Laurie J. Heyer

Teaching

At Davidson, I have taught the following classes:

MAT 130 Calculus I
MAT 112 Calculus I & Modeling (formerly MAT 130M)
MAT 140 Multivariable Calculus & Modeling (formerly MAT 137)
MAT 135 Calculus II
MAT 150 Linear Algebra
MAT 210 Mathematical Modeling
MAT 235 Differential Equations
MAT 340 Probability
MAT 341 Mathematical Statistics
MAT 482 Introduction to Operations Research
BIO / CSC 310 Bioinformatics (now BIO / CSC 209, on Moodle)

Microarrays

I have worked on the following projects in the application and interpretation of microarrays:

Software Development
We have created open source software for analyzing microarrays, called MicroArray Genome Imaging and Clustering (MAGIC) Tool. MAGIC Tool is freely available and works on all major platforms. In 2005, I coathored a paper on MAGIC Tool with the first six undergraduates to work on the program. MAGIC Tool is a large-scale software project with many users, and I continue to hire students every year to improve and add features to the program. Collaborators (in chronological order) Adam Abele, David Moskowitz, Parul Karnik, Danielle Choi, Brian Akin, Emily Oldham, A. Malcolm Campbell, Mackenzie Cowell, Gavin Taylor, Adam Topaz, Michael Gordon, and Andrew Martens*.
Design of Microarray Controls
Emily Oldham '03 studied microarray controls and sources of variation in her honors thesis, a part of her major in Computational Genomics. Malcolm Campbell and I co-supervised her thesis.
Clustering Algorithm
QT-Clust is a new method for clustering gene expression data, developed with fellow postdoctoral researchers Semyon Kruglyak and Shibu Yooseph in the Computational Molecular Biology group at the University of Southern California. The paper, "Exploring Expression Data: Identification and Analysis of Coexpressed Genes," appeared in Genome Research in 1999, and is freely available.
Microarray Workshops
In the summers of 2007 through 2009, we are teaching faculty how to produce their own microarray data and analyze it with MAGIC Tool in week-long NSF-funded workshops. Collaborators: faculty in the Genome Consortium for Active Teaching (GCAT).
Microarrays for High School Students
Malcolm Campbell and Ben Kittinger* developed the wet lab protocol for a microarray simulation that is easily accessible at the high school level. We have published a paper describing biological and mathematical curricular materials to help high school teachers bring microarrays into their classes. Genisphere offers the microarray simulation in a commercial kit.

Synthetic Biology

Synthetic biology is a new area of collaboration between mathematicians, biologists, computer scientists, and other traditional science and engineering disciplines. The goals of synthetic biology are to design and construct new biological parts, devices and systems for useful purposes. Davidson College undergraduate teams regularly compete in the international Genetically Engineered Machines (iGEM) jamboree.

2006

Goal: Build a simple living computer by designing a circuit to solve the Burnt Pancake Problem. Essentially, we let billions of cells "guess" the solution by randomly arranging a sequence of genes, and kill any cells that get it wrong.

Project wiki page

Davidson news story

iGEM Presentation (Powerpoint)

iGEM Presentation video

2005

Goal: Design and construct a biological circuit to interpret the presence or absence of three different chemicals as a number in base 2, and display that number in base 10 using fluorescently glowing bacteria.

Project wiki page

Davidson News story

iGEM Presentation (Powerpoint)

Textbook

I coauthored the first true undergraduate genomics textbook, Discovering Genomics, Proteomics and Bioinformatics, with A. Malcolm Campbell of the Davidson biology department. Now in its second edition, the book is jointly published by Benjamin Cummings and Cold Spring Harbor Laboratory Press. The accompanying web site is freely accessible.

The book includes "Math Minutes" that reveal the math behind the biology. Some examples of math minutes are listed in the following table.

Math Minute	Topic
What is an E-value?	Sequence alignment; statistical significance
What does a positive test result really mean?	Probability; Bayes’ Rule
Is cGMP production elevated?	Confidence interval; paired t-test
How do you know if the tree is correct?	Bootstrapping procedure
How do you find motifs?	Probability; logarithms
What are “positives” and what do they have to do with E-values?	Sequence alignment
Can you estimate the number of inversions in a dot plot?	Alternating cycles in graphs
How do you model population diversity?	Sampling with replacement; simulation