SYSTEMS BIOLOGY: MAMMALIAN SIGNALING NETWORKS

BME 556

Course Description

Introduction to the experimental and mathematical modeling techniques used in systems biology through lectures and critical analyses of relevant publications with a primary focus on gene/protein networks and mammalian systems.

Prerequisties

(MATH 319 , MATH 320 , or MATH 375 ), (BME 510 , ZOOLOGY 470 , ZOOLOGY 570 , PSYCH/ZOOLOGY 523 , or BIOCORE 383 ) and Junior Standing, graduate/professional standing, or member of Engineering Guest Students

Satisfies

This course does not satisfy any prerequisites.

Credits

Not Reported

Offered

Not Reported

Grade Point Average

3.48

1.96% from Historical

Completion Rate

100%

1.03% from Historical

A Rate

30%

-20.54% from Historical

Class Size

2.04% from Historical

Cumulative Grade Distribution

Instructors (2025 Fall)

Sorted by ratings from Rate My Professors

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.

BIOLOGICAL INTERACTIONS

BIOCORE 587

A capstone course to build on and integrate the knowledge and skills gained in previous Biocore coursework through readings and analysis of primary scientific literature. Work in small groups to analyze current and emerging topics through the lens of scientific research. Topics include signaling pathways, systems biology, genetic disease, and cancer.

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.

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.

CELL SIGNALING AND HUMAN DISEASE

CRB/MEDICINE 701

Landmark discoveries, as well as current knowledge and controversies in human health, with an emphasis on cancer biology.

SYSTEMS BIOLOGY: MAMMALIAN SIGNALING NETWORKS

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