GSVA score reveals molecular signatures from transcriptomes for biomaterials comparison

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MetadadosDescriçãoIdioma
Autor(es): dc.contributorUniversidade Estadual Paulista (Unesp)-
Autor(es): dc.contributorUniversidade de São Paulo (USP)-
Autor(es): dc.creatorFerreira, Marcel R. [UNESP]-
Autor(es): dc.creatorSantos, Gerson A. [UNESP]-
Autor(es): dc.creatorBiagi, Carlos A.-
Autor(es): dc.creatorSilva Junior, Wilson A.-
Autor(es): dc.creatorZambuzzi, Willian F. [UNESP]-
Data de aceite: dc.date.accessioned2022-02-22T00:32:22Z-
Data de disponibilização: dc.date.available2022-02-22T00:32:22Z-
Data de envio: dc.date.issued2020-12-11-
Data de envio: dc.date.issued2020-12-11-
Data de envio: dc.date.issued2019-12-31-
Fonte completa do material: dc.identifierhttp://dx.doi.org/10.1002/jbm.a.37090-
Fonte completa do material: dc.identifierhttp://hdl.handle.net/11449/201023-
Fonte: dc.identifier.urihttp://educapes.capes.gov.br/handle/11449/201023-
Descrição: dc.descriptionTwo in silico methodologies were implemented to reveal the molecular signatures of inorganic hydroxyapatite and β-TCP materials from a transcriptome database to compare biomaterials. To test this new methodology, we choose the array E-MTAB-7219, which contains the transcription profile of osteoblastic cell line seeded onto 15 different biomaterials up to 48 hr. The expansive potential of the methodology was tested from the construction of customized signatures. We present, for the first time, a methodology to compare the performance of different biomaterials using the transcriptome profile of the cell through the Gene set variation analysis (GSVA) score. To test this methodology, we implemented two methods based on MSigDB collections, using all the collections and sub-collections except the Hallmark collection, which was used in the second method. The result of this analysis provided an initial understanding of biomaterial grouping based on the cell transcriptional landscape. The comparison using GSVA score combined efforts and expand the potential to compare biomaterials using transcriptome profile. Altogether, our results provide a better understanding of the comparison of different biomaterials and suggest a possibility of the new methodology be applied to the prospection of new biomaterials.-
Descrição: dc.descriptionLaboratory of Bioassays and Cellular Dynamics Department of Chemistry and Biochemistry Institute of Biosciences São Paulo State University UNESP-
Descrição: dc.descriptionGenomic Medicine Center Department of Genetics of the Ribeirao Preto Medical School University of Sao Paulo-
Descrição: dc.descriptionLaboratory of Bioassays and Cellular Dynamics Department of Chemistry and Biochemistry Institute of Biosciences São Paulo State University UNESP-
Idioma: dc.languageen-
Relação: dc.relationJournal of Biomedical Materials Research - Part A-
???dc.source???: dc.sourceScopus-
Palavras-chave: dc.subjectalternative methods-
Palavras-chave: dc.subjectanalysis-
Palavras-chave: dc.subjectbioinformatics-
Palavras-chave: dc.subjectbiomaterials-
Palavras-chave: dc.subjectbone-
Palavras-chave: dc.subjectin silico-
Título: dc.titleGSVA score reveals molecular signatures from transcriptomes for biomaterials comparison-
Tipo de arquivo: dc.typelivro digital-
Aparece nas coleções:Repositório Institucional - Unesp

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