An adaptation of particle swarm clustering applied in basal cell carcinoma, squamous cell carcinoma of the skin and actinic keratosis

Página do item simplificado
dc.creatorFabiano de Oliveira Poswar
dc.creatorLaércio Ives Santos
dc.creatorLucyana Conceição Farias
dc.creatorTalita Antunes Guimarães
dc.creatorSérgio Henrique Sousa Santos
dc.creatorKimberly Marie Jones
dc.creatorAlfredo Maurício Batista de Paula
dc.creatorReinaldo Martinez Palhares
dc.creatorMarcos Flávio Silveira Vasconcelos D'Angelo
dc.creatorAndré Luiz Sena Guimarães
dc.date.accessioned2023-12-04T12:55:22Z
dc.date.accessioned2025-09-08T23:59:56Z
dc.date.available2023-12-04T12:55:22Z
dc.date.issued2017-06
dc.description.sponsorshipCNPq - Conselho Nacional de Desenvolvimento Científico e Tecnológico
dc.description.sponsorshipFAPEMIG - Fundação de Amparo à Pesquisa do Estado de Minas Gerais
dc.description.sponsorshipCAPES - Coordenação de Aperfeiçoamento de Pessoal de Nível Superior
dc.identifier.doihttps://doi.org/10.1016/j.mgene.2017.01.007
dc.identifier.issn2214-5400
dc.identifier.urihttps://hdl.handle.net/1843/61668
dc.languageeng
dc.publisherUniversidade Federal de Minas Gerais
dc.relation.ispartofMeta Gene
dc.rightsAcesso Restrito
dc.subjectCarcinoma basocelular
dc.subjectCarcinoma de células escamosas
dc.subjectPele - Câncer
dc.subjectBioinformática
dc.subjectCeratose
dc.subject.otherParticle swarm clustering
dc.subject.otherBioinformatics
dc.subject.otherSkin cancers
dc.subject.otherPotential malignant lesion
dc.subject.otherMetastasis
dc.titleAn adaptation of particle swarm clustering applied in basal cell carcinoma, squamous cell carcinoma of the skin and actinic keratosis
dc.typeArtigo de periódico
local.citation.epage77
local.citation.spage72
local.citation.volume12
local.description.resumoIntroduction: this study used the comparison of basal cell carcinoma (BCC), squamous cell carcinoma of the skin (SCC) and actinic keratosis (AK) to test a new method for data set clustering in the leader gene approach. Methods: genes related to BCC, SCC and AK, were identified in the databases: OMIM, Genecards and NCBI Gene. A network was built for BCC, SCC and AK using STRING. For each gene, a weighted number of links (WNL) was calculated based on the combined STRING scores. The genes were then clustered according to their WNL and TIS, using an adaptation of particle swarm clustering (PSC) or K-means clustering. Results: a disagreement between K-means clustering and PSC was observed for both BCC and SCC. PSC suggested completed different leader genes to BCC and SCC. While K-means clustering indicated that CTNNB1 and TP53 were associated with BCC and SCC. In contrast, no differences in methods were observed to AK, which had the shorter network. TP53 was the only leader gene for AK. Conclusion: in conclusion, the current study suggests that PSC is an interesting tool for clustering genes in bioinformatics analyses of prevalent diseases. K-means clustering should be used in the small network. The current study also suggests TP53 may play a central role for AK. Additionally, CTNNB1 seems to be related to BCC, while CTNNA1 is related to SCC.
local.publisher.countryBrasil
local.publisher.departmentENG - DEPARTAMENTO DE ENGENHARIA ELETRÔNICA
local.publisher.departmentICA - INSTITUTO DE CIÊNCIAS AGRÁRIAS
local.publisher.initialsUFMG
local.url.externahttps://www.sciencedirect.com/science/article/pii/S2214540017300087

Arquivos

Licença do pacote

Agora exibindo 1 - 1 de 1
Imagem de Miniatura
Nome:
License.txt
Tamanho:
1.99 KB
Formato:
Plain Text
Descrição:
Baixar

Coleções

Artigo de Periódico

Logo UFMG