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Type:	Artigo de Periódico
Title:	An adaptation of particle swarm clustering applied in basal cell carcinoma, squamous cell carcinoma of the skin and actinic keratosis
Authors:	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
Abstract:	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.
Subject:	Carcinoma basocelular Carcinoma de células escamosas Pele - Câncer Bioinformática Ceratose
language:	eng
metadata.dc.publisher.country:	Brasil
Publisher:	Universidade Federal de Minas Gerais
Publisher Initials:	UFMG
metadata.dc.publisher.department:	ENG - DEPARTAMENTO DE ENGENHARIA ELETRÔNICA ICA - INSTITUTO DE CIÊNCIAS AGRÁRIAS
Rights:	Acesso Restrito
metadata.dc.identifier.doi:	https://doi.org/10.1016/j.mgene.2017.01.007
URI:	http://hdl.handle.net/1843/61668
Issue Date:	Jun-2017
metadata.dc.url.externa:	https://www.sciencedirect.com/science/article/pii/S2214540017300087
metadata.dc.relation.ispartof:	Meta Gene
Appears in Collections:	Artigo de Periódico

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