BioExcel is a Centre of Excellence for Biomolecular Research, initially funded for three years by the EC Horizon 2020 program for e-Infrastructure, and refunded for another three years in BioExcel-2. (BioExcel-3 is funded from 2023, but without The University of Manchester participating, as the funding programme moved to EuroHPC which the UK is not participating in).

The centre facilitate the use of high-performance computing (HPC) and high-throughput computing (HTC) in biomolecular research, both in academia and industry.

The BioExcel project aims to improve the performance, efficiency, scalability and accessibility of software for biomolecular modelling (in particular GROMACS, HADDOCK, CP2K, PMX), allowing such tools to be scaled up to run on larger supercomputer systems, while also making them easier for biomolecular researchers to use on computational infrastructures by providing training and guidance on best practices and integration with commonly used workflow systems such as CWL, KNIME, Galaxy, Apache Taverna or COMPSs.

As a Centre of Excellence, BioExcel gathers biomolecular consultants with experience in both HPC/HTC and the life sciences, who can assist both academic and industrial researchers with using and improving tools for computational biomolecular research.

eScience Lab contributions

In the BioExcel-2 project we were involved in:

  • WP2: Convergence of HPC/HPDA and Improved Usability (deputy lead)
    • T2.1: Application building blocks for computational biomolecular simulations
    • T2.2: Definition, development and specification of workflow prototypes and demonstrators
    • T2.4: Convergence of High Performance Computing (HPC) and High-Performance Data Analytics (HPDA)
    • T2.5: Provisioning and maintaining a Workflow Environment
    • T2.6: Retaining usability, interoperability and reproducibility in Exascale workflows (task lead)
  • WP3: Community, Support and Use Cases
    • T3.1: Use Case Support
    • T3.2: Community Participation
    • T3.3: In-Depth Support
    • T3.4: Standards and Best Practice (task lead)
    • T3.5: User & Community Needs Analysis
    • T3.6: Challenge Participation and Support
  • WP4: Dissemination and Training
    • T4.1: Evaluate and test virtual learning environment
    • T4.2: Promotion and outreach
    • T4.3: User training
    • T4.4: Capacity building and knowledge transfer
    • T4.5: Collaboration

We built on our extensive experience and engagement with Common Workflow Language (CWL) and Research Objects and strengthened links between BioExcel communities and related projects like ELIXIR, EOSC and BioConda.

We developed and maintain the CWL Viewer with support from BioExcel, now maintained by Curii. We contributed to the BioExcel Building Blocks (BioBB) library, translating workflows into CWL and assisting with the development of their tutorial material and containers for Docker and Conda. We are also assisting with registering BioBB workflows on WorkflowHub.

Selected deliverables

See also full list of BioExcel deliverables.

BioExcel-2 (2019-2022)

BioExcel (2016-2018)

Selected publications

See also full list of BioExcel publications.

Stian Soiland-Reyes, Peter Sefton, Mercè Crosas, Leyla Jael Castro, Frederik Coppens, José M. Fernández, Daniel Garijo, Björn Grüning, Marco La Rosa, Simone Leo, Eoghan Ó Carragáin, Marc Portier, Ana Trisovic, RO-Crate Community, Paul Groth, Carole Goble (2022):
Packaging research artefacts with RO-Crate.
Data Science 5(2)

Michael R. Crusoe, Sanne Abeln, Alexandru Iosup, Peter Amstutz, John Chilton, Nebojša Tijanić, Hervé Ménager, Stian Soiland-Reyes, Bogdan Gavrilović, Carole Goble, The CWL Community (2022):
Methods Included: Standardizing Computational Reuse and Portability with the Common Workflow Language.
Communications of the ACM 65(6)

Paul Brack, Peter Crowther, Stian Soiland-Reyes, Stuart Owen, Douglas Lowe, Alan R Williams, Quentin Groom, Mathias Dillen, Frederik Coppens, Björn Grüning, Ignacio Eguinoa, Philip Ewels, Carole Goble (2022):
Ten Simple Rules for making a software tool workflow-ready.
PLOS Computational Biology 18(3):e1009823

Stian Soiland-Reyes, Genís Bayarri, Pau Andrio, Robin Long, Douglas Lowe, Ania Niewielska, Adam Hospital, Paul Groth (2022):
Making Canonical Workflow Building Blocks interoperable across workflow languages.
Data Intelligence 4(2)

Genís Bayarri, Pau Andrio, Adam Hospital, Modesto Orozco, Josep Lluís Gelpí (2022):
BioExcel Building Blocks REST API (BioBB REST API), programmatic access to interoperable biomolecular simulation tools.
Bioinformatics 38(12)

Rosa M. Badia, Javier Conejero, Jorge Ejarque, Daniele Lezzi, Francesc Lordan (2022):
PyCOMPSs as an instrument for Translational Computer Science.
Computing in Science and Engineering 24(2)

Genís Bayarri, Pau Andrio, Adam Hospital, Modesto Orozco, Josep Lluís Gelpí (2022):
BioExcel Building Blocks Workflows (BioBB-Wfs), an integrated web-based platform for biomolecular simulations.
Nucleic Acids Research 50(W1)

Carole Goble, Sarah Cohen-Boulakia, Stian Soiland-Reyes, Daniel Garijo, Yolanda Gil, Michael R. Crusoe, Kristian Peters, Daniel Schober (2020):
FAIR Computational Workflows.
Data Intelligence 2(1):108–121

Farah Zaib Khan, Stian Soiland-Reyes, Richard O. Sinnott, Andrew Lonie, Carole Goble, Michael R. Crusoe (2019):
Sharing interoperable workflow provenance: A review of best practices and their practical application in CWLProv.
GigaScience 8(11):giz095

Pau Andrio, Adam Hospital, Javier Conejero, Luis Jordá, Marc Del Pino, Laia Codo, Stian Soiland-Reyes, Carole Goble, Daniele Lezzi, Rosa M. Badia, Modesto Orozco, Josep Ll. Gelpi (2019):
BioExcel Building Blocks, a software library for interoperable biomolecular simulation workflows.
Scientific Data 6:169

Stian Soiland-Reyes, Marcos Cáceres (2018):
The Archive and Package (arcp) URI scheme.
2018 IEEE 14th International Conference on e-Science (e-Science).

Gil Alterovitz, Dennis A Dean II, Carole Goble, Michael R Crusoe, Stian Soiland-Reyes, Amanda Bell, Anais Hayes, Anita Suresh, Charles Hadley S King IV, Dan Taylor, KanakaDurga Addepalli, Elaine Johanson, Elaine E Thompson, Eric Donaldson, Hiroki Morizono, Hsinyi Tsang, Jeet K Vora, Jeremy Goecks, Jianchao Yao, Jonas S Almeida, Jonathon Keeney, KanakaDurga Addepalli, Konstantinos Krampis, Krista Smith, Lydia Guo, Mark Walderhaug, Marco Schito, Matthew Ezewudo, Nuria Guimera, Paul Walsh, Robel Kahsay, Srikanth Gottipati, Timothy C Rodwell, Toby Bloom, Yuching Lai, Vahan Simonyan, Raja Mazumder (2018):
Enabling Precision Medicine via standard communication of NGS provenance, analysis, and results.
PLOS Biology. 16(12):e3000099

Steffen Möller, Stuart W. Prescott, Lars Wirzenius; Petter Reinholdtsen, Brad Chapman, Pjotr Prins, Stian Soiland-Reyes, Fabian Klötzl, Andrea Bagnacani, Matúš Kalaš, Andreas Tille, Michael R. Crusoe (2017):
Robust cross-platform workflows: how technical and scientific communities collaborate to develop, test and share best practices for data analysis..
Data Science and Engineering 2:232 pp 232–244.

Julie A McMurry, Nick Juty, Niklas Blomberg, Tony Burdett, Tom Conlin, Nathalie Conte, Mélanie Courtot, John Deck, Michel Dumontier, Donal K Fellows, Alejandra Gonzalez-Beltran, Philipp Gormanns, Jeffrey Grethe, Janna Hastings, Jean-Karim Hériché, Henning Hermjakob, Jon C Ison, Rafael C Jimenez, Simon Jupp, John Kunze, Camille Laibe, Nicolas Le Novère, James Malone, Maria Jesus Martin, Johanna R McEntyre, Chris Morris, Juha Muilu, Wolfgang Müller, Philippe Rocca-Serra, Susanna-Assunta Sansone, Murat Sariyar, Jacky L Snoep, Stian Soiland-Reyes, Natalie J Stanford, Neil Swainston, Nicole Washington, Alan R Williams, Sarala M Wimalaratne, Lilly M Winfree, Katherine Wolstencroft, Carole Goble, Cristopher J Mungall, Melissa A Haendel, Helen Parkinson (2017):
Identifiers for the 21st century: How to design, provision, and reuse identifiers to maximize utility and impact of life science data.
PLOS Biology 15(6):e2001414

Kyle Chard, Mike D’ Arcy, Ben Heavner, Ian Foster, Carl Kesselman, Ravi Madduri, Alexis Rodriguez, Stian Soiland-Reyes, Carole Goble, Kristi Clark, Eric W. Deutsch, Ivo Dinov, Nathan Price, Arthur Toga (2016):
I’ll Take That to Go: Big Data Bags and Minimal Identifiers for Exchange of Large, Complex Datasets.
IEEE International Conference on Big Data 2016 5 December 2016. [preprint] [pdf] [zenodo] [researchgate]