Ferramenta de extração de características de sequências biológicas

Abstract

Bioinformatics is an area of science that seeks to analyze, interpret and solve biological pro- blems. In the analysis, an exploratory data analysis allows you to visualize and have a greater understanding of the data. For example, graphical or tabular representations are friendly ways of having this vision. In this sense, this TCC presents the final result of the construction of a Desktop tool for exploratory analysis of biological sequences, appealing for visualization of this data. The tool was developed in Python, which allows generating reports to view the results. Nine characteristics were implemented, namely: sequence size, GC content and GC ratio, k-mer count (ex: dinucleotides and trinucleotides), Dinucleotide-based Auto Covarience, Dinucleotide- based Cross Covarience, Trinucleotide-based Auto Covarience and Trinucleotide-based Cross Covarience. Thus, libraries such as Biopython, Numpy, Tkinter and Matplotlib, were used in the construction of the analysis of biological sequences and creation of graphics, through an intuitive and usual interface. Finally, it is a user-friendly tool in which the user can insert the sequence and export his reports and graphs in various formats to be used in his scientific works.