Search Results - "de Melo, Filipe M"

Peptide R18H from BRN2 Transcription Factor POU Domain Displays Antitumor Activity In Vitro and In Vivo and Induces Apoptosis in B16F10-Nex2 Cells by da Cunha, Fernanda F M, Mugnol, Katia C U, de Melo, Filipe M, Nascimento, Marta V S Q, de Azevedo, Ricardo A, Santos, Raquel T S, Magalhães, Jéssica A, Miguel, Danilo C, Tada, Dayane B, Mortara, Renato A, Travassos, Luiz R, Arruda, Denise C

“…BRN2 transcription factor is associated with the development of malignant melanoma. The cytotoxic activities and cell death mechanism against B16F10-Nex2 cells…”
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Interleukin-6 and the Gut Microbiota Influence Melanoma Progression in Obese Mice by Pereira, Felipe V., Melo, Amanda C. L., Silva, Marina B., de Melo, Filipe M., Terra, Fernanda F., Castro, Iris A., Perandini, Luiz A., Miyagi, Marcelli T., Sato, Fabio T., Origassa, Clarice S. T., Hiyane, Meire I., Donato, Jose, Wasinski, Frederick, Araujo, Ronaldo C., Festuccia, William T. L., da Silva, Joao Santana, Camara, Niels Olsen S.

“…There is a strong correlation between obesity and cancer. Here, we investigated the influence of IL-6 and gut microbiota of obese mice in melanoma development…”
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Relational partitioning fuzzy clustering algorithms based on multiple dissimilarity matrices by de Carvalho, Francisco de A.T., Lechevallier, Yves, de Melo, Filipe M.

“…This paper introduces fuzzy clustering algorithms that can partition objects taking into account simultaneously their relational descriptions given by multiple…”
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Anti‐metastatic immunotherapy based on mucosal administration of flagellin and immunomodulatory P10 by Melo, Filipe M, Braga, Catarina JM, Pereira, Felipe V, Maricato, Juliana T, Origassa, Clarice ST, Souza, Mariana F, Melo, Amanda C, Silva, Priscila, Tomaz, Samanta L, Gimenes, Karina P, Scutti, Jorge AB, Juliano, Maria A, Zamboni, Dario S, Câmara, Niels O, Travassos, Luiz R, Ferreira, Luis CS, Rodrigues, Elaine G

“…Current therapies against malignant melanoma generally fail to increase survival in most patients, and immunotherapy is a promising approach as it could reduce…”
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TLR4-mediated immunomodulatory properties of the bacterial metalloprotease arazyme in preclinical tumor models by Pereira, Felipe V., Melo, Amanda C. L., de Melo, Filipe M., Mourão-Sá, Diego, Silva, Priscila, Berzaghi, Rodrigo, Herbozo, Carolina C. A., Coelho-dos-Reis, Jordana, Scutti, Jorge A., Origassa, Clarice S. T., Pereira, Rosana M., Juliano, Luis, Juliano, Maria Aparecida, Carmona, Adriana K., Câmara, Niels O. S., Tsuji, Moriya, Travassos, Luiz R., Rodrigues, Elaine G.

“…Despite the recent approval of new agents for metastatic melanoma, its treatment remains challenging. Moreover, few available immunotherapies induce a strong…”
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Partitioning hard clustering algorithms based on multiple dissimilarity matrices by de Carvalho, Francisco de A.T., Lechevallier, Yves, de Melo, Filipe M.

“…This paper introduces hard clustering algorithms that are able to partition objects taking into account simultaneously their relational descriptions given by…”
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A multi-view relational fuzzy c-medoid vectors clustering algorithm by de Carvalho, Francisco de A.T., de Melo, Filipe M., Lechevallier, Yves

“…This paper gives a multi-view relational fuzzy c-medoid vectors clustering algorithm that is able to partition objects taking into account simultaneously…”
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A Fuzzy C-Medoids Clustering Algorithm Based on Multiple Dissimilarity Matrices by de A T de Carvalho, Francisco, de Melo, Filipe M., Lechevallier, Yves

“…This paper gives a relational fuzzy c-medoids clustering algorithm that is able to partition objects taking into account simultaneously several dissimilarity…”
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A relational fuzzy c-means clustering algorithm based on multiple dissimilarity matrices by de Assis Tenorio de Carvalho, Francisco, de Melo, Filipe M, Lechevallier, Yves

“…This paper introduces a relational fuzzy c-means clustering algorithm that is able to partition objects taking into account simultaneously several…”
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Semi-supervised fuzzy c-medoids clustering algorithm with multiple prototype representation by de Melo, Filipe M., de Carvalho, Francisco De A. T.

“…Semi-supervised clustering is a special form of classification that uses a large amount of unlabeled data together with labeled data to achieve better…”
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