NOTE: The Friday lectures will include discussing a paper related to the week topic. Papers will be announced about a week prior to the discussion.
Course Objectives: Biology and Control Theory
Feedback loops, which are ubiquitous in engineered systems, play a fundamental role in most biological processes. The survival of any organism strictly depends on its ability to sense and react to changes in its environment. Like electrical and mechanical control systems, cells have the molecular gear necessary to sense, compute and actuate. What are the theoretical and experimental tools available to understand the regulatory circuitry in biochemical systems? This course will provide students with an organized overview of research work between control theory and molecular biology.
The first part of the class will be dedicated to modeling, identification and controltheoretic methods for the analysis of biological networks, following a systems biology perspective. The second part of the class will instead focus on design principles, and the challenges related to constructing biological pathways. Can we build modular and robust networks satisfying performance specifications? This fascinating field offers a wide range of challenging open questions, which the students will be encouraged to critically discuss.
Course Schedule
Week 
Date 
Lecture Topic 
Papers considered in class 
BioControl Journal Club

1

Introduction, Modeling biological systems

29 March (M)

Course overview and objectives, layers of control of gene expression. Slides

Syllabus

NA

2 April (F)

Modeling: Ordinary Differential Equations. Slides

Review on modeling genetic regulatory networks and Modeling the trp operon

Modelbased redesign of transcriptional networks

2

Deterministic and stochastic modeling

6 April (T)

CDS methods for dynamic performance and periodic behaviors. The case of Negative AutoRegulation. Slides

Detection of multistability, bifurcations and hysteresis in biological positivefeedback systems , Negative Autoregulation Speeds the Response Times of Transcription Networks

NA

9 April (F)

Modeling: Stochastic methods, Gillespie algorithm. Slides

Gillespie's fundamental paper

Defining bifurcations in stochastic systems

3

Model identification in biology

13 April (T)

Overview of system identification methods. Slides


NA

16 April (F)

Experimental approaches to identification of biological networks Slides

Using noise for parameter identification, Identification of network connectivity, Experimental identification of network topologies, Using dynamic correlation to reveal regulatory activity

NA

4

Theory of Chemical Reaction Networks

20 April (T)

General introduction and examples. Structural properties of CRNs. Slides

M. Feinberg, original notes , H. Othmer, Theory of Complex Reaction Networks

NA

23 April (F)

Proof of the Deficiency Zero Theorem Slides

Chemical Reaction Network Theory for In Silico Biologists

Structural Sources of Robustness in Biochemical Reaction Networks, Shinar & Feinberg

5

Monotone systems

27 April (T)

Definitions and basic theorems Slides

Monotone Control Systems

NA

30 April (F)

Predicting oscillations; monotonicity in CRNs. The MAPK pathway. Slides

Oscillations in I/O Monotone Systems Under Negative FeedbackOscillations in I/O Monotone Systems Under Negative Feedback

Graphtheoretic characterizations of monotonicity of chemical networks in reaction coordinates.

6

Synthetic biology: design principles

4 May (T)

Design of molecular control systems and demand for gene expression


NA

7 May (F)

Network motifs, structural and dynamical properties



7

Synthetic biology: design principles

11 May (T)

Transcriptional and translational control


NA

14 May (F)

Ultrasensitivity



8

Robustness

18 May (T)

Theoretical aspects of robustness


NA

21 May (F)

Robustness in experimental biology



8

Modularity in control theory and biology

25 May (T)

Timescale separation principle and dynamical systems approaches to modularity


NA

28 May (F)

Modularity in experimental biology



Course Administration
This course is a special topics course in which the lecture material has been prepared by a senior graduate student. The class is P/F only and there is no required homework and no midterm or final exam. Students will be required to work on an individual or team course project.
Course Project
Project proposals are due at 5pm on the last day of the Midterm examination period (May 4) and are due by 5pm on the last day of the final examination period (June 7). Project theme: select a cellular regulatory mechanism, define a list of important features of the system, come up with a modeling framework and carry out an analysis of its properties (e.g. stability, robustness, modularity...).
