Description

This course is intended for students of diverse educational backgrounds within the natural sciences, who wish to gain competency in applying quantitative theory and logic to address questions in molecular biology. The course is co-taught by a biologist and a physicist, and aims to facilitate interdisciplinary communication between students from different fields. The goal of the course is to introduce the basic knowledge and skills of biology, physics, and mathematics required for a modern, integrated understanding of dynamical biological systems. As the field of molecular biology is advancing from the description of isolated molecular mechanisms to a quantitative understanding also of their interactions and coordinated regulation at the systems-level, the need for mathematical literacy in biology has never been greater. Throughout the course we focus on relatively simple, well-studied biological examples, often from microorganisms, because these systems are most suitable for quantitative studies and modeling.



Topics include the physics and biology of:

• Gene regulatory mechanisms
• Signal transduction
• Mutational analysis
• Bi-stability and noise in genetic networks
• Bacterial growth physiology and resource allocation
• Modeling of biological networks.
  
   

Knowledge:

At the conclusion of the course, the student will be able to:

• Describe the basic processes in gene expression, the macromolecules involved, and the interdepence of gene expression and growth.
• Describe and explain molecularly different gene regulatory mechanisms.
• Describe the functioning of feedback loops in biological systems, including gene regulatory networks and signal transduction pathways.
• Describe and appreciate the power of mutational analysis.
• Describe mechanisms that provide specificity, sensitivity, amplification and adaptation in a signal transduction pathway.

Skills:

At the conclusion of the course, the student will be able to:

• Critically evaluate scientific articles that use quantitative reasoning to investigate biological phenomena.
• Critically evaluate the suitability of laboratory experiments designed to test a particular hypothesis.
• Understand the steps in gene expression as stochastic processes and explain the role of noise in gene expression.
• Explain the difference between genetic screens and selections and how to apply them to solve biological problems.
• Plan simple genetic experiments to address a particular biological question.
• Modify Python code to simulate biological processes and examine the effect of altering different parameters.
• Analyze positive and negative feedback loops using ordinary differential equations.
• Analyze bistability and oscillation seen in biological systems.
  
   

Competences:

At the conclusion of the course, the student will be able to:

• Effectively discuss scientific problems and ideas with peers from disciplines other than their own.
• Collaborate with colleagues from different fields to solve interdisciplinary problems.
• Identify suitable collaborators from different disciplines to address particular aspects of an interdisciplinary problem.

Recommended qualifications

Academic qualifications equivalent to a BSc degree is recommended.