Systems Biology and Synthetic Biology

Overview

Our objective is to study current problems in systems and synthetic biology that are now frequently analyzed using mathematical modeling, quantitative analysis. The focus will be to understand aspects of embryonic development, and signaling cascades, gene control networks, and associated modeling and mathematical tools necessary to interrogate these biological systems. Our specific target here is to:

• study basic material on how to model stochastic and deterministic biochemical interactions, how to develop a model of gene control networks, and how to develop morphogen-mediated signaling model for species development.

• read and understand scientific papers that include coupled biological/mathematical analysis.

• learn the effective ways to communicate between disciplines for future interdisciplinary projects.

Morphogen Gradient Formation

• The Chemical Basis of Morphogenesis

• do morphogen gradients arise by diffusion

• Morphogen Gradient Formation

• The interpretation of morphogen gradients

Pattern Formation and Scaling

Gene Control and Regulatory Networks

• Modeling and Simulation of Genetic Regulatory Systems

Boolean Network for Biology

• Boolean modeling in systems biology: an overview of methodology and applications

• Concepts in Boolean network modeling: What do they all mean?

• Logic-Based Models for the Analysis of Cell Signaling Networks

• Metabolic stability and epigenesis in randomly constructed genetic nets

• Boolean network simulations for life scientists

• Robustness and fragility of Boolean models for genetic regulatory networks

• Statistical Mechanics of Complex Networks

• Scale-free networks in cell biology

• Biological switches and clocks

Information Theoretic Approach

• How Information Theory Handles Cell Signaling and Uncertainty

• Cellular noise and information transmission

• The application of information theory to biochemical signaling systems

• Information flow and optimization in transcriptional regulation

• Statistics of Natural Images: Scaling in the Woods

• Positional information, in bits