Difference between revisions of "Concept"

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'''Background''': Studies in Life Science traditionally have put less emphasis on mathematical training than other scientific disciplines like physics and engineering. Yet, an increasing fraction of biological problems can only be addressed with some level of mathematical, statistical or computational support. Accordingly, today an expanding community of formally trained scientists studies biological problems. At the same time many biologists lack basic knowledge and experience in applying mathematical concepts and tools to assist their research.  
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'''Background''': Many biological questions can only be addressed with some level of mathematical, statistical or computational expertise. Yet, studies in Life Science traditionally have put less emphasis on mathematical training than other scientific disciplines like physics and engineering. Students of biology should therefore improve their mathematical skills to stay competitive in many fields of biological research.
  
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'''Concept''': The fact that a significant number of biology students are uncomfortable in using mathematics may be rooted already in their high school education or even beyond. The frontal courses offered to biology students at UNIL (which are usually taught by EPFL lecturers) may help brushing up basic mathematical skills of some students, but are unlikely to reach those who have long lost their interest and self-confidence in solving mathematical problems.  
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'''Goals''': This course aims to improve mathematical and computational skills of undergraduate students in the 3rd year by studying a specific biological questions that requires some mathematical skills.
  
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The central idea of this course is to offer an alternative which aims at gaining mathematical strength by addressing a practical problem within a biological question which can only be solved with some piece of mathematics. Thus the emphasis is on learning by doing rather than an abstract approach where mathematical insights are detached from biological applications: Small groups of two to four students will be jointly supervised by a “biologist” and a “mathematician” (or people with a mutual background in some cases) in well-defined biological projects that require a particular mathematical skill.
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'''Contents''': The idea behind this course is that for many students a mathematical concept or tool is best understood in the context of an application. Thus rather than learning an abstract mathematical theory, this course is very applied and the learning process is driven by a biological question. For example, students may be confronted with big datasets (such genomic profiles for thousand of genes in hundreds of samples) and learn how to study such data using approaches like principle component analysis or clustering. Topics like regression analysis may be explored to associate different types of biological observation (e.g. genotypes and some phenotypes). Network concepts and analysis methods are taught in the context of protein interactions or other biological networks. All project include real biological or biomedical data and address questions that are of current research interest, while  requiring some non-trivial mathematical analysis whose outcome is open. Students will work in small groups of 2-4 students on projects under the weekly supervision of a teaching assistant (usually a PhD student or post-doc) with regular joint meetings: In the first joint meeting the project choices will be presented, in the second joint meeting students will present their projects and preliminary results, and in the final meeting the completed projects will be presented.
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'''Prerequisites''': All 3rd year students are welcome. Exceptionally we also permit 2nd year students if free places are available. Basic math, stats and programming knowledge is a big plus, but the key requirement is an interest to improve these skills.
  
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'''Target audience''': This is an optional course open to UNIL students from their third semester in life science studies. While it is focused at BA students it is also open to other interested students.
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'''Evaluation''': Up 5 points of the final grade are based on the performance in the final presentation. Here we look at the results, the depth of the student teams' analysis, and how well they are presented. 1 point of the final grade is based on the individual study performance throughout the course.
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(back to main page of [[Course: "Solving Biological Problems that require Math"]])
 
(back to main page of [[Course: "Solving Biological Problems that require Math"]])

Latest revision as of 18:28, 11 March 2024

Background: Many biological questions can only be addressed with some level of mathematical, statistical or computational expertise. Yet, studies in Life Science traditionally have put less emphasis on mathematical training than other scientific disciplines like physics and engineering. Students of biology should therefore improve their mathematical skills to stay competitive in many fields of biological research.

Goals: This course aims to improve mathematical and computational skills of undergraduate students in the 3rd year by studying a specific biological questions that requires some mathematical skills.

Contents: The idea behind this course is that for many students a mathematical concept or tool is best understood in the context of an application. Thus rather than learning an abstract mathematical theory, this course is very applied and the learning process is driven by a biological question. For example, students may be confronted with big datasets (such genomic profiles for thousand of genes in hundreds of samples) and learn how to study such data using approaches like principle component analysis or clustering. Topics like regression analysis may be explored to associate different types of biological observation (e.g. genotypes and some phenotypes). Network concepts and analysis methods are taught in the context of protein interactions or other biological networks. All project include real biological or biomedical data and address questions that are of current research interest, while requiring some non-trivial mathematical analysis whose outcome is open. Students will work in small groups of 2-4 students on projects under the weekly supervision of a teaching assistant (usually a PhD student or post-doc) with regular joint meetings: In the first joint meeting the project choices will be presented, in the second joint meeting students will present their projects and preliminary results, and in the final meeting the completed projects will be presented.

Prerequisites: All 3rd year students are welcome. Exceptionally we also permit 2nd year students if free places are available. Basic math, stats and programming knowledge is a big plus, but the key requirement is an interest to improve these skills.

Evaluation: Up 5 points of the final grade are based on the performance in the final presentation. Here we look at the results, the depth of the student teams' analysis, and how well they are presented. 1 point of the final grade is based on the individual study performance throughout the course.

(back to main page of Course: "Solving Biological Problems that require Math")

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