DISA tool

Detalhes bibliográficos
Autor(a) principal: Alexandre, Leonardo
Data de Publicação: 2022
Outros Autores: Costa, R. S., Henriques, Rui
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10362/145247
Resumo: CEECIND/01399/2017
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spelling DISA toolDiscriminative and informative subspace assessment with categorical and numerical outcomesarticlebiomedicinebiotechnologydiscretizationhumanlicenceoutcome assessmentvaliditycluster analysissoftwareGeneralCEECIND/01399/2017Pattern discovery and subspace clustering play a central role in the biological domain, supporting for instance putative regulatory module discovery from omics data for both descriptive and predictive ends. In the presence of target variables (e.g. phenotypes), regulatory patterns should further satisfy delineate discriminative power properties, well-established in the presence of categorical outcomes, yet largely disregarded for numerical outcomes, such as risk profiles and quantitative phenotypes. DISA (Discriminative and Informative Subspace Assessment), a Python software package, is proposed to evaluate patterns in the presence of numerical outcomes using well-established measures together with a novel principle able to statistically assess the correlation gain of the subspace against the overall space. Results confirm the possibility to soundly extend discriminative criteria towards numerical outcomes without the drawbacks well-associated with discretization procedures. Results from four case studies confirm the validity and relevance of the proposed methods, further unveiling critical directions for research on biotechnology and biomedicine. Availability: DISA is freely available at https://github.com/JupitersMight/DISA under the MIT license.LAQV@REQUIMTEDQ - Departamento de QuímicaRUNAlexandre, LeonardoCosta, R. S.Henriques, Rui2022-11-04T22:10:49Z2022-10-192022-10-19T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article19application/pdfhttp://hdl.handle.net/10362/145247eng1932-6203PURE: 47209287https://doi.org/10.1371/journal.pone.0276253info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2024-03-11T05:25:25Zoai:run.unl.pt:10362/145247Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T03:51:58.802848Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv DISA tool
Discriminative and informative subspace assessment with categorical and numerical outcomes
title DISA tool
spellingShingle DISA tool
Alexandre, Leonardo
article
biomedicine
biotechnology
discretization
human
licence
outcome assessment
validity
cluster analysis
software
General
title_short DISA tool
title_full DISA tool
title_fullStr DISA tool
title_full_unstemmed DISA tool
title_sort DISA tool
author Alexandre, Leonardo
author_facet Alexandre, Leonardo
Costa, R. S.
Henriques, Rui
author_role author
author2 Costa, R. S.
Henriques, Rui
author2_role author
author
dc.contributor.none.fl_str_mv LAQV@REQUIMTE
DQ - Departamento de Química
RUN
dc.contributor.author.fl_str_mv Alexandre, Leonardo
Costa, R. S.
Henriques, Rui
dc.subject.por.fl_str_mv article
biomedicine
biotechnology
discretization
human
licence
outcome assessment
validity
cluster analysis
software
General
topic article
biomedicine
biotechnology
discretization
human
licence
outcome assessment
validity
cluster analysis
software
General
description CEECIND/01399/2017
publishDate 2022
dc.date.none.fl_str_mv 2022-11-04T22:10:49Z
2022-10-19
2022-10-19T00:00:00Z
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format article
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dc.identifier.uri.fl_str_mv http://hdl.handle.net/10362/145247
url http://hdl.handle.net/10362/145247
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 1932-6203
PURE: 47209287
https://doi.org/10.1371/journal.pone.0276253
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