A demonstration of modularity, reuse, reproducibility, portability and scalability for modeling and simulation of cardiac electrophysiology using Kepler Workflows.
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http://data.d4science.org/ctlg/RISIS2OpenData/dedup_wf_001--4334fa1e6ed12c75063383d8d6881de5 |
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Identity
Access Modality
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Access Right | Open Access |
Attribution
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Author | Yang, Pei-Chi, 0000-0002-5753-1131 |
Author | Purawat, Shweta, 0000-0002-5183-2750 |
Author | Ieong, Pek U. |
Author | Jeng, Mao-Tsuen, 0000-0003-4454-4299 |
Author | DeMarco, Kevin R. |
Author | Vorobyov, Igor, 0000-0002-4767-5297 |
Author | McCulloch, Andrew D., 0000-0002-1708-5675 |
Author | Altintas, Ilkay |
Author | Amaro, Rommie E. |
Author | Clancy, Colleen E., 0000-0001-6849-4885 |
Contributor | Sauro, Herbert |
Publishing
Field | Value |
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Collected From | PubMed Central; eScholarship - University of California; ORCID; Datacite; UnpayWall; DOAJ-Articles; Crossref; Microsoft Academic Graph |
Hosted By | Europe PubMed Central; eScholarship - University of California; PLoS Computational Biology |
Publication Date | 2019-03-08 |
Publisher | eScholarship, University of California |
Additional Info
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Country | United States |
Description | Author summary We present a computational workflow as a proof of concept for integration and implementation of a reusable and reproducible cardiac multi-scale electrophysiology model that is expandable, modular and portable. This framework enables scientists to create intuitive, user-friendly and flexible end-to-end automated scientific workflows using a graphical user interface. Kepler is an advanced open-source platform that supports multiple models of computation. The underlying workflow engine handles scalability, provenance, reproducibility aspects of the code, performs orchestration of data flow, and automates execution on heterogeneous computing resources. One of the main advantages of workflow utilization is the integration of code written in multiple languages Standardization occurs at the interfaces of the workflow elements and allows for general applications and easy comparison and integration of code from different research groups or even multiple programmers coding in different languages for various purposes from the same group. A workflow driven problem-solving approach enables domain scientists to focus on resolving the core science questions, and delegates the computational and process management burden to the underlying Workflow. The workflow driven approach allows scaling the computational experiment with distributed data-parallel execution on multiple computing platforms, such as, HPC resources, GPU clusters, Cloud etc. The workflow framework tracks software version information along with hardware information to allow users an opportunity to trace any variation in workflow outcome to the system configurations. |
Format | application/pdf |
Language | Undetermined |
Resource Type | Other literature type; Article |
keyword | keywords.Ecology, Evolution, Behavior and Systematics |
system:type | publication |
Management Info
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Source | https://science-innovation-policy.openaire.eu/search/publication?articleId=dedup_wf_001::4334fa1e6ed12c75063383d8d6881de5 |
Author | jsonws_user |
Last Updated | 23 December 2020, 03:16 (CET) |
Created | 23 December 2020, 03:16 (CET) |