Kowalski Prize 2017 for publication on modeling covariance
UvA bioinformatics Age Smilde and Huub Hoefsloot together with other colleagues have received the Kowalski Prize 2017 for a publication describing a new method for modeling covariance. The prize was awarded in the category for Best Application Paper. The study was published in 2015 in the Journal of Chemometrics. The publication describes a new mathematical method for modeling covariance structures from multiblock data sets in a way that simplifies the overall model and relationships among different blocks.
The selection committee was unanimous in its decision and noted that this paper represents an important work in the field of -omics with a significant likelihood that the described methode will become widely used. In reaching its decision, the selection committee noted that the paper describes a new, alternative method for modeling covariance structures from multiblock data sets in a way that simplifies the overall model and relationships among different blocks. The committee noted that paper is well written, and as such has the potential to find wide application in metabolomics and systems biology.
The Kowalski Prize
This yearly award, worth around €850 honours the many contributions of the former Editor-in-Chief and Founding Editor of the Journal, Bruce Kowalski. It alternates between the 'best theoretical paper' and 'best applied paper' published in the Journal of Chemometrics in the previous two years.
De publication was written together with Marieke Timmerman of Rijksuniversiteit Groningen, Edoardo Saccenti of Wageningen Universiteit and Jeroen Jansen Radboud Universiteit.
Age K. Smilde, Marieke E. Timmerman, Edoardo Saccenti, Jeroen J. Jansen and Huub C. J. Hoefsloot (2015) ‘Covariances Simultaneous Component Analysis: a new method within a framework for modeling covariances’ J. Chemom., volume 29, pages 277-288