Our confirmed speakers:

• Tim Beissbarth
  University Medical Center Göttingen (UMG), Germany
  Methods to analyse transcriptome data in view of gene regulation and signaling pathways


• Philipp Bucher
  Swiss Institute for Experimental Cancer Research (ISREC), Lausanne, Switzerland
  Biophysical modeling of transcription factor binding specificity using large SELEX libraries and computational simulations


• Julio Collado Vides
  Center for Genomic Sciences, Universidad Nacional Autónoma de México (UNAM), Cuernavaca, Mexico
  RegulonDB: Accelerating access to genomic knowledge in Escherichia coli K-12
  (remote talk)


• Ivo Grosse
  Martin-Luther-Universität Halle-Wittenberg, Germany
  Phylotranscriptomic hourglass patterns and the emergence of biodiversity
  


• Reinhard Hehl
  Technical University Braunschweig, Germany
  Cross-kingdom transcriptional regulation in innate immunity


• Ralf Hofestädt
  University Bielefeld, Germany
  Gene regulation: Databases and Integration


• Dieter Jahn
  Technical University Braunschweig, Germany
  Gene regulatory networks in bacteria


• Alexander Kel
  genexplain GmbH, Wolfenbüttel, Germany
  TRANSFAC versus Cancer


• Fedor Kolpakov
  Institute of Systems Biology, Novosibirsk, Russia
  GTRD - a database on gene transcription regulation


• Vsevolod Makeev
  Vavilov Institute of General Genetics, Russian Academy of Sciences, Moscow, Russia
  From TRANSFAC to HOCOMOCO: using cross-validation and human curation to take most from the high throughput data compiling a complete collection of transcription factor binding motifs


• Alvaro Perdomo Sabogal
  Freie Universität Berlin, Berlin, Germany
  Soft selective sweeps on clusters of gene regulatory factors, a source of population-specific regulatory diversity in human


• Ekaterina Shelest
  German Centre for Integrative Biodiversity Research (iDiv), Leipzig, Germany
  Promoter-based prediction of gene clusters in eukaryotic genomes


• Johannes Soeding
  Max Planck Institute for Biophysical Chemistry, Göttingen, Germany
  Bayesian Markov models consistently improve accuracy of DNA binding site predictions by learning inter-nucleotide dependencies


• Takako Takai
  Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan
  Tohoku Medical Megabank Project: a project for personalized preventive medicine based on a biobank and prospective genome cohort studie


• Martin Vingron
  Max Planck Institute for Molecular Genetics, Berlin, Germany
  Computational methods in epigenetic regulation


• Thomas Werner
  University of Michigan, Ann Arbor, MI, USA
  From transcription factor binding sites to metabolic phenotype: A tale of MORE gene regulation