![]() Enter NeoDash, a tool that allows you to build a dashboard in minutes. ![]() In many cases, however, I’m looking for something that allows me to quickly prototype a dashboard with a direct database connection. Fortunately, a ton of tools exist to make the life of a Neo4j front-end developer easier (great examples are the GrandStack and Neode). the university training "Création, analyse et valorisation de données biologiques omiques" ( DU Omiques).Working at Neo4j, I frequently build front-end applications that use graph data.EUR G.E.N.E., the graduate school on Genetics and Epigenetics,.Université de Paris, via the Initiative of Excellence (IdEx) Label and its "inovating teaching" grant program,.Région Île-de-France, via the “Trophées franciliens de l’innovation numérique dans le supérieur” ( EdTech 2018) grant program,.Sponsors to the PLASMA initiative include: The development of ipycytoscape at QuantStack was funded as part of the PLASMA project, led by Claire Vandiedonck, Pierre Poulain, and Sandrine Caburet, associate professors at Université de Paris. Prior to QuantStack I worked as a developer on the PySide team at the Qt Company and as a web performance developer at Mozilla.Ĭurrently I’m working on expanding the Jupyter ecosystem with new libraries and functionalities, like an experimental SQLite kernel. ![]() I care deeply about the impacts that technology has in the world and try my best to be the change I want to see by contributing to open source projects that stand upon libre and diverse standards. My name is Mariana Meireles and I’m a software developer working for QuantStack. ipycytoscape offers integration between Pandas DataFrames and NetworkX, meaning that you can have a graph visualization of the data you already have with minimal or none adjustments and just a few lines of code. In this first version of ipycytoscape, there are still some limitations to what you may be able to do, but there are also some extents from the Python world that will just work out of the box for you. For that purpose, a custom JupyterHub-based system to control many different Jupyter instances is being specially developed by Jeremy Tuloup at QuantStack. PlasmaBio provides an authentic experience of the actual genomic and bioinformatic analyses performed in research labs. Its first instance, PlasmaBio, is designed for the needs of teachers and students of the European Master of Genetics at Université de Paris. This project aims at creating an interactive tool to teach computational analysis of massive scientific data. IPycytoscape is part of the PLASMA project (aka in French, Plateforme d'eLearning pour l'Analyse de données Scientifiques MAssives). Currently, there is an effort to make ipycytoscape an accessible tool for researchers that are trying to find ways to mitigate and understand it, there is more information about this initiative on the COVID OSS Help website and the discussion is happening in this repository if you're interested in joining it. Some examples consist in the development of new chemicals to analyze interactions between substances in the pharmaceutic industry, in security systems to create attack graphs that can be useful to show possible vulnerabilities in systems, modeling human behavior to understand people’s interaction with business or even to understand complex phenomena like the current crisis. The goal of ipycytoscape is to enable users of well-established libraries of the Python ecosystem like Pandas, NetworkX, and NumPy, to visualize their graph data in the Jupyter notebook, and enable them modify the visual outcome programmatically or graphically with a simple API and user interface.įortunately, Cytoscape offers a broad enough API that allows ipycytoscape to be a tool that can, in fact, be used to solve any type of problem modeled as a graph.
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