Mass Spectrometry Informatics in Systems Biology

Mass spectrometry (MS) became a standard tool for identifying metabolites in biological tissues, and metabolomics is slowly acknowledged as a legitimate research discipline for characterizing biological conditions. The computational analyses of metabolomics, however, lag behind compared with the rapid advances in analytical aspects for two reasons. First is the lack of standardized data repository for mass spectra: each research institution is flooded with gigabytes of mass-spectral data from its own analytical groups and cannot host a world-class repository for mass spectra. The second reason is the lack of informatics experts that are fully experienced with spectral analyses. The two barriers must be overcome to establish a publicly free data server for MS analysis in metabolomics as does GenBank in genomics and UniProt in proteomics. The workshop brought together bioinformaticians working on mass spectral analyses in Finland and Japan with the goal to establish a consortium to freely exchange and publicize mass spectra of metabolites measured on various platforms computational tools to analyze spectra spectral knowledge that are computationally predicted from standardized data. This book contains the abstracts of the presentations given in the workshop. The programme of the workshop consisted of oral presentations from Japan and Finland, invited lectures from Steffen Neumann (Leibniz Institute of Plant Biochemistry), Matej Oresic (VTT), Merja Penttila (VTT) and Nicola Zamboni (ETH Zurich) as well as free form discussion among the participants. The event was funded by Academy of Finland (grants 139203 and 118653), Japan Society for the Promotion of Science (JSPS Japan-Finland Bilateral Semi- nar Program 2010) and Department of Computer Science University of Helsinki. We would like to thank all the people contributing to the technical pro- gramme and the sponsors for making the workshop possible. Helsinki, October 2010 Masanori Arita, Markus Heinonen and Juho Rousu

Factors Driving Stock Option Grants - Empirical Evidence from Finland

This study contributes to the executive stock option literature by looking at factors driving the introduction of such a compensation form on a firm level. Using a discrete decision model I test the explanatory power of several agency theory based variables and find strong support for predictability of the form of executive compensation. Ownership concentration and liquidity are found to have a significant negative effect on the probability of stock option adoption. Furtermore, I find evidence of CEO ownership, institutional ownership, investment intensity, and historical market return having a significant and a positive relationship to the likelihood of adopting a executive stock option program.