BMT-53506 Single Cell Signal Processing, 5 cr
Additional information
Suitable for postgraduate studies.
Person responsible
Olli Yli-Harja, Meenakshisundaram Kandhavelu
Lessons
Implementation | Period | Person responsible | Requirements |
BMT-53506 2017-01 | 2 |
Meenakshisundaram Kandhavelu Olli Yli-Harja |
Participation in lectures, lab work and final presentation. |
Learning Outcomes
In this course, the student will learn to: - practical experience in single cell imaging and to solve problems involving measurement data. - perform data acquisition from raw data. - independently search for information and available methods to solve practical problems. - present results, methods and conclusions in written and oral reports.
Content
Content | Core content | Complementary knowledge | Specialist knowledge |
1. | Defining the area of single cell signal processing for health and biology, key terminology, needs and benefits. | Current topics in single cell signal processing methods in health informatics research. | |
2. | Applications of signal processing in systems biology and health informatics, and their key benefits. | Examples of applications with key benefits. |
Instructions for students on how to achieve the learning outcomes
The course will provide an overview on applications of single cell signal processing for health and biology. The emphasis is on computational methods for processing, analyzing and modelling of health and biological data. After the course the student will be able to: - define what are single cell signal processing methods and their application in health Informatics and which subareas they cover. - describe what is the need of single cell signal processing for health and biology. - describe some typical applications of signal processing tools for health and biology, and their benefits. - list basic signal processing methods used in these disciplines and use specific ready-made computational tools. - produce a summary of one of the current research topics in these fields.
Assessment scale:
Numerical evaluation scale (0-5)
Additional information about prerequisites
The course exercises are mainly based on Matlab. Previous knowledge is helpful but it is not a requirement.
Correspondence of content
There is no equivalence with any other courses