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5 materials found

Resource type: Jupyter notebook  or Manual 


BioExcel Building Blocks (BioBB) Training Material

BioExcel Building Blocks (BioBB) is a software library for interoperable biomolecular simulation workflows, built within the BioExcel CoE project, and developed following best practices on software development aligned with ELIXIR.

Keywords: molecular dynamics, Docking, Modeling, life sciences

Resource type: Jupyter notebook

DE-Sim examples, tutorials, and documentation

DE-Sim is an open-source, Python-based object-oriented discrete-event simulation (DES) tool that makes it easy to use large, heterogeneous datasets and high-level data science tools such as NumPy, Scipy,...

Scientific topics: Computational biology, Mathematics, Computer science, Simulation experiment

Operations: Visualisation, Modelling and simulation

Keywords: data-driven modeling, Computational modelling, discrete-event simulation, DES, object-oriented programming, Python, data visualization, Data Science

Resource type: examples, Tutorial, Jupyter notebook, API reference

How to use Common Workflow Language

This is an online tutorial where you can learn how to write tool wrappers and workflows using the Common Workflow Language (CWL). The materials provided here describe the first stable version of the CWL - Version 1.0. The tutorial is hosted on the [ELIXIR-SI eLearning...

Scientific topics: Workflows

Keywords: commonwl, common workflow language, CWL, Workflows, eLearning, EeLP

Resource type: Installation instructions, Manual

How to install and deploy Beacon

This is an online tutorial where you can learn how to install the Beacon application and "light a beacon" (i.e. deploy the Beacon application) on your data.

The tutorial is hosted on the ELIXIR-SI eLearning Platform (EeLP). The main part of the tutorial are learning materials with...

Scientific topics: Genomics

Keywords: genomics, open access, eLearning, EeLP

Resource type: Video, Manual, Slides, Installation instructions

Introductory image processing on biological images using python.

This is an image processing practical for students with an interest in analysing biologically derived images. It is written in the language python and utilises jupyter notebook for annotation and visualisation of the code. The practical is beginner level, although some knowledge of python is...

Resource type: Jupyter notebook, PDF