Johannes Fütterer: Catalogue data in Autumn Semester 2016
|Name||Dr. Johannes Fütterer|
|Department||Environmental Systems Science|
|551-0193-00L||Biological Information Mining |
Number of participants limited to 8.
|6 credits||7G||K. Bärenfaller, J. Fütterer|
|Abstract||Students will use lists of genes obtained in real experiments and learn how to obtain gene-centered information from literature and databases. They will use tools for gene function prediction and visualization of protein-protein interaction networks. The work will lead to a more meaningful annotation of co-detected genes and generate a hypothesis about their functional relationship.|
|Objective||Ability to use modern databases, mining- and modelling tools for functional annotation of genes and gene networks. Gene centered view of plant processes.|
|Content||Many new biological analysis methods result in lists of genes or proteins related to biological structures, functions, or processes. The information available about the genes or proteins is often scattered in multiple databases and publications, making it difficult to extract and uncover common features or relationships among the biological molecules. |
In the course students will use lists of genes or proteins from ongoing experiments in the laboratory and learn how to find and assemble gene-centered information in the literature, different databases and with analysis tools. The training and research will lead to a better and more meaningful annotation of co-detected genes members and generate a hypothesis about their functional relationship.
The work will be done exclusively using a computer. Students will work independently but with close supervision by experienced scientists. Daily discussions of the work will ensure progress. The computer work will be accompanied by lectures on theoretical and practical aspects of databases, gene networks and the project context of the gene lists that will be analyzed. Students will present their results and hypotheses at the end of the block course.
|551-1295-00L||Introduction to Bioinformatics: Concepts and Applications||6 credits||4G||W. Gruissem, K. Bärenfaller, A. Caflisch, G. Capitani, J. Fütterer, M. Robinson, A. Wagner|
|Abstract||Storage, handling and analysis of large datasets have become essential in biological research. The course will introduce students to a number of applications of bioinformatics in biology. Freely accessible software tools and databases will be explained and explored in theory and praxis.|
|Objective||Introduction to Bioinformatics I: Concepts and Applications (formerly Bioinformatics I) will provide students with the theoretical background of approaches to store and retrieve information from large databases. Concepts will be developed how DNA sequence information can be used to understand phylogentic relationships, how RNA sequence relates to structure, and how protein sequence information can be used for genome annotation and to predict protein folding and structure. Students will be introduced to quantitative methods for measuring gene expression and how this information can be used to model gene networks. Methods will be discussed to construct protein interaction maps and how this information can be used to simulate dynamic molecular networks.|
In addition to the theoretical background, the students will develop hands-on experiences with the bioinformatics methods through guided exercises. The course provides students from different backgrounds with basic training in bioinformatics approaches that have impact on biological, chemical and physics experimentation. Bioinformatics approaches draw significant expertise from mathematics, statistics and computational science.
Although "Intoduction to Bioinformatics I" will focus on theory and praxis of bioinformatics approaches, the course provides an important foundation for the course "Introduction to Bioinformatics II: Fundamentals of computer science, modeling and algorithms" that will be offered in the following semester.
|Content||Bioinformatics I will cover the following topics:|
From genes to databases and information
Prediction of gene function and regulation
RNA structure prediction
Gene expression analysis using microarrays
Protein sequence and structure databases
WWW for bioinformatics
Protein sequence comparisons
Proteomics and de novo protein sequencing
Protein structure prediction
Cellular and protein interaction networks
Molecular dynamics simulation