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Long noncoding RNAs as potential biomarkers of arthritis

Grant number: 14/19323-7
Support type:Scholarships in Brazil - Scientific Initiation
Effective date (Start): November 01, 2014
Effective date (End): October 31, 2015
Field of knowledge:Biological Sciences - Biochemistry
Principal Investigator:Helder Takashi Imoto Nakaya
Grantee:Gustavo Rodrigues Ferreira
Home Institution: Faculdade de Ciências Farmacêuticas (FCF). Universidade de São Paulo (USP). São Paulo , SP, Brazil
Associated research grant:12/19278-6 - Systems biology of long non-coding RNAs, AP.JP

Abstract

Arthritis is an inflammatory disease whose molecular mechanisms are not yet fullyunderstood. Several microarray studies have been carried out in an attempt to clarify theregulatory pathways involved in it, and the generated data were uploaded to a public databank. Long non-coding RNAs play crucial roles in regulating gene expression in eukaryotes.Here we propose to analyze the available microarray data in order to assess the role oflncRNAs in arthritis. To this end, we will identify lncRNAs which are differentially expressedin arthritis and the gene modules to which they may regulate. The robustness of the resultswill be evaluated using independent arthritis studies not previously analyzed.

Scientific publications
(References retrieved automatically from Web of Science and SciELO through information on FAPESP grants and their corresponding numbers as mentioned in the publications by the authors)
FERREIRA, GUSTAVO RODRIGUES; NAKAYA, HELDER IMOTO; COSTA, LUCIANO DA FONTOURA. Gene regulatory and signaling networks exhibit distinct topological distributions of motifs. Physical Review E, v. 97, n. 4 APR 27 2018. Web of Science Citations: 0.
RUSSO, PEDRO S. T.; FERREIRA, GUSTAVO R.; CARDOZO, LUCAS E.; BUERGER, MATHEUS C.; ARIAS-CARRASCO, RAUL; MARUYAMA, SANDRA R.; HIRATA, THIAGO D. C.; LIMA, DIOGENES S.; PASSOS, FERNANDO M.; FUKUTANI, KIYOSHI F.; LEVER, MELISSA; SILVA, JOAO S.; MARACAJA-COUTINHO, VINICIUS; NAKAYA, HELDER I. CEMiTool: a Bioconductor package for performing comprehensive modular co-expression analyses. BMC Bioinformatics, v. 19, FEB 20 2018. Web of Science Citations: 12.

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