DENIS@home: Difference between revisions
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In DENIS@home you can run different research projects. Each one uses a different application that you can choose to run. | In DENIS@home you can run different research projects. Each one uses a different application that you can choose to run. | ||
* '''[https://denis.usj.es/denisathome/projects.php#DENIS_Myocyte_Beta ''Beta of DENIS-myocyte (DENIS_Myocyte_Beta)'']''': Beta version of the simulator used for all | * '''[https://denis.usj.es/denisathome/projects.php#DENIS_Myocyte_Beta ''Beta of DENIS-myocyte (DENIS_Myocyte_Beta)'']''': Beta version of the simulator used for all DENIS@home applications. Every modification of the simulator is tested under this application. | ||
* '''[https://denis.usj.es/denisathome/projects.php#NHuVe ''New human ventricular cell model (NHuVe)'']''': Development of a new version of the model proposed by Carro et. al (2011). | * '''[https://denis.usj.es/denisathome/projects.php#NHuVe ''New human ventricular cell model (NHuVe)'']''': Development of a new version of the model proposed by Carro et. al (2011). | ||
* '''[https://denis.usj.es/denisathome/projects.php#HuVeMOp ''Human ventricular cell models optimization (HuVeMOp)'']''': Optimization of the public and most used human ventricular cell models for the representation of electrophysiological markers. | * '''[https://denis.usj.es/denisathome/projects.php#HuVeMOp ''Human ventricular cell models optimization (HuVeMOp)'']''': Optimization of the public and most used human ventricular cell models for the representation of electrophysiological markers. | ||
[[wikipedia:Electrophysiology|'''''Electrophysiological''''']] models are a powerful tool to study the electrical activity of cardiac cells under normal or pathological conditions and can also help predict the effects of drugs in the heart. Because these models are complex, it's necessary to simulate them many times (varying the conditions or model parameters). For this reason, researchers in this field usually require high computational power and BOINC is the perfect solution to distribute the work to volunteer computers and achieve that high computational power. | |||
Electrophysiological models are a powerful tool to study the electrical activity of cardiac cells under normal or pathological conditions and can also help predict the effects of drugs in the heart. Because these models are complex, it's necessary to simulate them many times (varying the conditions or model parameters). For this reason, researchers in this field usually require high computational power and BOINC is the perfect solution to distribute the work to volunteer computers | |||
== Project team / Sponsors == | == Project team / Sponsors == | ||
Revision as of 11:54, 10 February 2024
[[File:{{#setmainimage:DENIS@Home Logo.png}}|alt=logo image|center|frameless]]
DENIS@home is a volunteer distributed computing project that needs your help to investigate cardiovascular diseases (CVDs).
Why DENIS@home?
More than 17 million people die each year of cardiovascular diseases. That represents 31% of all global deaths, making these diseases the leading cause of death worldwide.
Goal
The five pillars of DENIS@home are:
- Distributed computing
- Electrophysiological models
- Networking collaboration
- In silico research
- Sharing knowledge
Methods
In DENIS@home you can run different research projects. Each one uses a different application that you can choose to run.
- Beta of DENIS-myocyte (DENIS_Myocyte_Beta): Beta version of the simulator used for all DENIS@home applications. Every modification of the simulator is tested under this application.
- New human ventricular cell model (NHuVe): Development of a new version of the model proposed by Carro et. al (2011).
- Human ventricular cell models optimization (HuVeMOp): Optimization of the public and most used human ventricular cell models for the representation of electrophysiological markers.
Electrophysiological models are a powerful tool to study the electrical activity of cardiac cells under normal or pathological conditions and can also help predict the effects of drugs in the heart. Because these models are complex, it's necessary to simulate them many times (varying the conditions or model parameters). For this reason, researchers in this field usually require high computational power and BOINC is the perfect solution to distribute the work to volunteer computers and achieve that high computational power.
Project team / Sponsors
Jesús Carro. Violeta Monasterio. Alejandro Alcaine. Marta Gómez.
Universidad San Jorge.
Scientific results
https://denis.usj.es/denisathome/publications.php