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Organizer: SIB Swiss Institute of Bioi...  or NanoCommons 

  • Online Jaqpot Hackathon

    3 June 2020

    Online Jaqpot Hackathon Under the subtitle “Take your research from the bench to the community by making your models available as a web service”, attendees learned how to use the Jaqpot suite and python to go from data to model, starting from a common CSV file. Jaqpot is a computational platform for in silico modelling of chemical compounds, that provides both access to its services both over a User Interface (GUI) and an Application Programming Interface (API). It is a cloud-ready application that uses the benefits of Java, R and Python, having incorporated functionality by various established and open-source machine learning and data analysis toolkits, while algorithms in any programming algorithm can be added to Jaqpot. Attached you find the following presentations: 1. Intro to NanoCommons by Martin Himly, PLUS 2. Electronic Lab Notebooks by Iseult Lynch, UoB 3. NanoCommons Knowledgebase by Dieter Maier, Biomax 4. Jaqpot Suite by Philip Doganis, NTUA 2020-06-03 10:00:00 UTC 2020-06-03 13:30:00 UTC NanoCommons [] [] early stage researchers in nanosafetymodellers for nanosafety predictionexperienced researchers in nanosafety workshops_and_courses [] Modelingdata FAIRnesstoxicity predictione-toolsnanoinformatics
  • Getting into using ELNs for experimental and computational workflows

    14 July 2020

    Getting into using ELNs for experimental and computational workflows On Tuesday, July 14th 2020, the NanoCommons team, in a joint initiative with the NanoSafety Cluster, is offering an interactive online workshop on implementing Electronic Laboratory Notebooks (ELNs) for nanosafety assessment. Under the subtitle “Getting into using ELNs for experimental and computational workflows”, you will learn how to establish a workflow using Scinote-based electronic lab notebooks. This starts with an introduction to the Scinote inventory and continues with hands-on instructions on how to manage, modify, create, and import protocols for assays. Tasks can be defined and assigned to different users and/or groups. Finally, data (incl. all relevant metadata) can be exported resulting in reports that facilitate data FAIRness. Technology advancement, the emergence of nanoinformatics and FAIR data principles implementation have increased the need for high-quality datasets. To achieve this, the data produced through academia, industry and regulatory bodies needs to be properly curated, to contain sufficient metadata and to be semantically annotated. In this way, data can be accessible and readable from both humans and machines, making it possible to be queried and mined using appropriate systems. One of the main objectives of NanoCommons is to promote the FAIR data principles, cross-project collaboration and data interoperability. This will make it possible to offer the nanosafety community high quality data that can be combined to produce big datasets and be used in novel modelling, machine learning, deep learning and AI techniques. The University of Birmingham (UoB) aims to achieve this by implementing data management processes covering the entire data lifecycle, and by moving the data curation process to the data generators. Capturing the data and metadata as they are produced will save substantial time and resources, while resulting in higher quality datasets. ELNs can be implemented, through cloud services or locally, into everyday experimental practice streamlining and simplifying experimental and computational workflows, practices and data capturing. 2020-07-14 10:00:00 UTC 2020-07-14 14:00:00 UTC NanoCommons [] [] Bench biologistscomputational scientists workshops_and_courses [] electronic lab notebook

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