If you are a biologist, chemist or engineer you may call it chemometrics, if you are a statistician you may call it multivariate data analysis, if you are a data scientist you may call it machine learning. These names all describe the same field, which aim is to generate knowledge and understanding of chemical or biological systems with application of statistical and mathematical approaches. Methods like principal components analysis, partial least squares, multiple linear regression, random forests and design of experiments have been workhorses in this area. Other methods such as support vector machines, self-organizing maps and artificial neural networks including recent developments in deep neural networks, may be new in the field, but at the same time they are natural extensions of approaches used so far in the chemometrics field.
Chemometrics methods can be applied in any area where analysis of complex chemical/biological data is needed, for example in materials science, process control, structure activity and structure property relationship studies, analytical method development, ‘omics’ analysis, etc. Chemometrics supports building of knowledge and understanding in chemistry, biology, medicine, physics, technology, and other science areas.
The Chemometrics division of The Swedish Chemical Society is a national organization established in 1992 with the aim to engage with people active in chemometrics, both from the point of view of methodology and applications. Another task of the division is to serve as an international contact with similar organizations active in chemometrics located outside Sweden.
Board members of the Chemometrics Division, Swedish Chemical Society:
Johan Trygg, Professor, Umeå University, Sweden
Sanela Kjellqvist, PhD, Karolinska Institutet, Sweden
Mats Josefson, PhD, AstraZeneca, Sweden
Mikael Karlsson, Vice President, Bestwood AB, Sweden
Anders Nilsson, PhD, Bruker Nordic AB, Sweden
Gunilla Wormbs, Director R&D, Essity Health and Hygiene AB, Sweden