Systems biology relies on empirically measured chemical properties and a functional infrastructure with a high reliability. Chemometrics is the science of extracting information from complex systems by data-driven means. The key to success in chemometrics multivariate modeling is high quality data management. A collection of data is however not information. Identifying features and patterns in the data leads to information, and only then has the potential to represent knowledge. It only becomes knowledge, however, when one is able to realize and understand the patterns and their implications.
Analytical quality and data management
• Data quality and data validity
• How to describe and communicate data and data quality control
• Handling of instruments to data-files
• Raw data transforming and communication
• ‘Omics data, sample selection, traceability and design of experiments (DOE)
Information from data
• Work-flow and Best practice
• Data mining and bioinformatics
• Student's t-test to Multivariate statistics and Bayesian probabilities
• Model interpretation, Visualization, network modeling and pathway mapping
• Quality control and Design of experiments.
Knowledge management
• Knowledge management and validation
• Knowledge hyphenation and inter disciplinary communication
• Opportunities from normal and revolutionary science
• Organizational and epistemological aspects on knowledge management
