BayesSuites: an Open Web Framework for Visualization of Massive Bayesian Networks

Bernaola Álvarez, Nikolas, Michiels Toquero, Mario, Bielza Lozoya, María Concepción ORCID: https://orcid.org/0000-0001-7109-2668 and Larrañaga Múgica, Pedro María ORCID: https://orcid.org/0000-0002-1885-4501 (2020). BayesSuites: an Open Web Framework for Visualization of Massive Bayesian Networks. "Proceedings of Machine Learning Research", v. 138 ; pp. 1-4. ISSN 2640-3498.

Description

Title: BayesSuites: an Open Web Framework for Visualization of Massive Bayesian Networks
Author/s:
Item Type: Article
Título de Revista/Publicación: Proceedings of Machine Learning Research
Date: 2020
ISSN: 2640-3498
Volume: 138
Subjects:
Freetext Keywords: Bayesian networks, Interpretability, Visualization of massive networks, Gene regulatory networks
Faculty: E.T.S. de Ingenieros Informáticos (UPM)
Department: Inteligencia Artificial
Creative Commons Licenses: Recognition - No derivative works - Non commercial

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Abstract

BayesSuites 1 is the first web framework for learning, visualizing, and interpreting Bayesian networks that can scale to tens of thousands of nodes while providing fast and friendly user experience. BayesSuites solves the problems of scalability, extensibility and interpretability that massive networks bring by separating backend calculations from the frontend interface and using specialized learning algorithms for massive networks. We demonstrate the tool by learning and visualizing a genome-wide gene regulatory network from human brain data with 20,708 nodes.

More information

Item ID: 68483
DC Identifier: https://oa.upm.es/68483/
OAI Identifier: oai:oa.upm.es:68483
Official URL: http://proceedings.mlr.press/v138/bernaola20a/bern...
Deposited by: Biblioteca Facultad de Informatica
Deposited on: 24 Feb 2023 09:39
Last Modified: 24 Feb 2023 09:39
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