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UNIVERSITY OF WISCONSIN-MADISON COURSES
BME 780: METHODS IN QUANTITATIVE BIOLOGY (FALL 2017, 2018, 2019, 2020)
This course focuses on understanding the key methods and principles of quantitative biology through a close reading of the primary literature. Class periods will alternate between a lecture outlining the basics of a particular quantitative biology technique and a student-led presentation of a key paper illustrating the use of that technique. Topics covered include deterministic and stochastic methods for modeling cellular systems, techniques in systems and synthetic biology, image processing tools and image analysis for biology, data-driven network models, genomic approaches, single-molecule approaches, and key computational biology tools. This course is intended for graduate students from a variety of backgrounds who are interested in pursuing quantitative biology during their graduate studies. Students who have a background in differential equations and linear algebra and cell biology will find themselves well prepared for this course.
BME 330: ENGINEERING PRINCIPLES OF MOLECULES, CELLS, AND TISSUES (FALL 2016, 2017, 2018, 2020)
This course provides an introduction to the fundamental principles of kinetics and transport that are relevant for the analysis of biological systems. Topics covered include concepts of reaction rate, stoichiometry, equilibrium, momentum/mass transport, and the interaction between transport and kinetics in biological systems.
BME 200-402: BIOMEDICAL ENGINEERING DESIGN (SPRING/FALL 2015, SPRING 2016, 2017, 2019, 2020)
The biomedical engineering undergraduate program was founded with design at the heart of the curriculum. Biomedical engineering design is a rigorous six-semester, team-based design sequence where undergraduates solve real-world, client-based design problems. This design sequence breaks down class boundaries, forms mentored relationships, actively involves each student in the evolution of the design course and department, and engages the students in active learning.
BIOCHEMISTRY 872: SELECTED TOPICS IN BIOPHYSICAL CHEMISTRY (SPRING 2017)
Biochemistry 872 is an advanced graduate topics course based on recent literature in biophysical sciences. The course focuses on biophysical techniques.
PRINCETON UNIVERSITY COURSES
ISC 236: A QUANTITATIVE, INTEGRATIVE INTRODUCTION TO GENETICS AND GENOMICS (Fall 2014)
An integrated, mathematically and computationally sophisticated introduction to genetics, developmental biology, genomics, evolution and population genetics. This is the first course in the year-long multidisciplinary integrated science sequence.
QCB301/MOL301: EXPERIMENTAL PROJECT LABORATORY IN QUANTITATIVE AND COMPUTATIONAL BIOLOGY (FALL 2009, 2010, 2011, 2012, 2013)
An intensive double credit course focusing on state-of-the-art experimental design and practice in quantitative biology. Emphasis is placed on functional genomics using global genome-wide measurements (e.g. microarray gene expression, sequence, phenotype) to understand physiological and evolutionary processes. Begins with a short introduction to technology and principles, followed by the design and execution of independent projects done by pairs of students in collaboration, with the continuing guidance and advice of the teaching staff
HARVARD UNIVERSITY COURSES
APPLIED MATHEMATICS 115: MATHEMATICAL MODELING (SPRING 2009)
Abstracting the essential components and mechanisms from a natural system to produce a mathematical model, which can be analyzed with a variety of formal mathematical methods, is perhaps the most important, but least understood, task in applied mathematics. This course approaches a number of problems without the prejudice of trying to apply a particular method of solution. Topics drawn from biology, economics, engineering, physical and social sciences.
APPLIED MATHEMATICS 105B: ORDINARY AND PARTIAL DIFFERENTIAL EQUATIONS (SPRING 2006, 2007)
Ordinary differential equations: power series solutions; special functions; eigenfunction expansions. Review of vector calculus. Elementary partial differential equations: separation of variables and series solutions; diffusion, wave and Laplace equations. Brief introduction to nonlinear dynamical systems and to numerical methods.