Data acquisition, analysis and modelling

• Process Analytical Technologies (PAT): PAT technologies are used to track and control manufacturing bioprocesses in real-time, thereby improving the quality and efficiency of bioprocesses. They may include spectroscopic analysis techniques, in-line sensors, and automated control systems.
• Data mining with customized algorithms: data mining involves the use of algorithms to discover patterns and relationships in large data sets. Customized algorithms can be developed to answer specific questions or to handle specific data types and big data.
• Development of (bio)analytical tests and analyses; complex sample preparation; derivatization strategies: these activities involve the development of new methods for testing and analyzing samples, including complex biological samples. This may include sample preparation, data analysis, and derivatization, which is the process of chemically modifying a substance to improve its analytical properties.
• Bioinformatics: bioinformatics is the application of computer science to biology, and is often used to analyze large biological data sets. This can include the analysis of genomic sequences, the modeling of protein structures, and the analysis of gene expression data.

These activities all focus on the use of data to understand and improve biological and biotechnological processes. They require a combination of expertise in biology, chemistry, computer science and statistics. All of the activities mentioned above are carried out in the BioSusChem research group by the following professors: