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Laboratory of Computer and Information Science / Neural Networks Research Centre CIS Lab Helsinki University of Technology

Course Description [Back to course web page]

T-61.6070 Special course in bioinformatics I:
Computational modeling methods in bioinformatics V P, (7 cr)

Lecturers Prof. Sami Kaski, Laboratory of Computer and Information Science, Helsinki University of Technology
In Collaboration withDoc. Christophe Roos and Jukka Matilainen, Medicel Oy
Assistant M.Sc. Merja Oja, Department of Computer Science, University of Helsinki
Credits (ECTS) 7
Semester Spring 2006 (during periods III and IV)
Sessions On Thursdays at 14-16 in lecture hall T4 in computer science building,
Konemiehentie 2, Otaniemi, Espoo. The first session on 19.1.2006. Note: Demo of the modeling platform during the first session.
Language English
Web http://www.cis.hut.fi/Opinnot/T-61.6070/
Registration TKK students: WebTopi, others: send mail to t616070@cis.hut.fi
E-mail t616070@cis.hut.fi

Introduction

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.

Prerequisites [back to top]

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.

Course format

The course consists of the following parts. Group work is encouraged but individual work is possible too.
  1. Brief seminar presentation of the details of one model/algorithm, and plans for implementing and testing it. Each group selects one state-of-the-art article with the help of the lecturers.
  2. Project work: Carry out the plan, supervised by a researcher of the field.
  3. Oral presentation of the results in a mini-conference.
  4. Brief written report and documentation of the codes.

Signing up for the course

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 t616070@cis.hut.fi.

Welcome,
Sami Kaski, Christophe Roos, Merja Oja

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