Machine Learning, Bioinformatics and Geospatial Technologies
We develop predictive models on complex spatio-temporal patterns, integrating the different molecular biology levels, spatially explicit population models and landscape environmental analysis. We aim to create novel mathematical methods and ICT platforms connecting physiopathological patterns of disease with high dimensional data now available for Functional Genomics (e.g DNA microarrays, SNPs, proteomics), with spatially epidemics simulation systems and geodatabases of environmental factors and socio-demographic data.
Our research is interdisciplinary. Since 1996, we have been working on biological and environmental data, porting novel Statistical Machine Learning Methods (classifiers and regression models) within Geographical Information Systems (GIS), with results in landscape epidemiology and environmental risk analysis. More recently, we started developing Individual Based Model (IBM) simulators of global pandemic scenarios (FLUMODCONT, EPIWORK). Since 2002, we also develop predictive machine learning methods for functional genomics: we design algorithms for predictive classification and profiling of high-throughput data, with implementation on standard workstations, computer clusters and in grid.
For our projects, we develop new software infrastructures (such as MITRIS) for data collection, management and analysis, supporting research and public agencies. We have created innovation in GIS (GRASS) and internet GIS (WebGIS) systems, and the spinoff company MPA Solutions in 2004. For high-throughput genomics data, we develop the Python/C machine learning package MLPY, several bioinformatics solutions, and we work for the integration of different genomics and patient data.
Finally, we actively promote the dissemination of interdisciplinary science with the WebValley Summer School Project (on multisensorial pattern identification in 2009!), and by acting as a training lab for undergraduate and graduate students. We are proud to support projects of social interest that require visualizing and understanding data patterns such as the Intersos WebGIS for Humanitarian Response for Darfur and Tchad and the OECD Global Project on "Measuring the Process of Societies".
NEW!! Opportunities for jobs, internships, theses, see page on this site.
NEW!! Wednesday 10th February, joint FBK & Cosbi "Informal Network Day" Workshop
NEW! Paper and Editorial on February 2009 issue of Nature Genetics!
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Repeatability of published microarray gene expression analysesJohn P A Ioannidis1,2,3, David B Allison4, Catherine A Ball5, Issa Coulibaly4, Xiangqin Cui4, AedÃn C Culhane6,7, Mario Falchi8,9, Cesare Furlanello10, Laurence Game11, Giuseppe Jurman10, Jon Mangion11, Tapan Mehta4, Michael Nitzberg5, Grier P Page4,12, Enrico Petretto11,13 & Vera van Noort14 Editorial Mostly, your results matter to others -High-throughput datasets and analysis protocols are intrinsically difficult to referee. Community standards enforced by journals may be less effective than is widely appreciated. Greater awareness of the needs and value of secondary data users can result in higher-impact papers. |
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Age-prioritized use of antivirals during an influenza pandemicBMC Infectious Diseases 2009, 9:117 Stefano Merler, Marco Ajelli, Caterina Rizzo Editorial Treatment with antivirals in the current H1N1 influenza outbreak should be prioritized by age once the age-specific case fatality rates are determined; people under 65 may need to take precedence to reduce mortality where stockpiles are limited. |
Le Nuove Frontiere della Biologia
Riva del Garda - Cortile della Rocca
Mercoledi' 3 Settembre 2008, ore 20:45
© 2008 Fondazione Bruno Kessler