Kaski, Laboratory of Computer and Information Science, Helsinki
University of Technology|
|In Collaboration with||Doc. Christophe Roos and Jukka Matilainen,
|Assistant||M.Sc. Merja Oja, Department of Computer Science, University of Helsinki|
|Semester||Spring 2006 (during periods III and IV)|
|Sessions|| On Thursdays at 14-16 in lecture hall T4
Konemiehentie 2, Otaniemi, Espoo. The first session on 19.1.2006. Note: Demo of the modeling platform during the first session.
|Registration||TKK students: WebTopi, others: send mail to email@example.com|
New insights into cell functioning, and the effects of the cellular and molecular-levels on the organism level, are being sought by reverse-engineering measurement data with various modeling and data-analysis methods. Various kinds of systems-level data can be collected (genomics, gene expression, metabolomics, proteomics, etc) and gained understanding is being collected into databases containing prior knowledge (known cellular pathways, ontologies, etc). The learned insights have practical use in a wide spectrum of fields, from enhancing health in humans to optimizing production properties in bioprocesses.
The bottleneck in the process is understanding of the data, for which data analysis and modeling is needed. This gives (computational) modelers plenty of exciting new challenges.
This course teaches two necessary aspects needed in modeling: (i) details of state of the art models and data analysis methods, and (ii) some insights about the research processes required for designing, implementing and testing the models and methods. The first aspect, the merits and weaknesses of the models and algorithms, can only be thoroughly understood by implementing them and experimenting with them. The second aspect would be boring without the connection to practical details. For these reasons, this course is a small-scale (applied) research project.
Our initial plan is to emphasize models for systems biology, but ultimately the focus will be determined by the interests of the participants. Possible topic areas include inference of gene regulatory, metabolic or other networks from expression data, component and clustering models for data analysis, and Hidden Markov Models for biological sequences. The list is not comprehensive.
The course participants have a unique chance of working with a new state-of-the art software platform developed by a Finnish company Medicel. Alternatively, other solutions such as the public domain Bioconductor can be used.
This course is intended mainly for graduate students of computer science, statistics, and applied mathematics, but students from other fields are welcome as well. In particular mathematically oriented biology, bioinformatics, and medical students are welcome.
Basic programming skills in some language are required (programming is not taught in the course), as well as basic knowledge of bioinformatics or computational biology. For instance "S-114.2510 Computational Systems Biology" or some other basic course on bioinformatics is sufficient. Additionally, probability, statistics, vector algebra, calculus, and/or combinatorics are required, depending on the chosen project.
|HUT students:||In Webtopi|
|Other universities:||Send email to the organizers or sign up at the introduction lecture.|
For more information, please send email to firstname.lastname@example.org.
Sami Kaski, Christophe Roos, Merja Oja
You are at: CIS → T-61.6070 Special course in bioinformatics I: Computational modeling methods in bioinformatics
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