METHODS IN QUANTITATIVE BIOLOGY

BME 780

Course Description

Focuses on understanding the key methods and principles of quantitative biology through a close reading of the primary literature. Topics covered will 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.

Prerequisties

Graduate/professional standing

Satisfies

This course does not satisfy any prerequisites.

Credits

Offered

Fall

Grade Point Average

3.85

-0.26% from Historical

Completion Rate

100%

No change from Historical

A Rate

70%

-9.58% from Historical

Class Size

50.54% from Historical

Instructors (2025 Fall)

Sorted by ratings from Rate My Professors

Megan MCCLEAN

[email protected]

Rating

Similar Courses

MODELING BIOLOGICAL SYSTEMS

BME/CBE 782

Literature survey of mathematical models in biology at the molecular and cellular levels; application of chemical kinetics and thermodynamics to biological systems; comparison of deterministic and stochastic strategies.

STATISTICAL METHODS FOR MOLECULAR BIOLOGY

BMI/STAT 877

Statistical and computational methods in statistical genomics for human and experimental populations. Review methods for quality control, experimental design, clustering, network analysis, and other downstream analysis of next-generation sequencing studies along with methods for genome wide association studies.

COMPUTATIONAL NETWORK BIOLOGY

BMI/COMPSCI 775

Introduces networks as a powerful representation in many real-world domains including biology and biomedicine. Encompasses theory and applications of networks, also referred to as graphs, to study complex systems such as living organisms. Surveys the current literature on computational, graph-theoretic approaches that use network algorithms for biological modeling, analysis, interpretation, and discovery. Enables hands-on experience in network biology by implementing computational projects.

MATHEMATICAL METHODS FOR SYSTEMS BIOLOGY

BIOCHEM/BMI/BMOLCHEM/MATH 609

Provides a rigorous foundation for mathematical modeling of biological systems. Mathematical techniques include dynamical systems and differential equations. Applications to biological pathways, including understanding of bistability within chemical reaction systems, are emphasized.

QUANTITATIVE SYSTEMS BIOLOGY AND DISEASE

MM&I 760

An overview of methods used in quantitative systems biology, with a focus on biochemical systems relevant to the study of host-pathogen interactions, disease and microbial communities.