VISUBIOMED: Data integration and visualisation of highly complex biological and medical data (VTT Service Beyond Theme)
The objective of the
project is to develop a visualization tool utilizing state-of-the-art 3D
techniques, modern mathematical modelling techniques, contextualization
etc. for diagnostics, drug target discovery, drug development and
education by linking information from macro- to nano- scales.
The project combines expertise of two VTT teams: Quantitative Biology and Bioinformatics (QBIX) and the Signal and Image Processing team.
As part of the project we have developed the megNet software for life science data integration and visualization. megNet enables integrative mining across the ontologies, pathways, and available experimental repositories (e.g. gene expression, metabolomics, ..).
Related projects: TRANSCENDO, ATLAS, SYSDIPP
Latest news and relevant publications
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J. R. Koikkalainen, M. Antila, J. M. P. Lötjönen, T. Heliö, K. Lauerma, S. M. Kivistö, P. Sipola, M. A. Kaartinen, S. T. J. Kärkkäinen, E. Reissell, J. Kuusisto, M. Laakso, M. Orešič, M. S. Nieminen, K. J. Peuhkurinen, Early familial dilated cardiomyopathy: identification with determination of dsease state parameter from cine MR image data, Radiology 249, 88-96 (2008).
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P. V. Gopalacharyulu, E. Lindfors, J. Miettinen, C. K. Bounsaythip, M. Orešič, An integrative approach for biological data mining and visualization, Int. J. Data Mining and Bioinformatics 2, 54-77 (2008).
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M. Orešič, J. Lötjönen, C. Bounsaythip, megNet®: visualization and modeling environment for translational medicine, ERCIM News 69, 32-34 (2007).
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J. Koikkalainen, M. Nyman, J. Hirvonen, J. Lötjönen, J. Hietala and U. Ruotsalainen. Shape Variability of the Human Striatum – Effects of Age and Gender, NeuroImage, in press, 2006.
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J. Koikkalainen, J. Lötjönen, S. Kivistö, M. Antila and S. Toiviainen-Salo. Estimation of Disease State Using Statistical Information from Medical Imaging Data. MICCAI 2006 Workshop: From statistical Atlases to Personalized Models: Understanding Complex Diseases in Populations and Individuals, in press , 2006 .
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P. V. Gopalacharyulu, E. Lindfors, C. Bounsaythip, and M. Orešič, Context dependent visualization of protein function, Proceedings of Probabilistic Modelling and Machine Learning in Structural and Systems Biology Workshop (Rousu, J., Kaski, S., and Ukkonen, E. eds.), Tuusula, Finland, June 17-18, 2006, pp. 26-31.
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M. Orešič, A. Vidal-Puig, and V. Hänninen, Metabolomic approaches to phenotype characterization and applications to complex diseases, Expert Rev. Mol. Diagn. 6, 575-585 (2006).
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P.V. Gopalacharyulu, E. Lindfors, C. Bounsaythip, T. Kivioja, L. Yetukuri, J. Hollmén, and M. Orešič, Data integration and visualization system for enabling conceptual biology, Bioinformatics 21, i177-i185 (2005).
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M. Orešič, P. V. Gopalacharyulu, E. Lindfors, C. Bounsaythip, I. Karanta, M. Hiirsalmi, L. Seitsonen and P. Silvonen, Towards an integrative and context sensitive approach to in silico disease modelling, ERCIM News 60, 25-26 (2005).
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J. Lötjönen, S. Kivistö, J. Koikkalainen, D. Smutek, K. Lauerma. Statistical shape model of atria, ventricles and epicardium from short- and long-axis MR images, Medical Image Analysis, vol. 8, no 3, pp. 371-386, 2004.