SGN-53206 Cell Culturing, Microscopy and Cell Image Analysis, 3 cr
Additional information
This course is lectured every year.
Course webpage: http://www.cs.tut.fi/~sanchesr/SGN-53206/index.htm
Suitable for postgraduate studies
Person responsible
Andre Sanches Ribeiro
Lessons
Implementation 1: SGN-53206 2015-01
| Study type | P1 | P2 | P3 | P4 | Summer |
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Requirements
Final project work (40% of the final grade). Final reports on the experimental work and the results obtained from the image analysis (60%). To pass the course, the student is required to: a) Execute the final project and deliver three reports on the experimental works. b) Attend at least 80% of the lessons.
Learning Outcomes
From this course the student will know how to prepare standard bacterial cultures and will have basic knowledge of how to operate microscopes. The student will also be introduced to state of the art software for cell image analysis and profiling. Finally, the students will gain insight on the interpretation of the results and will obtain knowledge on the efficiency of the algorithms when applied to real data. After the course, the student will be able to: 1) Identify and define experimental techniques related to bacterial culturing and cell imaging. Demonstrate the ability to apply these methods to extract information from biological systems. 2) Interpret data generated from the microscope, classify strengths and weaknesses of the bright field and fluorescence measurements, summarize results of the measurements and explain the connection between measurements and underlying biological processes. 3) Implement experimental techniques and apply them to extract data from biological systems. Calculate statistical properties of the features measured at the single cell level. Apply knowledge of existing software to extract the relevant information. 4) Analyze results of the measurements. Compare the various methodologies used for measuring a variable such as cell fluorescence levels. 5) Compare and appraise different algorithms for extracting quantifiable features from the images, and interpret the results from the measurements. 6) Create and develop new features that would improve the algorithms for specific goals.
Content
| Content | Core content | Complementary knowledge | Specialist knowledge |
| 1. | Principles of cell culturing of bacteria and microscopy | ||
| 2. | Experimental cell culturing of bacteria | ||
| 3. | Imaging fluorescent bacteria under the microscope | In this lesson, the students will use the fluorescence microscope to take images of the bacteria that were cultured in the previous lecture. Bright field images will also be taken as well. There is a discussion on what images are most suitable for the image analysis procedure. | |
| 4. | State of the art tools for cell images analysis | ||
| 5. | Segmentation and extraction of information about the cells using CellProfiler |
Instructions for students on how to achieve the learning outcomes
Project work (40% of the final grade). Final reports on the experimental work and the results obtained from the image analysis (60%). To pass the course, the student is required to: a) Execute the project work and deliver three reports on the experimental works. b) Attend at least 80% of the lessons.
Assessment scale:
Numerical evaluation scale (1-5) will be used on the course
Study material
| Type | Name | Author | ISBN | URL | Additional information | Examination material |
| Book | Molecular Biology of the Cell, 4th edition, Bruce Alberts, Alexander Johnson, Julian Lewis, Martin Raff, Keith Roberts, and Peter Walter. | No | ||||
| Journal | Fermino, A. M., Fay, F. S., Fogarty, K. and Singer, R. H., Visualization of single RNA transcripts in situ, Science, 280, 1998, 585-9. | No | ||||
| Journal | Reue, K., mRNA quantitation techniques: considerations for experimental design and application, J. Nutr. 128, 1998, 2038-44. | No | ||||
| Lecture slides | Lecture slides | Yes | ||||
| Other online content | CellProfiler | Carpenter AE, Jones TR, Lamprecht MR, Clarke C, Kang IH, Friman O, Guertin DA, Chang JH, Lindquist RA, Moffat J, Golland P, Sabatini DM (2006) CellProfiler: image analysis software for identifying and quantifying cell phenotypes. Genome Biology 7:R100. | Yes | |||
| Other online content | ImageJ | Rasband, W.S., ImageJ, U. S. National Institutes of Health, Bethesda, Maryland, USA, http://rsb.info.nih.gov/ij/, 1997-2009 | Yes |
Correspondence of content
| Course | Corresponds course | Description |
| SGN-53206 Cell Culturing, Microscopy and Cell Image Analysis, 3 cr | SGN-6126 Cell culturing, microscopy and cell image analysis, 3 cr |