higham. It is currently on "Math Reserve" in the library ( QA297 .H5217 2005).

For other MATLAB resources, including online tutorials, see below.

 

Review materials

  • probability_in_matlab_review.pdf
  • matlab_programming_review.pdf
  • cell_reproduction_review_code_1.m

    Syllabus

    (1) Course overview and introduction to mathematical models in the life sciences (1 week).
    Reading: EG Chapter 1, EG lab manual sections 1-6.
    • Modeling objectives: prediction and theory development
    • Rate equations, inflow-outflow models
    • Michaelis-Mentin Kinetics: enzyme-mediated chemical reactions
    • Complex models -- pharmacokinetics
    • Introduction to MATLAB: vectors, matrices, loops, logic, plotting

    Lecture notes, codes, and sampling of papers referred to in class:
    (5) More on fitting and testing models (1 weeks)
    Reading: EG Chapter 9

    Schedule and Homework

    Follow links in the table below to obtain a copy of the homework in Adobe Acrobat (.pdf) format. You may also obtain here solutions to some of the homework and exam problems. For additional information regarding viewing and printing the homework and solution sets, click here.

    Homework, Exams, and Events Date Problem sets, etc.
    First day of class Monday, March 31
    Homework#1 Due Wed. Apr 16, 8:30 AM Homework #1 (.pdf) Homework #1 solutions (.pdf) MATLAB SOLUTION CODES (link)
    Homework#2 Due Wed. Apr. 23, 8:30 AM (note due date) Homework #2 (.pdf) Homework #2 solutions (.pdf) ( eigenvalue_sensitivity_derivation.pdf ) Homework #2 MATLAB SOLUTION CODES (link)
    Fri., Apr 25 class cancelled
    Homework#3 Due Fri. May 2, 8:30 AM Homework #3 (.pdf), SequenceOfCurrentsDatamatrix.dat) Homework #3 solutions (.pdf) Homework #3 MATLAB SOLUTION CODES (link)
    Midterm Review Mon. May 5
    Midterm Wed. May 7, in class Midterm
    Homework#4 Due Fri. May 16, 8:30 AM
    Case study presentations IN CLASS May 21 and May 23 8:30 AM
    Memorial Day Monday, May 26 no classes
    Homework#5 Due Fri. May 30, 8:30 AM
    FINAL PROJECTS DUE Fri. June 6 8:30 AM

    MATLAB programming skills and lab sessions

    It's essential to keep up with the below lab assignments and (accumulating) list of programming skills. Please use the online tutorial at the bottom of the page, as well as our book's lab manual (link to free .pdf above), and other MATLAB resources as mentioned above.
    Week of Lab session assignment MATLAB SKILLS: partial list to keep up with and review
    March 31 IN LAB: Work through EG Lab manual sections 1-3. Do Ex 1.1, 1,2, 1.3, 3.1, 3.2, 3.3, 3.4. AS (UNGRADED) HW: Work through EG Lab manual sections 4-5. Do Ex 4.1, 4,2, 4.3, 5.1. List of techniques -- updated regularly. (.pdf)
    Apr 8 IN LAB: Work through EG Lab manual sections 6, 7, and 9 (skip 8 for now), with Ex 6.1, 6.3, 6.4, 9.1, 9.2, 9.3. No ``busy work," if you know this material, but please make sure you understand how to do all parts of these problems. List of techniques -- updated regularly. (.pdf)
    Apr 15 IN LAB: Discuss HW1. Work through EG Lab manual sections 8, and 7 if you skipped it before, with Ex 8.1, 8.2. List of techniques -- updated regularly. (.pdf)
    Apr 22 IN LAB: Discuss HW2, review compiled list of techniques. List of techniques -- updated regularly. (.pdf)
    Apr 29 IN LAB: Discuss HW3, and work through sec 11 of lab manual.

    Homework submission and course policies

    Homework is due at the beginning of class on the days above. Please take careful note of these dates, as they are somewhat irregularly spaced. Please also note that these dates might change somewhat as the course progresses -- webpage and email updates will be provided.

    No late homework will be accepted. However, for all students, I will drop the lowest ONE homework grade (i.e., one out of the five) when calculating the homework average.

     

    Grading

    Your course grade will be calculated via the following weights:

    Homework 40%

    Midterm 25%

    Case study presentation 5%

    Course project 30%

    The test schedule is in the table above.

    Case study and final project presentation -- follow link to more details.

    Each student will give a brief in-class presentation of a paper that applies the modeling and computational techniques we have learned in the course (case study). These studies will be developed into course projects. PLEASE NOTE: projects may be done in groups of one, two, three, or four students -- and you are strongly encouraged to choose to work in a group. Of course, if you work in a pair, group of two (three, or four), the project will be expected to be twice (or three, four times) as impressive! FOLLOW THIS LINK TO PROJECT AND CASE STUDY DETAILS.

    Matlab Resources

    In this course, we will make extensive use of Matlab, a technical computing environment for numerical computation and visualization produced by The MathWorks, Inc. Computers running with MATLAB, as well as the accompanying documentation, are available in the ICL Lab. If you are working in the Windows environment, be sure to check out the Matlab notebook feature that integrates Matlab with Microsoft Word.

    There are many additional Matlab resources available on the net, such as the below and many tutorials.