Pedro Igor Câmara de Oliveira

Pedro Igor Câmara de Oliveira

MSc. student,

Bioinformatics, PPGBIOINFO, Federal University of Rio Grande do Norte

E-mail:

Lattes: http://lattes.cnpq.br/0897489508458779

Pedro is a pharmacist graduated in 2015 at Universidade Federal do Rio Grande do Norte (UFRN). He is currently pursuing a Master of Science degree in Bioinformatics at PPGBIOINFO - UFRN. He is planning on a rational approach to develop new drugs for Chagas' disease treatment.

Project Abstract

Marcel da Câmara Ribeiro Dantas

Marcel da Câmara Ribeiro Dantas

MSc. student,

Bioinformatics, PPGBIOINFO, Federal University of Rio Grande do Norte

E-mail: mribeirodantas@lais.huol.ufrn.br

Lattes: http://lattes.cnpq.br/1623821220022021

 

Marcel is a Computer Engineer with an automation and computer engineering degree obtained from Universidade Federal do Rio Grande do Norte, with over six years of experience in health informatics and biomedical engineering as a researcher at the Laboratory for Technological Innovation in Healthcare. He is currently pursuing a Master of Science degree in Bioinformatics at PPGBIOINFO-UFRN, studying transcriptional regulatory networks in Ewing's Sarcoma under the supervision of PhD. Prof. Rodrigo Dalmolin.

His latest cancer related papers published were:
Computer-aided detection (CADe) and diagnosis (CADx) system for lung cancer with likelihood of malignancy.
Computer-aided detection system for lung cancer in computed tomography scans: Review and future prospects.

Project Abstract

Diego Arthur de Azevedo Morais

Diego Arthur de Azevedo Morais

MSc. student,

Bioinformatics, PPGBIOINFO, Federal University of Rio Grande do Norte

E-mail: arthurvinx@gmail.com

Lattes: http://lattes.cnpq.br/0627546477822130

 

Diego is a computer scientist, he obtained his bachelor's degree from Universidade do Estado do Rio Grande do Norte in 2012, and concluded a specialization course, lato sensu, in computer forensics at Universidade Potiguar in 2017. He is currently pursuing a master's degree in bioinformatics, at PPGBIOINFO-UFRN, researching transcriptional analysis and developing a R package to support his research group.

Project Abstract

Thayna Nhaara Oliveira Damasceno

Thayna Nhaara Oliveira Damasceno

MSc. student, Bioinformatics, PPGBIOINFO, Federal University of Rio Grande do Norte E-mail:  thaynanhaara@hotmail.com Lattes: http://lattes.cnpq.br/1258656274876050
Nurse graduated at the Federal University of Rio Grande do Norte - UFRN
Specialist in ICU from CENPEX - RN.
Student of the Master in Bioinformatics by the Federal University of Rio Grande do Norte - UFRN
Technical student of electronic from the technical course - Metrópole Digital - UFRN.

Projetct Abstract

With the advancement of technology and information systems, and the increasing technological innovation, the health industry closely followed the growth of data available on health, looking for ways to provide better assistance to their patients, with the aim of improving public health.
This research aims to develop a tool that allows to analyze the clinical status of patients without the need to search on repositories of existing data. Currently, such information can be obtained using tools you already have registered data, thus, the analysis of the patient becomes dependent on these repositories. For this reason, the proposal provides greater flexibility in this regard.
Priscilla Machado do Nascimento

Priscilla Machado do Nascimento

MSc. student,

Bioinformatic, PPGBIOINFO, Federal University of Rio Grande do Norte

E-mail: priscilla.machado@ufrn.edu.br, priscillamnas@gmail.com

Lattes: http://lattes.cnpq.br/3621071310427601

Masters student at the postgraduate of bioinformatics program in the Federal University of Rio Grande do Norte, graduated in Systems Analysis and Development by the Federal Institute of Education, Science and Technology of Rio Grande do Norte (2015). Has experience in Computer Science, with an emphasis on programming, Web development languages and bioinformatics.

Projetct Abstract

The current scientific advances within the genomics, have been provided due to extraction of meaningful information from the DNA because of the use of new technologies available to perform the analysis of genetic data. Precision medicine makes use of these advances to better understand the complex biological mechanism and the possible changes that might come to produce disease in an individual. My work aims the development of a software product responsible for providing assistance to the collected genetic data in order to use them efficiently in the analysis and display so they can be applied studies on such data. In this sense, also allowing the application of data collected in public databases, the work aims to assist in the treatment of individuals who have some genetic changes that went previously identified by the system. The aims of this project are develop a product capable of: to facilitate the use of public genetic data collected, store the results of the tests already carried out and detect patterns that help in the diagnosis to be presented.
Laise Cavalcanti Florentino

Laise Cavalcanti Florentino

MSc. student,

Bioinformatics, PPGBIOINFO, Federal University of Rio Grande do Norte

E-mail: l.unifolie@gmail.com, laisecf@ufrn.edu.br

Lattes: http://lattes.cnpq.br/8881925073912858

Masters student in Bioinformatics at the Universidade Federal do Rio Grande do Norte - UFRN. Graduated in Computer Science by the Universidade Federal de Campina Grande - UFCG.

Projetct Abstract

Structural consequences of SNPs associated to cancer

Each individual has distinct patterns of SNPs spread across their genome. Understanding these profiles is important to identify different responses to drugs and treatments. Furthermore, pontual mutations are well known to trigger human cancers, by means of affecting genomic sequence and their products, like proteins, in a chemical point of view. However, mutational impact on protein structure has not yet been systematically analyzed. To join efforts in this way, the objective of this project is to identify the real structural effect of SNPs related to certain types of cancer. That is, to identify SNPs in known “druggable” structures and to characterize structural consequences of variation. So, if the mutation alters the structure of the drug binding region to the target, to search drugs and others chemical compounds that will dock with mutated proteins.
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