PhD. student,

Bioinformatics, PPGBIOINFO, Federal University of Rio Grande do Norte



Graduated in Biomedicine (Medical Technology) by Federal University of Rio Grande do Norte (2014). Master of Sciente in Biochemstry by Federal University of Rio Grande do Norte (2017) Currently student of PhD Degree on Bioinformatics, of Federal University of Rio Grande do Norte.

Project Abstract

Sepsis is the collective of clinical manifestations which depends on inflammatory response from the patient. After infection, the pathogenic agent triggers a immune response. This response may evolve to a hyperinflammatory state, depending on which cytokines are produced by the patient. The immune pattern will drive the response to different states, that may evolve to systemic shock, organ disfunction and severe sepsis. This problem is a matter of discussion, since there is few mollecular signatures that could help in identification of sepsis, this work intends to use systems biology tools to assess transcriptomic data related to sepsis. Using regulatory networks, our objective is to identify transcription masters regulators (MA) directly involved with sepsis response, and build the regulatory network of the genes related to sepsis response, using public databases. By using mutual information, we intend to infer correlations and coexpression patterns of thousand of genes. Taken together, this information could reveal which transcription factors potentially inflluence genic signatures, making possible infer causal relation between pathologic state and regulatory genes. This approach may assist in discovering new targets for prognostic and/or treatment.