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Introductory Computer Science Courses
Introductory Mathematics/Applied Mathematics
Courses
Introductory Science Courses
Other Introductory Courses
Introductory Computer
Science Courses
Introductory Mathematics
and Applied Mathematics Courses
Courses that Replace/Revise Standard Calculus
University of California, Davis
Calculus for Biology and Medicine (MAT 17A/17B/17C)
This year-long, three-quarter sequence of courses provides an
introduction to differential calculus via
applications in biology and medicine. It covers important topics such as
limits, derivatives of polynomials, trigonometric, and exponential functions,
graphing, and applications of the derivative to biology and medicine. Each course requires a three-hour lecture and a one-hour
discussion section. It currently uses the text Calculus for Biology and Medicine (Prentice
Hall, 2nd edition, 2003).
Target Audience: Prospective majors in biology and other biologically related fields
Prerequisites: Two years of high school algebra, plane geometry, plane trigonometry, and
analytical geometry, and satisfaction of the Mathematics Placement Requirement.
http://www.math.ucdavis.edu/courses
Contact: Vice Chair for Undergraduate Matters, Department of Mathematics,
vicechair-undergrad@math.ucdavis.edu
University of Minnesota
Calculus with Biological Emphasis (MAT 1281/1282)
This calculus course for prospective biology majors covers the
most important calculus topics, including differential and difference
equations, matrix models, matrix algebra (eigenvalues, etc.), as well
as probability and statistics. It emphasizes word problems taken from
research papers. The text Calculus for Biology and Medicine (Prentice
Hall, 2nd edition, 2003) was written especially for this and similar courses.
Target Audience: Prospective biology majors.
Prerequisites: 4 years of high school math including trigonometry,
or grade of at least C- in Precalculus or Intensive Precalculus, or placement
exam.
http://biosci.cbs.umn.edu/eeb/faculty/NeuhauserClaudia.html
Contact: Claudia Neuhauser, Professor, Head, and Director of Graduate
Studies, Ecology, Evolution, and Behavior, (612) 624-6790, cneuhaus@cbs.umn.edu
University of Tennessee
Mathematics for the Life Sciences (MATH 151/152)
This year-long sequence provides an introduction to a variety of mathematical
topics of use in analyzing problems arising in the biological sciences.
The general aim is to show how mathematical and analytical tools may be
used to explore and explain a wide variety of biological phenomena that
are not easily understood with verbal reasoning alone. The course has
an accompanying computer laboratory component where students use the software
packages Matlab and Maple for their assignments.
Target Audience: Undergraduates in biology, agriculture, forestry,
wildlife, pre-medicine and other pre-health professions. (Not for students
who desire a strong mathematical grounding and who plan to take more advanced
math courses.)
Prerequisites: 2 years of high school algebra; 1 year of
geometry; half a year of trigonometry.
http://www.tiem.utk.edu/~gross/math151.html
http://www.tiem.utk.edu/~gross/math152.html
Contact: Louis J. Gross, Professor of Ecology and Evolutionary Biology
and Mathematics, gross@tiem.utk.edu
University of Toronto
Biology, Models and Mathematics (JMB170Y)
This year-long course provides mathematical training for prospective life
science students. It is team-taught by 2-3 faculty in Biology and Mathematics.
The biologists introduce a number of biology-related problems that require
mathematical analyses. The mathematician then teaches the required mathematics
in the context of the biological applications. The biological problems
are selected from a diversity of disciplines, including population genetics,
conservation biology, evolution, growth, population dynamics, physiology,
cell biology, and chaos. The mathematical topics include linear regression,
logarithms, power functions, logarithmic graph paper, exponential and
logistic growth, elementary probability, derivatives, integration, dynamic
programming, differential equations, Markov chains, and a brief introduction
to chaos theory.
Target Audience: Prospective life science students (specialists
and majors).
Corequisites: Introductory biology.
http://zardoz.zoo.utoronto.ca/zooweb2/undergrad/ugcoursedescr.asp?ID=31
Contact: Joe Repka, Professor, Dept. of Mathematics, (416) 978-4692,
repka@math.toronto.edu; Jim Rising, Professor, Dept. of Zoology, (416)
978-3482, rising@zoo.toronto.edu
University of Utah
Calculus for Biologists (MATH 1170/1180)
This full-year calculus sequence is designed to teach students
the mathematics necessary to do biology in this quantitative age. The
course has an accompanying one-hour weekly computer lab where students
use Maple for the lab assignments.
Target Audience: Prospective biology majors with little or no previous
calculus.
Prerequisites: Math ACT score of 28 or grade of C or better in
college algebra or trigonometry.
http://www.math.utah.edu/~adler/oldcourses/math1170/index.html
http://www.math.utah.edu/~adler/oldcourses/math1180/index.html
Contact: Frederick R. Adler, Professor of Biology and of Mathematics,
(801) 581-6848, (801) 585-6202, adler@math.utah.edu
Washington University in St. Louis
Calculus II Data Analysis Laboratory (MATH 132L)
This is a required laboratory component given in conjunction with the
university's regular Calculus II. It reinforces the course concepts from
Calculus II and exposes students to "real world" applications
of the Calculus featuring those concepts. The labs incorporate scientific
experiments from a variety of disciplines, including physics and chemistry
(the Mathematics Department is developing new labs inspired by still other
disciplines), so that students can begin to see Calculus as a powerful,
active, and versatile problem-solving tool capable of being applied in
a variety of situations. Students use the LoggerPro software, a data-gathering
software capable of basic statistical analysis, regression curve-fitting,
and graphing, to help collect and analyze the data. Students are strongly
encouraged to work in teams with one or more partners.
Target Audience: All students enrolled in Calculus II.
Prerequisites: Calculus I.
Corequisites: Calculus II.
http://www.math.wustl.edu/~alex/WebDocs/132LHome.html
Contact: Blake Thornton, Coordinator of Lower Division Teaching, Dept.
of Mathematics, (314) 935-6301, blake@math.wustl.edu
Other Introductory Mathematics Courses
University of California, Davis
Applied Statistics for Biological Sciences (STA 100)
The one-quarter course introduces biology majors to applied statistics.
It covers such topics as probability computation/modeling, estimation,
hypothesis testing, contingency tables, ANOVA, regression, and
implementation of statistical methods using computer packages. It currently
uses the text Statistics for the Life Sciences (Third Edition). Course completion
can satisfy general education requirements in science and engineering.
Target Audience: Majors in biology and other biologically related fields.
Prerequisites: Second-quarter calculus.
http://www.stat.ucdavis.edu/courses/
Contact: Christiana Drake, Associate Professor and Undergraduate Advisor, Department of Statistics,
drake at wald.ucdavis.edu
University of South Carolina
Mathematical Modeling for the Life Sciences (MATH 172)
This one-semester course is less concerned with the mechanical aspects
of computation and more concerned with why we want to do these calculations.
Students form a mathematical model of a changing real world situation,
use a variety of methods to analyze it, and then interpret the calculated
results in the context of the original problem. Students solve problems
by using a blend of numerical, graphical, and analytic methods (manipulation
of formulas), and then communicate the solutions effectively, both in
writing and orally.
Target Audience: Anyone, particularly biology majors, who have
taken the first semester of calculus and desire (require) a second calculus-level
mathematics course.
Prerequisites: A grade of C or better in the first semester of
calculus.
http://www.math.sc.edu/~miller/172/
Contact: Douglas B. Meade, Undergraduate Director of Mathematics,
Dept. of Mathematics, (803) 777-6183, meade@math.sc.edu; Matt Miller,
Professor, Dept. of Mathematics, (803) 777-3690, miller@math.sc.edu
Introductory Science
Courses
University of California, Davis
Modeling in Biology (BIS 20Q)
This two-unit course introduces students to quantitative concepts and techniques
using Mathcad, a software tool that can be used to do routine computations and modeling.
The course centers on downloadable modules that have to be completed by the student every week.
Class meetings consist of weekly lectures and optional two-hour computer labs. The modules
themselves present biological problems that require quantitative thinking.
Target Audience: Majors in biology and other biologically related fields.
Prerequisites: Completion of, or concurrent enrollment in, second-quarter calculus.
http://quantbio.ucdavis.edu/courses.html (includes downloadable example modules)
Contact: Carole Hom, Academic Coordinator, Biological Invasions IGERT and Quantitative Biology,
Department of Biological Sciences, clhom at ucdavis.edu
Utah State University
Integrated Life Science (USU 1350)
This interdisciplinary course focuses on basic concepts of life science.
It demonstrates the role of modeling, prediction, and observation in the
process of scientific discovery, which occurs within an historical and
social context. The course fulfills the university's General Education
Life Sciences Breadth Requirement.
Target Audience: Non-science majors.
Prerequisites: None.
http://www.uintahbasin.usu.edu/riche/live1350opener.htm
Contact: Richard Etchberger, Associate Professor, Natural Resources,
(435) 789-6100, richarde@ext.usu.edu
Other Introductory
Courses
Stony Brook University
Laboratory Methods in Biomedical Engineering (BME 212)
This course provides students with the opportunity to gain insight into
the research process in biomedical engineering, the result of which may
lead to scientific discoveries and technological advances. The class relies
heavily on hands on experience and uses laboratory experiments to teach
experimental design as well as the collection, analysis, interpretation,
and presentation of data. Importantly, the design of all labs is discovery-based
rather than purely instruction-based. Particular emphasis is placed on
the statistical analysis of the collected data. The course also provides
students with the opportunity to write and defend reports based on the
laboratory work, consistent with formats and standards found in scientific
journals in biomedical engineering.
Target Audience: Biomedical Engineering sophomores.
Prerequisites: 1 semester of calculus; 1 semester of freshman
biology; 1 semester of biomedical engineering.
http://www.bme.sunysb.edu
http://bme.sunysb.edu/bme/ugrad/courses.html
Contact: Stefan Judex, Assistant Professor in Biomedical Engineering,
(631) 632-1549, stefan.judex@sunysb.edu
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Advanced Courses in Computational Biology
Advanced Courses in Mathematical Biology
Advanced Courses in Modeling
Other Advanced Courses
Advanced Courses in
Computational Biology
Undergraduate
University of California, Davis
Theory and Practice of Bioinformatics (ECS 124)
This course focuses on the fundamental biological, mathematical, and algorithmic models
underlying bioinformatics. Students will learn a set of common bioinformatics tools, such as sequence analysis, database search, gene prediction,
molecular structure comparison
and prediction, phylogenetic trees, high throughput biology, massive datasets. Topics will include biological applications in molecular biology and genetics.
Target Audience: Majors in biology and other biologically related fields, or minors in quantitative biology and bioinformatics
Prerequisites: One computer programming course, one statistics course, one introductory biology course, some calculus.
http://www.cs.ucdavis.edu/courses/exp_course_desc/124.html
Contact: Daniel M. Gusfield, Professor of Computer Science, gusfield at cs.ucdavis.edu
University of Pennsylvania
Computational Biology (BIOL 536/CIS 535)
Advanced Computational Biology (BIOL 537/CIS 635)
This two-semester sequence provides a rigorous hands-on introduction
to the biological side of computational biology. It covers fundamentals
of algorithms, statistics, and mathematics as applied to biological problems.
Particular emphasis is given to biological problem modeling and theoretical
perspectives. Students are expected to learn basic algorithm principles,
basic mathematical and statistical proofs, and molecular biology. Lectures
are supplemented with demonstrations and computer laboratory assignments.
The course is team-taught by faculty from Biology, Computer & Information
Sciences, and the Center for Bioinformatics.
Target Audience: Computer science and engineering students who
require a better grasp of molecular biology and bioinformatics and biology
students interested in becoming skilled users of molecular genetic analysis
applications.
Prerequisites: College level introductory biology; undergraduate
or graduate level statistics; molecular biology and/or genetics (encouraged);
familiarity with computers (encouraged).
http://www.bio.upenn.edu/courses/S01/BIOL536/
http://www.bio.upenn.edu/courses/S04/BIOL536/
http://www.bio.upenn.edu/courses/F02/BIOL537/
Contact: Warren Ewens, Professor of Biology, (215) 898-7109, wewens@sas.upenn.edu
Advanced Courses in
Mathematical Biology
Undergraduate
University of California, Davis
Mathematical Biology (MAT 124)
This quarter-long course focuses on the methods of mathematical modeling
of biological systems including such topics as difference equations,
ordinary differential equations,
stochastic and dynamic programming models. Students will also learn computer
simulation methods as applied to biological systems. Biological applications will
cover population growth, cell biology, physiology, evolutionary ecology, and protein clustering.
Target Audience: Majors in biology and other biologically related fields
Prerequisites: Knowledge of a computer language or Matlab, one year of calculus, and differential equations.
http://www.math.ucdavis.edu/courses
Contact: Vice Chair for Undergraduate Matters, Department of Mathematics,
vicechair-undergrad@math.ucdavis.edu
University of Washington
Techniques for Mathematical Biology (BIOL 428)
This course equips students to use, rather than prove, many applied mathematics
techniques essential in mathematical biology. Students use symbolic computation
software (Mathematica, Macsyma) to do by computer the kind of mathematical
formula manipulation that mathematicians formerly performed by hand.
Target Audience: Biology majors.
Prerequisites: Calculus (recommended); linear algebra (recommended).
http://www.washington.edu/students/crscat/biology.html
Contact: Garrett M. Odell, Professor, Dept. of Biology, Center
for Cell Dynamics, Friday Harbor Laboratories, (206) 616-0895, odellgm@u.washington.edu
Utah State University
Applied Mathematics in Biology (BIOL/MATH 4230)
This capstone course for the BioMath Minor is team-taught by faculty in
the Departments of Biology and Mathematics & Statistics. The course
revolves around formulation, analysis, and experimental tests of mathematical
models in biology. Students use mathematical, computational and statistical
approaches to investigate biological problems in theoretical and laboratory
settings. The goals are to illustrate the importance of dynamical concepts
in real-world, especially biological, circumstances, to discover some
of the important mathematical results which apply to biological situations,
to give students as realistic an experience as possible in interdisciplinary
mathematical science, and to provide a scientific experience in which
the primary aim is quality of output, not quantity.
Target Audience: Bio-Mathematics minors.
Prerequisites: 2 semesters of biology; 1 semester of linear algebra/differential
equations; programming experience (recommended).
http://www.math.usu.edu/~powell/biomath/index.html
Contact: James W. Haefner, Professor, Dept. of Biology and
Ecology Center, (435) 797-3553, jhaefner@biology.usu.edu; James Powell,
Professor, Dept. of Mathematics & Statistics, (435) 797-1953, powell@math.usu.edu
Graduate/Undergraduate
North Carolina State University
Biomathematics I (BMA/MA/ST 771)
The goal of this course is to enable students to construct, interpret,
analyze, understand, discuss, and critique linear and nonlinear ordinary
differential equations as models of biological systems, by various methods,
and to gain knowledge of the types of behavior that these models exhibit
(equilibria, oscillations, bifurcations, etc.).
Target Audience: Graduate students and advanced undergraduates
in biomathematics, mathematics, statistics, engineering, and biological
sciences.
Prerequisites: Advanced calculus; reasonable background in biology.
http://www4.ncsu.edu/~lubkin/bma771.html
http://www2.acs.ncsu.edu/reg_records/crs_cat/BMA.html#BMA771
Contact: Sharon Lubkin, Associate Professor, Biomathematics Program,
Dept. of Mathematics, (919) 515-1904, lubkin@eos.ncsu.edu
University of Utah
Mathematical Biology (MATH 5110/5120, BIOL 5011/5012)
This one-year sequence is designed to introduce students with
strong mathematical skills to some basic models and methods of mathematical
biology in the biological and medical sciences. The first semester covers
models of population dynamics, reaction kinetics, diseases, and cells
that can be written as ordinary differential questions, delay-differential
equations, and discrete-time dynamical systems. The second semester covers
models using partial differential equations. Students in the second semester
also work on a semester-long project.
Target Audience: Biology majors and mathematics majors. No previous
knowledge of biology is necessary.
Prerequisites: 1 semester of linear algebra/differential equations.
http://www.math.utah.edu/~adler/oldcourses/math5110/index.html
http://www.math.utah.edu/~adler/oldcourses/math5120/index.html
Contact: Frederick R. Adler, Professor of Biology and of Mathematics,
(801) 581-6848, (801) 585-6202, adler@math.utah.edu
Advanced Courses in Modeling
Undergraduate
North Carolina State University
Mathematical Models in Life and Social Sciences (MA 432)
This course includes topics from differential and difference equations,
probability, and matrix algebra applied to the formulation and analysis
of mathematical models in biological and social science (e.g., population
growth).
Target Audience: Primarily mathematics majors, but others are welcome.
Prerequisites: 1 semester of differential equations; 1 semester
of linear algebra; programming language proficiency.
Corequisites: 1 semester of probability.
http://www2.acs.ncsu.edu/reg_records/crs_cat/MA.html#MA432
Contact: Mette Olufsen, Assistant Professor, Dept. of Mathematics,
msolufse@math.ncsu.edu
University of California, Davis
Introduction to Dynamic Modeling in Biology (BIS 132)
This course gives an overview of models based on the notion that biological
entities change over time. It will cover various approaches for
dynamic modeling in the biological sciences,
including matrix models, difference equations, and differential equations and simulation, with emphasis on
understanding the models, their assumptions, and implications.
Target Audience: Majors in biology and biologically related fields, or minors in quantitative biology and bioinformatics.
Prerequisites: One year of calculus and at least one class in biology.
http://biosci.ucdavis.edu/undergrad/minors/qbb/courses/BIS_132.html
Contact: Carole Hom, Academic Coordinator, Biological Invasions IGERT and Quantitative Biology,
Department of Biological Sciences, clhom at ucdavis.edu
University of Minnesota
The Modeling of Nature and the Nature of Modeling (EEB 3963/5963)
This course provides hands-on modeling experiences in the context of biological
applications. Students carry out modeling steps, from developing the model,
to analytical analysis, to developing computer code, to running the models.
Target Audience: Prospective biology majors and beginning biology
graduate students.
Prerequisites: 1 year of calculus including some familiarity with
differential equations.
http://cbs.umn.edu/class/fall2003/eeb/3963/
Contact: Claudia Neuhauser, Professor, Head, and Director of Graduate
Studies, Ecology, Evolution, and Behavior, (612) 624-6790, cneuhaus@cbs.umn.edu
Graduate/Undergraduate
North Carolina State University
Mathematical & Experimental Modeling of Physical Processes II (BMA/MA
574)
This course provides an in-depth treatment of case studies in the application
of mathematics to problems currently under investigation in industrial
and governmental laboratories. The case studies include problems in biology
and electromagnetism. The course covers the background information for
each case study, the development of mathematical models, the analytical
and computational methods appropriate to the models, and model validation
using experimental data collected during field trips to the laboratories.
Target Audience: Graduate students in mathematics and related fields.
Prerequisites: 1 semester of differential equations; 1 semester
of linear algebra; knowledge of high-level programming language.
http://www2.acs.ncsu.edu/reg_records/crs_cat/MA.html#MA574
Contact: Hien Tran, Professor, Dept. of Mathematics, tran@math.ncsu.edu
North Carolina State University
Modeling of Biological Systems (BMA 567)
This course provides an introduction to quantitative modeling in biology.
It covers the use of Forrester diagrams, probabilistic and deterministic
description of dynamic processes, the development of model equations,
simulation methods, and criteria for model evaluation, and examines current
literature dealing with application of models and simulation in biology.
An integral component is student participation in individual and class
modeling projects.
Target Audience: Graduate students in biological sciences and biomathematics.
Prerequisites: 1 semester of calculus.
http://www2.acs.ncsu.edu/reg_records/crs_cat/BMA.html#BMA567
Contact: George Hess, Associate Professor, Dept. of Natural Resources,
grhess@eos.ncsu.edu
University of South Carolina
Mathematical Modeling of Population Biology (MATH 523/BIOL 763/SCCC 411B)
This course offers an opportunity for math majors to see how mathematics
is used in a focused area of application. The goal of the course is to
make the theoretical and modeling literature in population biology accessible
to students so that they will be able to discern how mathematics is used
and to examine critically this usage both analytically and by running
computer simulations. The course is team-taught by faculty in Mathematics
and Biology.
Target Audience: Undergraduates majoring in Mathematics or Biology
and graduate students entering the Ecology program in Biology or the biological
track of Marine Sciences.
Prerequisites: 1 year of calculus; 1 semester of Ecology and Evolution
(recommended).
http://www.math.sc.edu/~miller/763/
Contact: Douglas B. Meade, Undergraduate Director of Mathematics,
Dept. of Mathematics, (803) 777-6183, meade@math.sc.edu; Matt Miller,
Professor, Dept. of Mathematics, (803) 777-3690, miller@math.sc.edu
University of Utah
Mathematical Modeling in Biology (BIOL 5910)
This course is designed for life science students with a perhaps rusty
background in calculus who wish to become comfortable with the mathematical
techniques used to study biological systems. The course covers various
techniques of mathematical modeling of a range of biological systems,
including ecology, physiology, cell biology, and genetics.
Target Audience: Graduate students and undergraduates in the life
sciences.
Prerequisites: 1 year of calculus.
http://www.math.utah.edu/~adler/oldcourses/bio5910/index.html
Contact: Frederick R. Adler, Professor of Biology and of Mathematics,
(801) 581-6848, (801) 585-6202, adler@math.utah.edu
Utah State University
Modeling Biological Systems (BIOL 5020/6020)
This course exposes students to a method of synthesizing empirical data
and formulating theoretical questions, as well as to the tools of mathematical
and computer modeling, and a variety of models from different biological
systems. Students develop the skills to formulate dynamical models of
biological systems, perform computer simulation of mathematical models,
apply model predictions to data sets, document models, and program in
C. Students also complete a modeling project on some biological topic.
Target Audience: Biology majors.
Prerequisites: 1 year of calculus (recommended); 1 semester of
statistics (recommended); programming experience (recommended).
http://www.biology.usu.edu/biol5200-1/
Contact: James W. Haefner, Professor, Dept. of Biology and
Ecology Center, (435) 797-3553, jhaefner@biology.usu.edu
Other Advanced Courses
Undergraduate
Stony Brook University
Linear Systems Analysis with Biomedical Applications (BME 461)
The goal of this course is to offer students an opportunity to learn and
model and simulate static and dynamic physiological systems using linear
systems theory. Simulations and estimation are performed using Matlab
and already developed software.
Prerequisites: 1 semester of Laboratory Methods in Biomedical Engineering;
1 semester of Bioelectricity.
http://www.bme.sunysb.edu
http://bme.sunysb.edu/bme/ugrad/courses.html
Contact: Ki H. Chon, Associate Professor of Biomedical Engineering,
Physiology & Biophysics, Dept. of Biomedical Engineering, (631) 444-7286,
ki.chon@sunysb.edu
Graduate/Undergraduate
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