faculty across all levels of chemistry courses are incorporating quantitative thinking as a critical skill for students to learn. in addition to making sure students learn the discipline-specific chemistry concepts and associated mathematics, courses at the undergraduate and higher levels are also teaching computation – such as how to access, visualize, and analyze data, and the skills required to accomplish these tasks. instructors choose matlab because students can get started easily, work in a single platform, and quickly find helpful resources.
teaching computation and domain knowledge in a single course is challenging, and thus, requires some forethought and a well-organized course framework. also necessary are problem sets and other resources, such as videos, for students to learn required foundation material and develop necessary programming skills.
introducing matlab to students
- (interactive tutorial)
- getting started with matlab (10:00) (video)
tools and code examples
- – toolbox for simulating and fitting epr spectra
- (supports nmr, epr, mri and more)
- data acquisition examples
interactive apps
course curricula
case studies & pedagogy
- - video
textbooks
additional resources
- bioinformatics toolbox
- access standard file formats for biological data, such as protein data bank (pdb), mass spectrometry data, online databases, websites, and more
- structural analysis: visualize and analyze 3-d structures of molecules
- mass spectrometry and bioanalytics
- connect to data acquisition cards, devices, and modules
teach with live editor
combine code, output, and formatted text to create an interactive, executable narrative.
visualize the 3-d structure of a molecule
import protein information from the protein data bank repository.