DENIS@home

From BOINC Projects
Revision as of 16:26, 19 May 2026 by Al Piskun (talk | contribs) (infobox and updates)
Jump to navigation Jump to search

[[File:{{#setmainimage:DENIS@Home Logo.png}}|alt=logo image|center|frameless]]











DENIS@home
DENIS@home application preferences interface
Development
DeveloperCoMBA Research Group, Universidad San Jorge
Initial release2016
Software
Written inC++, BOINC
Operating systemWindows, Linux, macOS
Metadata
Websitedenis.usj.es/denisathome
LicenseApache License 2.0

DENIS@home is a volunteer distributed computing project based on the BOINC middleware platform. The project is operated by the CoMBA (Computational Multiscale Biology and Medicine) research group at Universidad San Jorge in Zaragoza, Spain, and focuses on large-scale simulations of cardiac electrophysiology and cardiovascular disease research.[1][2]

The project's name is an acronym representing its five main principles: Distributed computing, Electrophysiological models, Networking collaboration, In silico research, and Sharing knowledge.[3]

Universidad San Jorge, home institution of the DENIS@home project

History

DENIS@home was launched in 2016 as a research initiative to use volunteer computing for the simulation of cardiac electrophysiological models.[4] The project was developed by researchers from the CoMBA group to provide computational resources for large-scale studies into cardiac arrhythmias, ventricular cell behavior, and the effects of drugs on the human heart.[5]

The project was listed among BOINC-based scientific computing initiatives by the University of California, Berkeley and has been referenced in volunteer computing communities and distributed computing forums.[6]

Why DENIS@home?

More than 17 million people die each year from cardiovascular diseases, representing approximately 31% of all global deaths.[7] DENIS@home was created to provide researchers with the computational power required to investigate the electrical activity of the heart and develop improved cardiac electrophysiological models.

The platform allows volunteers to donate unused CPU processing time from their personal computers to scientific simulations.[8]

Goal

The five pillars of DENIS@home are:

  • Distributed computing
  • Electrophysiological models
  • Networking collaboration
  • In silico research
  • Sharing knowledge

Distributed computing

DENIS@home uses volunteer computers to perform large numbers of cardiac electrophysiological simulations. The project uses the idle processing capacity of Windows, Linux, and macOS computers connected through the BOINC middleware platform.[9]

The distributed nature of BOINC enables researchers to process large simulation batches that would otherwise require access to expensive supercomputing infrastructure.[10]

Electrophysiological models

DENIS@home computes large sets of cardiac electrophysiological model variations. These models mathematically represent the electrical behavior of cardiac cells and are used to study arrhythmias, heart failure, and drug interactions.[11]

The models are described using the CellML language, an XML-based open standard developed by the Auckland Bioengineering Institute for storing and exchanging mathematical biological models.[12]

Cardiac electrical activity measured using an electrocardiogram

Networking collaboration

The project was designed to connect volunteers and researchers internationally through a collaborative computing infrastructure. DENIS@home also encourages scientific collaboration between institutions and research groups working in computational cardiology.[13]

In silico research

The project focuses on in silico cardiac simulations, allowing researchers to investigate heart behavior under normal and pathological conditions using computer models rather than laboratory or clinical experimentation alone.[14]

Sharing knowledge

DENIS@home promotes open scientific research. Results produced using the project are expected to be published openly, and the software developed for the project is released under the Apache License 2.0.[15]

Methods

Volunteers may choose to run one or more scientific applications through the BOINC client:

Electrophysiological models are used to investigate the electrical activity of cardiac cells and predict the effects of pharmaceutical compounds and pathological conditions on the heart.[16]

All DENIS@home software is distributed under the Apache License 2.0 and source code has been published through the project's Bitbucket repositories.[17]

preferences
DENIS@home application selection preferences

Computing platform

DENIS@home applications are available for:

  • Microsoft Windows
  • Linux
  • macOS

The project primarily uses CPU-based computations and supports both 32-bit and 64-bit systems depending on application version.[18]

Project team / Sponsors

The members of the research group participating in the project include:

  • Jesús Carro
  • Violeta Monasterio
  • Alejandro Alcaine
  • Marta Gómez

DENIS@home is developed and maintained by the CoMBA research group at Universidad San Jorge.[19]

Scientific results

The project publishes scientific results and associated research papers through its official publications page.[20]

Scientific publications

Research results from DENIS@home

  1. J. Carro (2019). New Methodologies for the Development and Validation of Electrophysiological Models. PhD Thesis.
  2. J. Carro, J.F. Rodríguez-Matas, E. Pueyo (2016). A Methodology to Improve Human Ventricular Models for the Investigation of Cardiac Arrhythmias. Biophysical Journal 111(12):2706–2715.
  3. V. Monasterio, J. Castro-Mur, J. Carro (2018). DENIS: Solving cardiac electrophysiological simulations with volunteer computing. PLoS ONE 13(10):e0205568.
  4. J. Castro-Mur, V. Monasterio, J. Carro (2016). Volunteer Computing Approach for the Collaborative Simulation of Electrophysiological Models. IEEE WETICE 2016.

Research results using DENIS@home software

  1. M. Gomez, J. Carro, E. Pueyo, V. Monasterio (2022). An in Silico Investigation into the Role of SK Channels in Failing Ventricular Myocytes. Computing in Cardiology Conference 2022.
  2. M. Gomez, J. Carro, V. Monasterio, E. Pueyo (2022). Investigación in silico sobre el papel de los canales SK en miocitos ventriculares de pacientes con insuficiencia cardiaca. Jornada de Jóvenes Investigadores e Investigadoras del I3A.
  3. M. Gómez, J. Carro, E. Pueyo, V. Monasterio (2021). Modificación de un modelo de miocito ventricular humano para representar el papel de los canales SK en insuficiencia cardiaca. CASEIB 2021.

Publications about DENIS@home

  1. V. Monasterio, J. Castro-Mur, J. Carro (2018). DENIS: Solving cardiac electrophysiological simulations with volunteer computing. PLoS ONE 13(10):e0205568.
  2. J. Castro-Mur, V. Monasterio, J. Carro (2016). Volunteer Computing Approach for the Collaborative Simulation of Electrophysiological Models. IEEE WETICE 2016.

See also

External links

References

  1. DENIS@home. Universidad San Jorge. Retrieved 2026-05-19}.
  2. (2018}).DENIS: Solving cardiac electrophysiological simulations with volunteer computing. PLoS ONE. pp. e0205568. DOI: 10.1371/journal.pone.0205568.
  3. DENIS@home Overview. Universidad San Jorge. Retrieved 2026-05-19}.
  4. Castro-Mur, J..(2016})."Volunteer Computing Approach for the Collaborative Simulation of Electrophysiological Models".pp. 118–123.DOI: 10.1109/WETICE.2016.34.
  5. (2018}).DENIS: Solving cardiac electrophysiological simulations with volunteer computing. PLoS ONE. pp. e0205568. DOI: 10.1371/journal.pone.0205568.
  6. BOINC Projects List. University of California, Berkeley. Retrieved 2026-05-19}.
  7. Cardiovascular diseases (CVDs). World Health Organization. Retrieved 2026-05-19}.
  8. DENIS@home. Universidad San Jorge. Retrieved 2026-05-19}.
  9. BOINC. University of California, Berkeley. Retrieved 2026-05-19}.
  10. (2004}).BOINC: A System for Public-Resource Computing and Storage. 5th IEEE/ACM International Workshop on Grid Computing. DOI: 10.1109/GRID.2004.14.
  11. (2016}).A Methodology to Improve Human Ventricular Models for the Investigation of Cardiac Arrhythmias. Biophysical Journal. pp. 2706–2715. DOI: 10.1016/j.bpj.2016.11.2183.
  12. CellML. Auckland Bioengineering Institute. Retrieved 2026-05-19}.
  13. (2018}).DENIS: Solving cardiac electrophysiological simulations with volunteer computing. PLoS ONE. pp. e0205568. DOI: 10.1371/journal.pone.0205568.
  14. (2018}).DENIS: Solving cardiac electrophysiological simulations with volunteer computing. PLoS ONE. pp. e0205568. DOI: 10.1371/journal.pone.0205568.
  15. Apache License 2.0. Apache Software Foundation. Retrieved 2026-05-19}.
  16. (2016}).A Methodology to Improve Human Ventricular Models for the Investigation of Cardiac Arrhythmias. Biophysical Journal. pp. 2706–2715. DOI: 10.1016/j.bpj.2016.11.2183.
  17. DENIS Bitbucket Repository. Bitbucket. Retrieved 2026-05-19}.
  18. DENIS@home Applications. Universidad San Jorge. Retrieved 2026-05-19}.
  19. CoMBA Research Group. Universidad San Jorge. Retrieved 2026-05-19}.
  20. DENIS@home Publications. Universidad San Jorge. Retrieved 2026-05-19}.