Promoter hunting and systems modelling of cellular pathways

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   IMPORTANT DATES for this Course
   Deadline for applications: April 9th 2015
   Latest notification of acceptance: April 13th 2015
   Course date: April 22nd - April 24th 2015

Candidates with adequate profile will be accepted in the next 72 hours after the application until we reach 20 participants.


Alexander Kel is the Founder and Chief Scientific Officer (CSO) of geneXplain GmbH. He has been involved in research in practically all fields of bioinformatics, from molecular evolution, and structural biology to database development, application of machine learning techniques and sequence analysis. In the recent years his interests shifted considerably towards system biology including structural analysis of signal transduction and gene regulatory pathways and dynamic modelling of regulatory circuits of such complex cellular processes as cell cycle, differentiation and apoptosis. He participated in many Pathway Analysis, Gene and Promoter finding, Gene Regulatory Networks courses in GTPB as an instructor. He is a co-founder of PathProt together with Roman Zubarev and Pedro Fernandes.

Affiliation: geneXplain GmbH, Wolfenbuettel, DE

Christoph Wierling is heading the bioinformatics and modeling unit at Alacris Theranostics GmbH, a Berlin-based company working in the field of systems medicine. Christoph studied Biology at the University of Munster and obtained a PhD in biochemistry at the Free University of Berlin. His research interest focuses on modeling and simulation of biological systems and the development of systems biology software and data resources. Before moving to Alacris Theranostics, Christoph was heading the Systems Biology group of the department Vertebrate Genomics at the Max Planck Institute for Molecular Genetics in Berlin. Christoph participated in the PA09 and PA11 Pathway Analysis courses as well as PNaS13 course in GTPB as an instructor and several PathProt workshops as a speaker.

Affiliation: Alacris Theranostics GmbH, Berlin, DE


This course starts by reviewing basic principles of gene regulation and how information is encoded in the huge part of genome - it's so called "non-coding" part. Bioinformatics plays a huge role in exploring how gene regulation works. We will introduce mathematical modelling of cellular pathways and address the interplay between feedback and feed-forward loops of regulation. We will see how a range of modelling techniques can help us to:

- find master regulators
- understand disease mechanisms
- build models for use in precision medicine
- design novel systems for biotechnology

Starting from techniques for the computational prediction of promoters and distant enhancers, we will deal with the analysis of the structure of regulatory regions by identifying binding sites for transcription factors. A complete annotation of a newly sequenced genome has to address the identification of these regions in addition to the classical task of finding genes in terms of coding regions. Regulatory regions determine where, under which conditions and when genes become active. Thus, they are a fundamental part of the definition of the function of a gene. We will have a chance to introduce and acquire *hands-on* practice in next generation sequencing (NGS) techniques for genome-wide epigenetic analyses such as ChIP-seq.

Then we will approach the analysis and modelling of biological systems from several practical angles. Systems biology and modelling are approched here from the interaction and network-based perspectives. We will introduce several pathway databases, such as Reactome, KEGG, TRANSPATH, TRANSFAC, ConsensusPathDB and use these information resources to perform pathway analysis. Next, we will use modelling of biological systems to look at different mathematical modelling strategies, such as Boolean networks and ordinary differential equation systems (ODEs). We will describe computational tools, like Cytoscape and CellDesigner, for the set-up and development of model prototypes and show further tools, such as Copasi, BioUML and PyBioS that can be used for parameter-fitting and sensitivity analysis.

We will follow-on by looking at methods for reconstructing gene regulatory networks from gene expression data. The application of such methods can reveal key nodes in networks as potential biomarkers or drug targets. Dynamic systems modelling will be used to check the consistency of target and biomarker predictions. We will show real examples of application of these methods for identification of disease related biomarkers, drug discovery and personalized medicine.

Special attention will be given to the application of the above mentioned methods in designing novel biological systems, in the growing field of Synthetic Biology.


Participants will learn about several techniques of finding promoters and enhancers and the principles on which these methods are based on. In the hands-on exercises, several analytical tools will be introduced and the results critically evaluated to assess their reliability. The course sessions will consist of lectures that lay out the conceptual framework as needed, and hands-on exercises, which will provide the practical insight on the use of the methods, gradually, in order to produce skills that can be used with a relatively high degree of independence. Participants will learn how to set-up some of the programs, and use publicly available servers for more complex analytical jobs, in an informed fashion, so that they fully understand the output generated and how their quality can be assessed. Participants will also learn the novel principles of organization of gene regulatory regions, which will help them to interpret their results of genomic and transcriptomic studies.

The course will provide sufficient skills for the participants to address problems using open source software and freely accessible data resources. It will also be a chance to use commercially licensed resources such as TRANSFAC or the geneXplain integrated analytic platform for specific purposes.

Target Audience

The course was designed for researchers in biology, bioinformatics, biochemistry and medicine that have an interest in gene regulation and related topics.

Course Pre-requisites

Basic biochemistry. Elementary computing skills. Background knowledge in bioinformatics is not absolutely necessary, but may be instrumentally useful.

Detailed Program

Instituto Gulbenkian de Ciência,

Apartado 14, 2781-901 Oeiras, Portugal

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Last updated:  Mar 6th 2015