Jupyter Notebook AutoEncoders for MD Analysis tutorial Version 1
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Download RO-CrateAutoEncoders for Anomaly Detection tutorial using BioExcel Building Blocks (biobb)
This tutorial involves the use of a multilayer AutoEncoder (AE) for feature extraction and pattern recognition by analyzing Molecular Dynamic Simulations, step by step, using the BioExcel Building Blocks library (biobb).
Copyright & Licensing
This software has been developed in the MMB group at the BSC & IRB for the European BioExcel, funded by the European Commission (EU Horizon Europe 101093290, EU H2020 823830, EU H2020 675728).
- (c) 2015-2026 Barcelona Supercomputing Center
- (c) 2015-2026 Institute for Research in Biomedicine
Licensed under the Apache License 2.0, see the file LICENSE for details.
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Version 1 (earliest) Created 27th Mar 2026 at 08:59 by Genís Bayarri
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Created: 27th Mar 2026 at 08:59
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https://orcid.org/0000-0003-0513-0288
BioExcel is the leading European Centre of Excellence for Computational Biomolecular Research. Established in 2015, the centre has grown into a major research and innovation hub for scientific computing. BioExcel develops some of the most popular applications for modelling and simulations of biomolecular systems. A broad range of additional pre-/post-processing tools are integrated with the core applications within user-friendly workflows and container solutions.
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The BioExcel Building Blocks (biobb) software library is a collection of Python wrappers on top of popular biomolecular simulation tools. This library offers a layer of interoperability between the wrapped tools, which make them compatible and prepared to be directly interconnected to build complex biomolecular workflows. The building blocks can be used in many different workflow systems, including Galaxy, CWL, Jupyter Notebook and PyCOMPSs – notably their ...
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Interactive Jupyter Notebooks in combination with Conda environments can be used to generate FAIR (Findable, Accessible, Interoperable and Reusable/Reproducible) biomolecular simulation workflows. The interactive programming code accompanied by documentation, and the possibility to inspect intermediate results with versatile graphical charts and data visualization is very helpful, especially in iterative processes, where parameters might be adjusted to a particular system of interest. This work ...
