Explore the fascinating world of myxobacteria in this seminar by Prof. Oleg Igoshin from Rice University. Delve into the mechanisms of pattern formation and emergent collective behaviors exhibited by these remarkable microorganisms. Learn about chemical signals, multicellularity, and data-driven models used to understand their complex interactions. Discover how traffic jam effects, self-organized behavior, and collective cell alignment contribute to the unique characteristics of myxobacteria. Examine active matter principles, self-propelled rods, and orientation memory in bacterial colonies. Investigate mechanical interactions, coarse-grain approaches, and pneumatic alignment in bacterial growth. Gain insights into how myxobacteria communicate, aggregate, and form intricate patterns through various biological and physical processes.
Uncovering Mechanisms of Pattern Formation and Emergent Collective Behaviors in Myxobacteria
ICTP-SAIFR via YouTube
Overview
Syllabus
Introduction
What is your research about
What is your motivation
What is your favorite bacteria
Engines
Chemical signals
Multicellularity
Learning from data
Fluorescent microscopy
Behavioral case
Traffic jam model
Traffic jam effect
Datadriven models
Selforganized behavior
Open loop model
Projection
Collective Cell Alignment
Active Matter
Selfpropelled rods
Spring and North model
Collision
Simulation
Experiments
Orientation Memory
Selforganized patterns
White spaces
Mechanical interactions
The neighbors in cells
Bacteria cannot actively steer
Coarse grain approaches
How bacteria grow
Pneumatic alignment
How do they know
Contract signal
Aggregates
Conclusion
Alignment
Taught by
ICTP-SAIFR
