Clovis Ferreira dos Reis

Clovis Ferreira dos Reis

PhD. student,

Bioinformatics, PPGBIOINFO, Federal University of Rio Grande do Norte

E-mail: cfreis@ufrn.edu.br

Lattes: http://lattes.cnpq.br/5487049518249525

Projetct Abstract

Micro-organisms are the most numerous group in the planetary biome. With the cheapening of sequencing process an tecnologies, the metagenomical databases starts to grow up faster than those microbiome's information can be analised and interpreted. New tecnologies and process must to be developed to process rapidly an efficiently. In this context this project will develop bioinformatic tools to analise and show the systemic metabolic interactions beteween genes and their products into a soil metagenome.
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.
Karla Cristina Tabosa Machado

Karla Cristina Tabosa Machado

MSc. student,

Bioinformatics, PPGBIOINFO, Federal University of Rio Grande do Norte

E-mail: karlactabosa@gmail.com

Lattes: http://lattes.cnpq.br/3371348709222085

Graduated in Computer Science (2016) at the Federal University of Paraíba - UFPB

Project Abstract

Development of computational approaches for the analysis of proteomic data.

Protein analysis by mass spectrometry (MS) went through big technological improvements in the past decade, in a manner almost similar to developments in genomic research. However, the development of computational approaches targeting analysis of MS data lagged behind. This is particularly relevant regarding meta-analysis, i.e., the combined analysis of MS data collected independently by different research groups. Such type of analysis is relevant because, while data collected for a specific project can fulfill only narrow objectives (for example, a project studying membrane fractions from a cell of the immune system), meta-analysis can explore wider questions (using the same example above, the analysis of many datasets where different fractionation methods were used can help to evaluate and optimize the efficiency of such methods). The worst bottleneck on this type of analysis is how to handle the normalization of the data that was collected by different groups using unique instruments and approaches. This raises the need for computational tools using mathematical approaches that will allow for that. Therefore, the main aim of this project is to employ computational biology in the proteomics field, being able to normalize and compare samples collected independently and which can be applied to several topics.
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