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The range of CIRAD's research has given rise to numerous datasets and databases associating various types of data: primary (collected), secondary (analysed, aggregated, used for scientific articles, etc), qualitative and quantitative. These "collections" of research data are used for comparisons, to study processes and analyse change. They include: genetics and genomics data, data generated by trials and measurements (using laboratory instruments), data generated by modelling (interpolations, predictive models), long-term observation data (remote sensing, observatories, etc), data from surveys, cohorts, interviews with players.
The Infectious Diseases Data Observatory (IDDO) assembles clinical, laboratory and epidemiological data on a collaborative platform to be shared with the research and humanitarian communities. The data are analysed to generate reliable evidence and innovative resources that enable research-driven responses to the major challenges of emerging and neglected infections. Access is available to individual patient data held for malaria and Ebola virus disease. Resources for visceral leishmaniasis, schistosomiasis and soil transmitted helminths, Chagas disease and COVID-19 are under development. IDDO contains the following repositories : COVID-19 Data Platform, Chagas Data Platform, Schistosomiasis & Soil Transmitted Helminths Data Platform, Visceral Leishmaniasis Data Platform, Ebola Data Platform, WorldWide Antimalarial Resistance Network (WWARN)
OpenWorm aims to build the first comprehensive computational model of the Caenorhabditis elegans (C. elegans), a microscopic roundworm. With only a thousand cells, it solves basic problems such as feeding, mate-finding and predator avoidance. Despite being extremely well studied in biology, this organism still eludes a deep, principled understanding of its biology. We are using a bottom-up approach, aimed at observing the worm behaviour emerge from a simulation of data derived from scientific experiments carried out over the past decade. To do so we are incorporating the data available in the scientific community into software models. We are engineering Geppetto and Sibernetic, open-source simulation platforms, to be able to run these different models in concert. We are also forging new collaborations with universities and research institutes to collect data that fill in the gaps All the code we produce in the OpenWorm project is Open Source and available on GitHub.
The NDEx Project provides an open-source framework where scientists and organizations can share, store, manipulate, and publish biological network knowledge. The NDEx Project maintains a free, public website; alternatively, users can also decide to run their own copies of the NDEx Server software in cases where the stored networks must be kept in a highly secure environment (such as for HIPAA compliance) or where high application load is incompatible with a shared public resource.