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Biological Physics (2023/2024: Periode 4)
Cursusdoel
Upon successful completion of this course, students will be able to:
- Apply dimensionality analysis to reason about a system quantitatively
- Simplify and abstract a biological problem to a physical model described by equations. More specifically:
- Use classical mechanics to describe and quantify motion.
- Use methods to mathematically describe oscillations, important for the perception of sound or gene expression
- Use continuum mechanics to describe and understand the material properties of tissue;
- Use statistical physics to describe and understand random motion of biomolecules;
- Solve models analytically and numerically;
- Prepare a line of argument in words and justify it with equations;
- Present a scientific argument in front of peers;
- Adapt to and follow interdisciplinary terminology and reasoning from physics, biology, and computer science.
Vakinhoudelijk
In this course students develop a physical understanding of biological phenomena. Students learn to apply the fundamental laws of physics to biological problems.
Introduction:
The structure and function of all living cells are governed by fundamental laws of physics and chemistry. Therefore, to understanding biological systems, it is critical to develop a physical understanding of natural phenomena. Physical laws, usually expressed by mathematical equations, are scientific generalizations that represent a summary description of nature. In doing so, this conceptual framework facilitates organization of observations and other data in a meaningful way and helps to identify the most critical parameters of a given process, as well as their interplay. Furthermore, it can be used to predict future outcomes when system-dependent conditions are specified. Because of the increasing use of sophisticated technology in biological experiments, it is now possible to acquire large amounts of quantitative data and to perform precise quantitative perturbation experiments. Therefore, it is necessary for all researchers in the Life Sciences to have a quantitative intuition about living systems in order to interpret data, to identify the most important aspects, and to plan critical experiments. In this course we will lay the foundation to develop such skills.
Set up of this course:
This concept-context course is structured around two weekly plenary lectures and one tutorial during which relevant biological case studies and examples are used to introduce the fundamental physical concepts essential in the study of biological phenomena. For instance, classical mechanics is applied to investigate oscillations important for the perception of sound, continuum mechanics to describe the flow of developing tissue, and statistical physics to investigate random motion of molecules. Although the language of physics is mathematics, the emphasis of the course is on physics, not mathematics. Students are introduced to the fundamental tools for quantitative descriptions, study different branches of physics, and learn to apply them to biological problems. Throughout the course, students engage with the material in a diverse set of assignments and computational exercises. This learning-by-doing strategy teaches students how to use considerations based on fundamental physical principles to develop a quantitative intuition about biological systems. Individual e-assessments enable students and teachers to monitor knowledge and understanding as the course progresses.
Relation to other courses:
This course builds on the knowledge and skills students acquired in the course “Mathematics and Programming” (MBLS-102), expands this knowledge with an understanding of the physical laws underpinning all biological processes, and applies this to the wider context of living systems. This course provides the fundament for more advanced biological physics courses.
Teaching format course (estimation):
This course is set up according to a Concept-Context teaching method. Concept-context rich education is a form of education in which subject matter (“concepts”) is offered to students in various “contexts” in order to deepen subject knowledge, enhance transfer of knowledge and skills, and building connections among subjects. Moreover, an authentic and relevant context has been shown to increase students’ motivation to learn. Lectures with experimental demonstrations are alternated with tutorials.
A Flipped Classroom approach is used for tutorials: students complete the contextual assignments and computational exercises prior to the tutorial. Students present their results to the teacher and to fellow students in the tutorial. The tutorials serve to clarify any remaining questions resulting from the completed assignments and to initiate a curiosity-driven exploration of quantitative models.
Lectures = 25%
Tutorials = 25% (ratio max 30/group)
Practicals (programming) = 25%
Presenting = 5%
Writing = 5%
Self study = 15%
Grading (see course manual for details):
test/exam part 1 (40%)
test/exam part 2 (40%)
Individual presentation of physics assignments (10%)
Group presentation of programming exercises (10%)
Introduction:
The structure and function of all living cells are governed by fundamental laws of physics and chemistry. Therefore, to understanding biological systems, it is critical to develop a physical understanding of natural phenomena. Physical laws, usually expressed by mathematical equations, are scientific generalizations that represent a summary description of nature. In doing so, this conceptual framework facilitates organization of observations and other data in a meaningful way and helps to identify the most critical parameters of a given process, as well as their interplay. Furthermore, it can be used to predict future outcomes when system-dependent conditions are specified. Because of the increasing use of sophisticated technology in biological experiments, it is now possible to acquire large amounts of quantitative data and to perform precise quantitative perturbation experiments. Therefore, it is necessary for all researchers in the Life Sciences to have a quantitative intuition about living systems in order to interpret data, to identify the most important aspects, and to plan critical experiments. In this course we will lay the foundation to develop such skills.
Set up of this course:
This concept-context course is structured around two weekly plenary lectures and one tutorial during which relevant biological case studies and examples are used to introduce the fundamental physical concepts essential in the study of biological phenomena. For instance, classical mechanics is applied to investigate oscillations important for the perception of sound, continuum mechanics to describe the flow of developing tissue, and statistical physics to investigate random motion of molecules. Although the language of physics is mathematics, the emphasis of the course is on physics, not mathematics. Students are introduced to the fundamental tools for quantitative descriptions, study different branches of physics, and learn to apply them to biological problems. Throughout the course, students engage with the material in a diverse set of assignments and computational exercises. This learning-by-doing strategy teaches students how to use considerations based on fundamental physical principles to develop a quantitative intuition about biological systems. Individual e-assessments enable students and teachers to monitor knowledge and understanding as the course progresses.
Relation to other courses:
This course builds on the knowledge and skills students acquired in the course “Mathematics and Programming” (MBLS-102), expands this knowledge with an understanding of the physical laws underpinning all biological processes, and applies this to the wider context of living systems. This course provides the fundament for more advanced biological physics courses.
Teaching format course (estimation):
This course is set up according to a Concept-Context teaching method. Concept-context rich education is a form of education in which subject matter (“concepts”) is offered to students in various “contexts” in order to deepen subject knowledge, enhance transfer of knowledge and skills, and building connections among subjects. Moreover, an authentic and relevant context has been shown to increase students’ motivation to learn. Lectures with experimental demonstrations are alternated with tutorials.
A Flipped Classroom approach is used for tutorials: students complete the contextual assignments and computational exercises prior to the tutorial. Students present their results to the teacher and to fellow students in the tutorial. The tutorials serve to clarify any remaining questions resulting from the completed assignments and to initiate a curiosity-driven exploration of quantitative models.
Lectures = 25%
Tutorials = 25% (ratio max 30/group)
Practicals (programming) = 25%
Presenting = 5%
Writing = 5%
Self study = 15%
Grading (see course manual for details):
test/exam part 1 (40%)
test/exam part 2 (40%)
Individual presentation of physics assignments (10%)
Group presentation of programming exercises (10%)
Werkvormen
Computerpracticum
Hoorcollege
Inzage
Presentatie
Werkcollege
Zelfstudie
Hoorcollege
Inzage
Presentatie
Werkcollege
Zelfstudie
Toetsing
Eindresultaat
Verplicht | Weging 100% | ECTS 7,5
Ingangseisen en voorkennis
Ingangseisen
Er is geen informatie over verplichte ingangseisen bekend.
Voorkennis
Er is geen informatie over benodigde voorkennis bekend.
Voertalen
- Engels
Cursusmomenten
Gerelateerde studies
Tentamens
Er is geen tentamenrooster beschikbaar voor deze cursus
Verplicht materiaal
-
BOEKIntroductory physics for biological scientist, Christof Aegerter, 2018, Cambridge Univ. PressISBN: 9781108525862
Aanbevolen materiaal
Er is geen informatie over de aanbevolen literatuur bekend
Coördinator
| dr. F.M. Berger | f.m.berger@uu.nl |
Docenten
| M. Locarno MSc | m.locarno@uu.nl |
| dr. F.M. Berger | f.m.berger@uu.nl |
Inschrijving
Let op: deze cursus is niet toegankelijk voor studenten van andere faculteiten, bijvakkers mogen zich dus niet inschrijven.
Inschrijving
Van maandag 29 januari 2024 tot en met vrijdag 23 februari 2024
Na-inschrijving
Van dinsdag 2 april 2024 tot en met woensdag 3 april 2024
Inschrijving niet geopend
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