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http://hdl.handle.net/1843/61668| Tipo: | Artigo de Periódico |
| Título: | An adaptation of particle swarm clustering applied in basal cell carcinoma, squamous cell carcinoma of the skin and actinic keratosis |
| Autor(es): | Fabiano de Oliveira Poswar Laércio Ives Santos Lucyana Conceição Farias Talita Antunes Guimarães Sérgio Henrique Sousa Santos Kimberly Marie Jones Alfredo Maurício Batista de Paula Reinaldo Martinez Palhares Marcos Flávio Silveira Vasconcelos D'Angelo André Luiz Sena Guimarães |
| Resumen: | Introduction: 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. |
| Asunto: | Carcinoma basocelular Carcinoma de células escamosas Pele - Câncer Bioinformática Ceratose |
| Idioma: | eng |
| País: | Brasil |
| Editor: | Universidade Federal de Minas Gerais |
| Sigla da Institución: | UFMG |
| Departamento: | ENG - DEPARTAMENTO DE ENGENHARIA ELETRÔNICA ICA - INSTITUTO DE CIÊNCIAS AGRÁRIAS |
| Tipo de acceso: | Acesso Restrito |
| Identificador DOI: | https://doi.org/10.1016/j.mgene.2017.01.007 |
| URI: | http://hdl.handle.net/1843/61668 |
| Fecha del documento: | jun-2017 |
| metadata.dc.url.externa: | https://www.sciencedirect.com/science/article/pii/S2214540017300087 |
| metadata.dc.relation.ispartof: | Meta Gene |
| Aparece en las colecciones: | Artigo de Periódico |
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