Computing and Mathematics Across the Sciences
Links and Resources
Books and Reports
- Introduction to Scientific Computation and Programming by Daniel Kaplan
- Introduction to Statistical Modeling by Daniel Kaplan
- Discovering Genomics, Proteomics, and Bioinformatics by A. Malcolm Campbell and Laurie J. Heyer
- Introductory Statistics with R by Peter Dalgaard
- Python Programming in Context by Bradley N. Miller and David L. Ranum
- Practical Programming: An Introduction to Computer Science Using Python by Jennifer Campbell, Paul Gries, Jason Montojo, and Greg Wilson
- BIO 2010
- Math & BIO 2010: Linking Undergraduate Disciplines
- Curriculum Renewal Across the First Two Years (CRAFTY)
- Distinctively American: The Residential Liberal Arts College
Academic Programs
- Computational Science at Wittenberg
- Genomics at Davidson
- Integrated Quantitative Science at Richmond
- Computational Studies at Capital University
- Integrated Science at Princeton
- Interdisciplinary Computer Science at Virginia
- Genomics at Wheaton
Courses
- Math 155: Introduction to Statistical Modeling (Macalester)
- CS 121: Introduction to Scientific Programming (Macalester)
- Math/CS 365: Scientific Computation (Macalester)
- COMP/MATH 260: Computational Models and Methods (Wittenberg)
- CS 187: Scientific Computing: Discrete Systems (Haverford)
- COS 126: General Computer Science (Princeton)
- COS 323: Computing for the Physical & Social Sciences (Princeton)
- CS 112: Computation for the Sciences (Wellesley)
- CMSC 155: Introduction to Scientific Computing (Richmond)
- STAT 598Z: Concepts in Computing with Data (Purdue)
Software