Author

Jeroniza Nunes Marchaukoski

Universidade Federal do ParanáORCID 0000-0002-5176-7055Unclaimed ORCID profile · follow to get notified of new preprints

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Jeroniza Nunes Marchaukoski1 paper

Biology Disciplines

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Bioinformatics· 3

Signature Assays, Organisms & Methods

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Approach:statistical model· 3 Research Focus:benchmarking· 2 Organism:bacteria (other)· 1 Research Focus:clustering· 1 Research Focus:database / resource· 1 Approach:deep learning· 1 Assay:DNA methylation· 1 Research Focus:gene regulatory network inference· 1

Frequent Co-Authors

Roberto Tadeu RaittziD· 3 shared Camilla Reginatto De PierriiD· 2 shared Alexandre Quadros Lejambre· 1 shared Aryel Marlus Repula de Oliveira· 1 shared Bruno Thiago de Lima NichioiD· 1 shared Danrley R. Fernandes· 1 shared Dieval GuizeliniiD· 1 shared Diogo J. S. Machado· 1 shared

Activity by Year

2018-2020 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 30 mutual co-author links

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3 shared papersBioinformatics

Roberto Tadeu RaittzORCID

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3 papers

Recent·Most cited

BioinformaticsbioRxivPreprintSep 9, 2020

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

Danrley R. Fernandes, Mariane Gonçalves-Kulik, Diogo J. S. Machado…·Roberto Tadeu Raittz

The paper introduces rSWeeP, an R/Bioconductor package implementing the SWeeP model for efficient heuristic representation of Big Data, and demonstrates its use in phylogenetic and PCA analysis of viral proteomes.

1 citation

virusproteomics

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BioinformaticsBMC BioinformaticsPeer-reviewedJul 15, 2019

RAFTS3G - An efficient and versatile clustering software to analyses in large protein datasets

Bruno Thiago de Lima Nichio, Aryel Marlus Repula de Oliveira, Camilla Reginatto De Pierri…·Roberto Tadeu Raittz

RAFTS3G is a clustering tool for protein datasets that is faster than CD-HIT and better at detecting low-similarity homology.

6 citations

protein sequencestatistical model

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BioinformaticsbioRxivPreprintAug 17, 2018

The identification of DNA binding regions of the σ54 factor using artificial neural network

Leandro F. Moreno, Roberto Tadeu Raittz, Jeroniza Nunes Marchaukoski…·Liu Un Rigo

This study introduces a neural network model and tool to identify σ54 TFBSs with high sensitivity and specificity, enabling genome-wide analysis of σ54-regulated genes across bacterial species.

DOI 10.1101/393736

bacteria (other)DNA methylation

𝕏 PostBluesky