Canadian Centre for Computational Genomics
Analytical solutions for Next-Generation Sequencing data
- 2026
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Analytical solutions for Next-Generation Sequencing data
Amplifying Research Imapct through Open Source
Tool development in bioinformatics, computational biology, data visualization
DBpedia is a crowd-sourced community effort to extract structured information from Wikipedia and make this information available on the Web. It allows for a global and unified access to Knowledge Graphs.
EMBL-EBI is a global centre for biological data, developing and maintaining open data resources and open-source software that support life science research worldwide. Our services are used daily by researchers across academia, healthcare, and industry, and span genomics, transcriptomics, metagenomics, molecular interactions, chemistry, and functional annotation.
The International Neuroinformatics Coordinating Facility (INCF; www.incf.org) is an international organization launched in 2005, following a proposal from the Global Science Forum of the OECD.
Integrating biological data sources, making it easy to query and analyse data
U.S. IOOS is a national and regional partnership working to provide ocean, coastal and Great Lakes observations, data, tools, and forecasts to improve safety, enhance the economy, and protect our environment. Our primary purpose is to provide free and open data about the state of our oceans and Great Lakes to our users. These data are fundamental to understanding the health of our marine ecosystems, to monitor the climate signal as captured in oceanographic conditions, and to provide predictions about the future state of our oceans and coasts.
Open for Innovation
Metaflow is a human-friendly Python library that makes it straightforward to develop, deploy, and operate various kinds of data-intensive applications, in particular those involving data science, ML, and AI. Metaflow was originally developed at Netflix to boost the productivity of data scientists who work on a wide variety of projects, from classical statistics to state-of-the-art deep learning.
a fast, flexible machine learning library
Open-source software for mass spectrometry
The National Resource for Network Biology (NRNB, https://nrnb.org) organizes the development of free, open-source software technologies to enable network-based visualization, analysis, and biomedical discovery. Biomedical research is increasingly dependent on knowledge expressed in terms of networks, including gene, protein and drug interactions, cell-cell and viral-host communication, and vast social networks. Our technologies enable researchers to assemble and analyze these networks and to use them to better understand biological systems and, in particular, how they fail in disease. The NRNB mentoring organization includes projects such as Cytoscape (https://cytoscape.org/), WikiPathways (https://wikipathways.org/), SBML (https://sbml.org/), SBGN (https://sbgn.github.io/) and others. This is a great opportunity to work at the intersection of biology and computing! For example, Cytoscape is downloaded over 24,000 times per month by researchers. We take mentoring seriously and are proud of our 96% success rate (https://nrnb.org/alumni.html#gsoc-tab) with former students and projects. But don’t take our word for it, read testimonials from prior NRNB students (https://nrnb.org/testimonials.html#student-tab) and mentors (https://nrnb.org/testimonials.html#mentor-tab). Find out more about the software projects being developed in coordination with NRNB at our website (https://nrnb.org). Also refer to our GSoC page (https://nrnb.org/gsoc.html) for additional resources and application tips.
NumFOCUS supports and promotes world-class, innovative, open source scientific software. Most individual projects, even the wildly successful ones, find the overhead of a non-profit to be too large for their community to bear. NumFOCUS provides a critical service as an umbrella organization for this projects.
Advancing Open Source & Open Science for Chemistry
OpenAstronomy is a collaboration between open source astronomy, astrophysics & heliophysics projects that are used by researchers and software engineers around the world to study our universe either by analysing the data obtained from amazing instruments like the [James Webb Space telescope](https://jwst.nasa.gov/), the [Square Kilometer Array](https://www.skatelescope.org/) or the [Solar Dynamic Observatory](http://sdo.gsfc.nasa.gov/), developing very sophisticated numerical models (eg., [FLASH](http://flash.uchicago.edu/)) or designing interplanetary trajectories for human-made spacecraft. The analysis of such data helps multiple types of research, from being able to forecast solar storms to detecting planets in other stars, to understanding how galaxies are formed to explain the expansion and the origin of the universe.
Climate change science has witnessed an explosion in the amount and types of data that can be brought to bear on the potential responses of the terrestrial carbon cycle and biodiversity to global change. Many of the most pressing questions about global change are not necessarily limited by the need to collect new data as much as by our ability to synthesize existing data. This project specifically seeks to improve this ability. Because no one measurement provides a complete picture, multiple data sources must be integrated in a sensible manner. Process-based models represent an ideal framework for integrating these data streams because they represent multiple processes at different spatial and temporal scales in ways that capture our current understanding of the causal connections across scales and among data types. Three components are required to bridge this gap between the available data and the required level of understanding: 1) state-of-the-art ecosystem model, 2) a workflow management system to handle the numerous streams of data, and 3) a data assimilation statistical framework in order to synthesize the data with the model.
The Most Versatile Data Management Platform
R provides a wide variety of statistical and graphical techniques, and is highly extensible. R is often the tool of choice for research in statistical methodology.
Research on Multimodal Communication
Tools for scientific computation in Ruby
Unified and efficient Machine Learning
TensorFlow is a ML framework for everyone.
The Julia Language is an open-source, high level, and dynamic language built to be easy to use like Python while having speed near C++. As an umbrella organization, we house projects related to core Julia (the language) as well as packages from the broader Julia ecosystem.
Contributor counts are accepted projects per cycle.
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