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Found 4 result(s)

Bioconductor

Open Source Software for Bioinformatics

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Bioconductor provides tools for the analysis and comprehension of high-throughput genomic data. Bioconductor uses the R statistical programming language, and is open source and open development. It has two releases each year, and an active user community. Bioconductor is also available as an AMI (Amazon Machine Image) and a series of Docker images.

Kaggle

Your home for data science

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Kaggle is a platform for predictive modelling and analytics competitions in which statisticians and data miners compete to produce the best models for predicting and describing the datasets uploaded by companies and users. This crowdsourcing approach relies on the fact that there are countless strategies that can be applied to any predictive modelling task and it is impossible to know beforehand which technique or analyst will be most effective.

OpenWorm

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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.

Community Surface Dynamics Modeling System

CSDMS

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CSDMS is a virtual home for a vibrant and growing community of about 1,000 international modeling experts and students who study the dynamic interactions of lithosphere, hydrosphere, cryosphere, and atmosphere at Earth’s surface. Participating in cross-disciplinary groups, members develop integrated software modules that predict the movement of water, sediment, and nutrients across landscapes and into the ocean. We share an open library of models, software, and access to high-performance computing. We also share knowledge that helps create higher-resolution simulations, often involving higher complexity algorithms. Together, we support the discovery, use, and conservation of natural resources; mitigation of natural hazards; geotechnical support of commercial and infrastructure development; environmental stewardship; and terrestrial surveillance for global security.