Desenvolvimento de um software bioinformático escrito em linguagem de programação Python para leitura e extração de informações de arquivos provenientes do Geocancerprognosticdatasetsretriever

Abstract

Bioinformatics is fundamental to understanding many different biological processes, especially at the molecular level. Therefore, this paper presents a search tool called geoCancerPrognosticDatasetsRetriever as a solution to reduce the difficulties researchers have in efficiently and quickly retrieving gene expression datasets linked to cancer prognosis, which are available in the GEO (Gene Expression Onminus) database. However, even though the tool does this optimization, the amount of information in each file is still very large, which makes manual processing difficult. To solve this problem, UNITE-1 (Understanding Novel Information Through Expression) was created to speed up the extraction of data that is mainly related to cancer prognosis from any file available in GEO, generating a new personalized file, solving another important problem faced by researchers who need to analyze gene expression data to compose their work with practicality, speed and efficiency. With the combination of these two tools, geoCancerPrognosticDatasetsRetriever (Perl) and UNITE-1 (Python), researchers can delve into data related to the prognosis of some type of cancer, efficiently and quickly, showing the potential not only to boost their scientific research, but also to facilitate the creation of new proposals to combat the disease.