The Advanced Course on Genomics in Industrial Biotechnology aims at familiarizing industrial and academic research professionals with modern concepts in genomics, their use in microbial research and development, and their utility in contemporary biotechnological industry.
Date: October 31 – November 4, 2016
Target audience: This Advanced Course is aimed both at participants from industry, who want to update and extend their theoretical knowledge and practical insight in this field and at participants from universities and research institutions with a wish to evaluate practical implications of their research.
It is intended for postgraduates (MSc, PhD level, or equivalent experience), with a sound background in microbiology, microbial physiology, molecular cell biology, biochemistry or biochemical engineering, and a basic working knowledge in some of the other disciplines. Having some basic insight into one or more of the genomics technologies or in bioinformatics is not compulsory, but certainly is an advantage.
Program: This course focuses on the singular and combined utilization of the modern molecular research tools genome sequencing, transcriptomics, proteomics, and metabolomics to elucidate cellular regulatory mechanisms of sensing and signalling, metabolic flux and physiology. Mathematical tools and computer algorithms are indispensable to analyze, interpret and model this experimental data. In combined approaches, these tools offer unprecedented possibilities for industrial biotechnology research.
Experts will present lectures on genome analysis and -interpretation, genome-wide mRNA expression analysis (transcriptomics), whole-organism protein expression and activity analysis (proteomics), and metabolic pathway analysis (metabolomics). Data handling and bioinformatics are key to the successful application of genomics and hence, will be an integral part of the course. The necessary links between theory and practice will be provided in interactive case studies and demo-workshops. Implementation of these technologies in industrial R&D will be illustrated with real-life examples.