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De Pierri, C. R.

Publications and source records attributed to De Pierri, C. R..

2 recordsLinked to original sources

Biotext: Exploiting Biological-like format for text mining

The large amount of existing textual data justifies the development of new text mining tools. Bioinformatics tools can be brought to Text Mining, increasing the arsenal of resources. Here, we present BIOTEXT, a package of strategies for converting natural language text into biological-like information data, providing a general protocol with standardized functions, allowing to share, encode and decode textual data for amino acid and DNA. The package was used to encode the arbitrary information present in the headings of the biological sequences found in a BLAST survey. The protocol implemented in this study consists of 12 steps, which can be easily executed and/ or changed by the user, depending on the study area. BIOTEXT empowers users to perform text mining using bioinformatics tools. BIOTEXT is freely available at https://pypi.org/project/BIOTEXT/ (Python package) and https://sourceforge.net/projects/BIOTEXTtools/files/AMINOcode_GUI/ (Standalone tool).

bioinformatics↗

rSWeeP: A R/Bioconductor package deal with SWeeP sequences representation

The rSWeeP package is an R implementation of the SWeeP model, designed to handle Big Data. rSweeP meets to the growing demand for efficient methods of heuristic representation in the field of Bioinformatics, on platforms accessible to the entire scientific community. We explored the implementation of rSWeeP using a dataset containing 31,386 viral proteomes, performing phylogenetic and principal component analysis. As a case study we analyze the viral strains closest to the SARS-CoV, responsible for the current pandemic of COVID-19, confirming that rSWeeP can accurately classify organisms taxonomically. rSWeeP package is freely available at https://bioconductor.org/packages/release/bioc/html/rSWeeP.html.

bioinformatics↗