BIOMATH M270
Optimal Parameter Estimation and Experiment Design for Biomedical Systems
Biomathematics · 4 units · Graduate courses (200-299)
(Same as Bioengineering M296B, Computer Science M296B, and Medicine M270D.) Estimation methodology and model parameter estimation algorithms for fitting dynamic system models to biomedical data. Model discrimination methods. Theory and algorithms for designing optimal experiments for developing and quantifying models, with special focus on optimal sampling schedule design for kinetic models. Exploration of PC software for model building and optimal experiment design via applications in physiology and pharmacology.
Letter grading.
Requisites
Official UCLA wording
Requisite: course 220 or Bioengineering CM286 or M296A.
BruinTree reads · Prerequisite
needs reviewconfidence 0.90 · from text- · "BIOMATH 220" is not in this catalog version
Requires
Everything that has to come before this course, not just the courses named in the requisite above.
BIOMATH M270
- BIOENGR CM286Computational Systems Biology: Modeling and Simulation of Biological Systems
- LIFESCI 30AMathematics for Life Scientists
- MATH 31ADifferential and Integral Calculus
- MATH 1Precalculus
- LIFESCI 30BMathematics for Life Scientists
Unlocks
What this course is a requisite for, and what those courses lead to in turn.
No course in the catalog lists this as a requisite.