10th Course in Bioinformatics and Systems Biology for Molecular Biologists

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1 10th Course in Bioinformatics and Systems Biology for Molecular Biologists March 14th-17th, 2010 Schloß Hohenkammer, Germany Invitation to participate in the 10 th Bioinformatics Spring School The 10th edition of the Spring School of Bioinformatics for Molecular Biologists will be held from 14th through 17th of March It is organized by the Institute of Bioinformatics and Systems Biology of the Helmholtz Centre München (IBIS). The course is part of the HMGU Ph.D. programme (Graduate School) but open to other Ph.D. students and post-graduates. It is also part of the Helmholtz Alliance in Systems Biology. In this year s Spring School, we want to introduce the basics in tutorials but also to discuss new developments in the interdisciplinary fields of Bioinformatics and Systems Biology. The concept of the course is tailored for Molecular Biologists and aims to support the important dialogue between the experimentalist interested in a specific biological problem and the theoretician eager to solve problems in a generic, reusable way. The alliance between the generation of biological data and methods of interpretation and modelling of biological systems will be pivotal for the future. The Course aims to allow for a head start by presenting basic concepts as well as recent applications. The intended audience is Ph.D. students and junior scientists. Its main subjects will be the integration of information, biological networks, and concepts in Systems Biology. Schloß Hohenkammer is a first-class seminar centre located off the beaten track, but still only a 30 min car ride away from Munich. Its location is exquisite and the castle is surrounded by fields which provide the estate with organic food.

2 Sustainability is the motto for the entire Hohenkammer estate, for example its raw materials from surrounding forest and fields supply the complex with enough fuel, making it independent of external energy supplies. This place is worth a visit! Please register early since the number of available places is limited! Please distribute this invitation to all interested Ph.D. students and young scientists. For reservations please contact the IBIS Office (ibis.office@helmholtzmuenchen.de). Sincerely yours, H. Werner Mewes Prerequisites for participation: Participants should have some basic knowledge in bioinformatics including sequence analysis, basic knowledge of gene and structure prediction methods, and be familiar with molecular databases (e.g. EMBL, SwissProt, KEGG). Fee and registration: Ca. 600 (including tuition, course material, room and board for the whole duration of the event, but NOT travel expenses; to be paid directly at Schloss Hohenkammer) Registration: at Helmholtz-Institute for Bioinformatics and Systems Biology (ibis.office@helmholtzmuenchen.de). DIRECTOR: H.W. Mewes (Helmholtz Zentrum München and TU München, GERMANY) How to get there:

3 Faculty members of the 10th Course on Bioinformatics and Systems Biology Hohenkammer 2010 Prof. Dr. H.Werner Mewes (Course Director) Professor for Bioinformatics at the Technische Universität München, Weihenstephan and Director of the Inst. f. Bioinformatics and Systems Biology at the Helmholtz-Zentrum München. Founder of the MIPS-Group and Co-Founder of Biomax Informatics AG. Main interests: genome analysis, systems biology of multifactorial diseases, qualitative models and knowledge representation. Topics: Systems Biology of Diseases: Diseases are aberrations from the healthy homeostasis. The classification of pathophenotypes and the subsequent treatment has been the classical approach of medical treatment. Only recently rationale insight into disease aitioloy based on genetic and functional molecular information became feasible. I will discuss how Systems Biology might help to translate knowledge into health care.

4 Prof. Dmitrij Frishman, TU München Dmitrij Frishman received a M.S. in Biomedical Electronics from the Saint Petersburg Electrotechnical University in 1984 and a Ph.D. in Biochemistry from the Russian Academy of Sciences in An Alexander von Humboldt Research Fellowship he received at the end of 1991 allowed him to join the Pat Argos group at the Biocomputing Department of EMBL in Heidelberg, where he pursued postdoctoral training in structural bioinformatics until He subsequently joined the Munich Information Center for Protein Sequences as a senior scientist and later became Deputy Director of the Institute for Bioinformatics at the German Research Center for Health and Environment. Since 2003, Dmitrij Frishman has been Professor for Bioinformatics at the Technical University of Munich. His current research interests focus on genome annotation, prediction and analysis of protein interactions, and structural genomics Topic: Protein-protein interactions represent the natural context in which proteins execute their cellular function. Using advanced molecular biological techniques it has become possible to experimentally determine interaction partners for large subsets of gene products encoded in a given genome. I my talk I will explain how protein interaction networks can be reconstructed analyzed, and used for global function prediction and understanding of system-level cellular organization in model organisms. I will also provide an overview of modern methods to predict protein interactions from sequence data.

5 Prof. Lars Juhl Jensen is Honorary professor at the Novo Nordisk Foundation Center for Protein Research, University of Copenhagen. He received a Ph.D. from the Technical University of Denmark in 2002 for his thesis on "Prediction of Protein Function from Sequence Derived Protein Features". He worked in Peer Bork's group at the EMBL from 2003 to He is author of 65 publications. Topic: Integration of heterogeneous data High-throughput technologies technologies such as DNA sequencing, microarrays, mass spectrometry, and protein interaction assays have resulted in an ever increasing flood of data. To make the most of such data sets, it is important to integrate them both with each other and with the existing scientific literature. In my presentation, I will explain how heterogeneous data types are integrated in STRING to construct a network of functional associations. I will also briefly introduce the resources STITCH, NetworKIN, and Reflect that build upon STRING to predict phosphorylationdependent signaling, to construct a protein-chemical network, and to perform real-time tagging of web pages, respectively.

6 Dr. Robert Küffner, Ludwig-Maximilians-Universität München Topic: Expression Analysis: Platforms, biological questions and analysis techniques Since the introduction of microarrays in the late 1990s they consistently gained wider interest by allowing scientists to answer new biological questions and spurred the development of new analysis approaches. Microarrays enable to simultaneously capture the activity of thousands of genes. Standard experimental setups aim to compare cellular responses to multiple factors (e.g,. cell type, disease, nutrients) and their intrinsic differences. This course starts by introducing some of the major biological questions that researchers try to address when planning microarray experiments. To target the different questions, a range of different microarray platforms have been developed with characteristic advantages or special target areas such as the detection of alternative spliced genes or expressed non-coding RNAs. Then some of the basic first steps in gene expression analysis including data preprocessing and various routine analyses are presented. These include data normalization to render different measurements comparable, clustering to detect patterns of coexpressed genes, sample classification to identify diagnostic features or predict clinical outcomes and the determination of differentially expressed genes that enable the best differentiation between the different states. Some advanced topics will also be discussed, for instance the utilization of prior knowledge in the form of gene ontologies for the analysis of micrarray measurements.

7 Prof. Dr. Thomas Rattei Professor for Computational Biology and head of the Department of Computational Systems Biology at the University of Vienna. Main interest: microbial genomics and systems biology, genomics of pathogens, metagenomics, large scale sequence analysis. Topics: Concepts in Bioinformatics, Sequence and Genome Analysis: Nucleotide and protein sequences establish the foundation of modern molecular biology and bioinformatics. I will introduce basic concepts in the analysis of biological sequences, covering the wide range from the analysis of single gene sequences up to comparative genomics using more than completely sequenced chromosomes. Bioinformatics Databases and Resources: Bioinformatics databases are more than simple storage containers for nucleotide and protein sequences. Primary databases store basic sequence data in a structured way and allow easy retrieving of datasets of interest. Secondary databases process these sequence data to further annotate it. Both types of databases can be accessed through powerful bioinformatics web portals. I will introduce the basic principles of primary and secondary databases. I will especially focus on the quality of the contained data and annotation and methods to assess it.

8 Dr. Matthias Scherf Head of Discovery at Genomatix Software GmbH Munich. Main interest: gene regulation, comparative genomics, pattern recognition, next generation sequencing. Topic: Gene regulation Gene regulation is the basic principle ruling any subsequent metabolic pathways, signaling cascades and their interweaving into biological networks of a living cell. I will present an overview about how bioinformatics methods can support the process of understanding gene regulation at the molecular level. Prof. Dr. K. Suhre Professor for Bioinformatics at the Ludwig Maximilians University, Munich, and Group Leader Metabolomics at the Institute for Bioinformatics and Systems Biology, Helmholtz Zentrum München. Present main interest: metabolomics and genetics. Topic: Metabolomics vs. Genetics Metabolomics is the systems level approach to the quest of understanding all relevant metabolic processes of an organism, with an emphasis on quantifying the largest possible set of all endogenous organic compounds in a biological sample. In contrast to genomics, transcriptomics, and proteomics, metabolomics ideally provides access the true endpoints of biological processes. In a non-targeted metabolomics approach, the largest possible number of metabolites will be recorded, without a prior knowledge about their biochemical identify. In contrast, in a targeted metabolomics approach, only previously identified metabolites will be analyzed. Using appropriate internal standards, metabolite concentrations can then be quantified. At the Helmholtz Center Munich, both metabolomics approaches are implemented. I will give an overview of the related technologies with a special emphasis on the relevant bioinformatics and data analysis methods, and present selected examples from our research on the role of genetic variation in human metabolism. The objective of this tutorial is to introduce the participants to the potential of metabolomics research and to assist them in finding out how this technology may be useful for their individual research projects.

9 Prof. Dr. Dr. Fabian Theis, Helmholtz Zentrum München Group Leader "Computational Modeling in Biology" at the Inst. f. Bioinformatics and Systems Biology at the Helmholtz-Zentrum München and Professor at Math Department, TU Munich. Main interest: data-based modeling in systems biology. Topic: Learning systems biology models from data When estimating models from data, an interesting interplay between statistics and machine learning methods is often key to successful model derivation. Here, I will show some examples of model estimation from signaling models based on differential equations over discrete models to stochastic modeling. Biological applications are from stem cell differentiation and neural development. Dr. Gunnar Rätsch Friedrich Miescher Laboratorium der Max Planck Gesellschaft, Tübingen Dr. Gunnar Rätsch received the Diplom in computer science from the University of Potsdam (Germany) in 1998, along with the Jacob Jacoby prize for the best student of the faculty of natural sciences. Three years later, he obtained a Ph.D. in natural sciences with his work on Boosting at the Fraunhofer Institute in Berlin for which he received the Michelson award from the University of Potsdam. Gunnar Rätsch has been a postdoctoral fellow in the Research School of Information Sciences and Engineering of the Australian National University in Canberra (Australia), at the Max Planck Institute for Biological Cybernetics in Tübingen (Germany) and at Fraunhofer FIRST in Berlin (Germany). Currently, he is leading a research group at the Friedrich Miescher Laboratory of the Max Planck Society in Tübingen, Germany. In 2007 he was awarded the Olympus prize from the German Association for Pattern Recognition. He is interested in Machine Learning methods such as Boosting and Support Vector Machines and their application in computational biology and drug discovery. Recently he has focussed on the analysis of transcriptome data, gene finding and the prediction of alternative splicing.

10 Topic: Next Generation Sequencing, Tiling Arrays and Predictive Sequence Analysis for Transcriptome Analysis The complement of RNA transcribed from the genome (the transcriptome) essentially determines cellular protein concentrations. The characterization of transcriptomes in different organisms under different conditions is an important step towards the understanding understanding of innumerable cellular processes that lead to the expression of a gene. I will describe recent advances in transcriptome analysis, including experimental techniques like next generation sequencing and tiling arrays, as well as novel statistical analysis techniques and their combination with methods for predictive sequence analysis. Benedikt Wachinger, PhD student at the Biological Information Systems Group (BIS) at the Institute for Bioinformatics and Systems Biology (IBIS) at the Helmholtz-Zentrum München. Main interest: Semantic technologies for text mining and knowledge management Topic: Mining biomedical literature. Due to the growing amount of literature, the need for knowledge extraction has been increasing over the last years. Text mining is the first choice for automatically inferring relevant information from published articles. In this talk I will give an introduction to text mining using semantic technologies, discuss different existing approaches as well as future directions. Dominik Wittmann, Helmholtz Zentrum München PhD student in the "Computational Modeling in Biology" group at the Inst. f. Bioinformatics and Systems Biology at the Helmholtz-Zentrum München. Main interest: quantification of discrete models and parameter fitting in dynamical systems. Topic: Quantitative models and simulation In Systems Biology experimentalists and theoreticians make a concerted effort to unravel the functionality of complex biological systems: Experimental knowledge allows the creation and refinement of mathematical models, which, in turn, help to design and optimize further experiments. In this talk I will present different kinds of quantitative models and explain how they can be simulated in-silico. Also, I will discuss several analysis techniques for these models.

11 Dr. Volker Stümpflen, Helmholtz Zentrum München Group Leader Biological Information Systems at the Institute for Bioinformatics and Systems Biology (IBIS) at the Helmholtz-Zentrum München. Main interests: systems biology of multifactorial diseases, knowledge management and representation of distributed information with semantic technologies. Topic: micrornas Small molecules with a large impact. Almost 15 years ago it slowly turned out that some single-stranded small RNA molecules of approximately nucleotides in length also called micrornas are playing an important role not only in the regulation of some genes but in many different cellular processes in general. Several aspects of micrornas including origin, (prediction) of regulation and their general impact will be discussed within the lecture. Prof. Dr. Ralf Zimmer Professor for Computer Science and Bioinformatics at the Ludwig-Maximilians-Universität München. Chairman of the DFG Bioinformatics Center Munich (BIM) and LMU-spokesperson of the International Research Training Group RECESS Regulation and Evolution of Cellular Systems (cooperation between Munich and Moscow funded by DFG). Main interests: Network Analysis, Biological Networks and Pathways,Text Mining, Expression Analysis, Gene Regulation, Alternative Splicing, Protein Sequence and Structure analysis, Systems Biology, Petri Nets. Topic: Graphs, Networks, and Systems for Bioinformatics and Systems Biology Most methods in bioinformatics rely and exploit network information for the analysis of large scale data sets e.g. genome-wide gene expression measurements, and for systems biology modelling. This talk introduces graph and network concepts (e.g. Petri Nets, Random and complex graphs) and discusses the underlying techniques of recent methods for inferring and representing biological

12 knowledge using these networks. The talk discusses methods for generating appropriate networks from databases and literature, for analysing and visualizing these networks, for extracting pathway information from large networks, and for constructing network systems from pathways for (semi-) quantitative systems biology simulations. The main goal of the talk would be to demonstrate the application of networks and network analysis for representing and validating biological hypotheses about (large-scale) experimental data. Examples are identifying regulation contexts and disease hypotheses from a large data set of microarray experiments on arthritis (human patient, animal model and cell-line) samples.