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 brings together bioinformaticians working on mass spectral analyses in Finland and Japan and establishes a consortium to freely exchange and publicize
Since most spectral data are only commercially available, research collaboration to provide a free archive to the community is extremely important.
The MassBank project (http://massbank.jp/) of Japan is the internationally leading effort towards providing a publicly available center of mass spectral data and analysis. From Finland, investigators of Computational Systems Biology and Bioinformatics group (CSBB) provide computational tools to analyze mass spectra. Especially, the group can provide a computational approach for predicting fragmentation schemes, a functionality currently lacking from mass spectral databases.
The workshop also invites renowned researchers from fields related to metabolomics and promotes interdisciplinary collaboration through mass spectral resources.
The workshop is organized by Assoc. Prof. Masanori Arita, Prof. Juho Rousu and Markus Heinonen.
The workshop is open to any researchers interested in the topic, but the number of participants is limited. Participants are accepted on first come - first served principle.
The registration has closed.
Dr. Nicola Zamboni, Institute of Molecular Systems Biology, ETH, Switzerland
Dr. Steffen Neumann, Leibniz Institute of Plant Biochemistry, Germany
Research Prof. Matej Orešič, VTT Technical Research Centre of Finland
Research Prof. Merja Penttilä, VTT Technical Research Centre of Finland
Prof. Takaaki Nishioka, Institute for Advanced Biosciences, Keio University, Japan
Assoc. Prof. Masanori Arita, University of Tokyo and RIKEN Plant Science Center, Japan
Assoc. Prof. Kensuke Nakamura, Nara Institute of Science and Technology, Japan
Ass. Prof. Masahiro Sugimoto, Institute for Advanced Biosciences, Keio University, Japan
Assoc. Prof. Ken Tanaka, Institute of Natural Medicine, University of Toyama, Japan
Prof. Juho Rousu, University of Helsinki, Finland
Markus Heinonen, University of Helsinki, Finland
Workshop is to be organized in 28th - 29th October, 2010, in lecture room D122 in Exactum building at Kumpula Campus of University of Helsinki. Kumpula Campus is approximately 5 kilometers north from the main railway station and 20 minutes by public transportation.
Use the excellent Journey Planner to find your way with the city transport.
From city center to Kumpula one can take either Tram 6 to Arabia (and leave off at kumpula on the stop kyläsaarenkatu). The trams go every 10 minutes or so throughout the day. The buses 700-742 also go to kumpula frequently, leaving from eastern side of the main railway station. The tickets can be bought from the bus/tram driver (coins and small bills preferred) for 2.50 euros. Day tickets can be bought from ticket machines, railway stations and from the quite ubiquitous "R-kiosks".
Computational Systems Biology and Bioinformatics group, Department of Computer Science, University of Helsinki (leader Prof. Juho Rousu). Part of National Centre of Excellence 'Algorithmic Data Analysis', the group develops computational tools, models and methods for molecular, cell, and systems biology. The group combines expertise on optimization algorithms and machine learning to solve these problems. The focus for method development is given by the three intertwined biological research fields where the group operates: Metabolic modelling (which are the metabolic pathways of given organism and how do they operate), functional genomics (what is the purpose of a given gene in an organism), and drug and biomarker discovery (finding new molecules and diagnostics methods that have medical value). The group has a lond-standing experience in developing computational tools for analyzing mass spectrometry data arising in systems biology applications. The group has developed tools for de-convoluting tandem- MS spectra arising from 13C labeling experiments, novel 13C flux analysis methods relying on such data, as well as techniques for identification of daughter ions of metabolites. Other tools include atom-level metabolic pathway inference algorithms and methods for predicting atom-atom mappings in biochemical reactions.
MassBank group (leader Prof. Takaaki Nishioka, co-leaders Assoc Prof. Masanori Arita and Prof. Shigehiko Kanaya). Massbank is an academic consortium supported by Japan Science and Technology Corporation (JST) for 2006-2010 to establish a freely available mass spectral database for metabolomics. The three investigators manages the development of spectral, chemical, and species-metabolite relational data contents, respectively, and provides over 20,000 spectra on more than 3,000 metabolites at MassBank. Based on this database development, each investigator explores interdisciplinary research using the accumulated information. Prof. Takaaki Nishioka, analytical chemist, analyzes fragmentation schemes of biological molecules under electrospray ionization. Assoc. Prof. Masanori Arita, bioinformatician, developed an atom-resolved metabolic pathway analysis using a wiki-based system at http://metabolomics.jp. Lastly, Prof. Shigehiko Kanaya develops the analysis pipelines to deconvolute (peak- detect) GC and FTICR/MS raw data, and has developed the KNApSAcK database for analysing metabolite-species relationships, containing information on over 100,000 metabolite-species pairs.
