This page contains links to books, projects and exercises used in undergraduate and graduate courses to teach quantitative cell biology. Quantitative cell biology is defined here as the research field that measures biological properties and uses those measurements to posit the behavior of the biological system. Quantitative Cell Biology makes use of computer modeling to test the hypothesis generated from experimental measurements.
Virtual Cell Curricular Exercises - Compilation of materials that use the Virtual Cell to teach biological concepts or aspects of modeling.
Computational Cell Biology - Christopher P. Fall, Eric S. Marland, John M. Wagner, John J. Tyson, Springer, 2004. This textbook provides an introduction to dynamic modeling in cell biology.
The Geometry of Biological Time - Art Winfree, Springer, 2001. Written for advanced undergraduates, graduate students and researchers, this book presents a mathematical description of periodic processes in biological systems and their non-living analogues.
BioNetGen - A web-based tool for automatically generating a biochemical reaction networks from user-specified rules for biomolecular interactions.
cellmigrationgateway - modeling software
CellML- The CellML language is an open standard based on the XML markup language at the University of Auckland and affiliated research groups.
CompCell Bio Web - Development site for teaching modules on quantitative cell biology.
E-Cell - A Multi-Algorithm, Multi-Timescale Simulation Software Environment.
Kitware - Professional Visualization Solutions, Tools and Support.
MCell - General Monte Carlo Simulator of Cellular Microphysiology.
SBML - The Systems Biology Markup Language (SBML) is a computer-readable format for representing models of biochemical reaction networks.
Cell Image Library - The Cell an Image Library from the American Society for Cell Biology
Cell Organizer - From the Center for Bioimage Infromatics
SLIF - Subcellular Location Image Finder - Finds fluorescent images in on-line journal articles and indexes them based on cell line, labeled proteins and resolution.