Register training material
5 materials found

Resource type: Jupyter notebook  or Vignette 


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

Research Data Management in Life Sciences

The content provided via this link was used in the training on 9 and 10 November 2020 organized by Ghent University and Elixir Belgium and VIB in collaboration with Interreg Vlaanderen-Nederland: https://training.vib.be/all-trainings/research-data-management-life-sciences.

Scientific topics: Data management

Resource type: Presentation, Vignette, Video

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

BridgeDbR Tutorial

BridgeDb is a combination of an application programming interface (API), library, and set of data files for mapping identifiers for identical objects [1]. Identifier mapping databases are available for gene products and metabolites. This Bioconductor Vignette explains how to use BridgeDb in the R...

Keywords: ELIXIR RIR, BridgeDb

Resource type: Tutorial, Vignette

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