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Dynamical Models In Molecular Biology
Second title: Dynamical Models In Molecular Biology
Provider: Faculty of Science

Activity no.: 5077-21-01-31
	Enrollment deadline: 21/11/2021

Date and time	22.11.2021, at: 00:00 - 28.01.2022, at: 00:00
Regular seats	30
ECTS credits	7.50

Contact person	Sine Lo Svenningsen E-mail address: sls@bio.ku.dk

Enrolment Handling/Course Organiser	Sine Lo Svenningsen E-mail address: sls@bio.ku.dk
Written language	English
Teaching language	English
Semester/Block	Block 2
Scheme group	C
Exam requirements	To be qualified for the exam, a mandatory group presentation must first be approved.
Exam form	Oral examination
Exam details	25-minute oral exam withour preparation time
Exam aids	Without aids
Grading scale	7 point grading scale
Censorship form	Several internal examiners

Content 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 regulations at the systems-level, the need for mathematical literacy in biology has never been greater. 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. 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 • Growth physiology and resource allocation • Mutational analysis • Bi-stability and noise in genetic networks • Modeling of biological networks, including modification of simple Python programs. Learning outcome Knowledge: At the conclusion of the course, the student will be able to: • Describe the power of mutational analysis. • Describe the basic processes in gene expression, and the components, speed and error rates of macromolecules involved in gene expression. • 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 the dynamics of signal transduction. • 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. • Understand the processes of 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. • Describe gene regulatory mechanisms with ordinary differential equations. • Analyze positive and negative feedback loops using ordinary differential equations. • Analyze bistability and oscillation seen in biological systems. 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. Literature See Absalon. Teaching and learning methods Each week, we read a scientific article that has made a significant contribution to basic biology through the use of quantitative reasoning and theory. An introduction to each paper is provided in the form of a lecture on the biological and mathematical concepts used. The students then read the article at home, and we discuss it in the classroom. In addition, a weekly exercise session provides an opportunity for the students to use the tools they learned to solve simple problems in a group setting. At the conclusion of the course, a group of students with different backgrounds help each other understand an assigned interdisciplinary article, and presents it to the class.

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