Author

R. J. G. Pimenta

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Plant Biology· 3

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Research Focus:gene regulatory network inference· 3 Approach:machine learning (classical)· 3 Assay:bulk RNA-seq· 2 Approach:statistical model· 2 Research Focus:variant calling· 2 Research Focus:cell type annotation· 1 Research Focus:differential expression· 1 Organism:plant (other)· 1

Frequent Co-Authors

A. H. Aono· 3 shared A. P. de Souza· 3 shared L. R. Pinto· 2 shared M. C. Goncalves· 2 shared M. G. d. A. Landell· 2 shared A. E. Coutinho· 1 shared C. C. da Silva· 1 shared C. M. d. S. Dambroz· 1 shared

Activity by Year

2020-2022 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 33 mutual co-author links

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3 shared papersPlant Biology

A. H. Aono

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3 papers

Recent·Most cited

Plant BiologybioRxivAug 18, 2022

Multiomic investigation of sugarcane mosaic virus resistance in sugarcane

R. J. G. Pimenta, A. H. Aono, R. C. V. Burbano…·A. P. de Souza

This study identifies SNPs associated with sugarcane mosaic virus resistance using GWAS and machine learning, and annotates markers to uncover biological processes involved in resistance.

DOI 10.1016/j.cj.2023.06.009

bulk RNA-seqmachine learning (classical)

𝕏 PostBluesky

Plant BiologybioRxivAug 5, 2022

Genome-wide characterization of the common bean kinome: catalog and insights into expression patterns and genetic organization

A. H. Aono, R. J. G. Pimenta, C. M. d. S. Dambroz…·W. A. Pereira

The paper characterizes the common bean kinome, identifying 1,203 PKs and analyzing their classification, distribution, structure, and expression patterns using RNA-Sequencing data.

DOI 10.1016/j.gene.2022.147127

plant (other)bulk RNA-seq

𝕏 PostBluesky

Plant BiologybioRxivSep 4, 2020

Genome-wide approaches for the identification of markers and genes associated with sugarcane yellow leaf virus resistance

R. J. G. Pimenta, A. H. Aono, R. C. B. Villavicencio…·A. P. de Souza

The paper identifies markers and genes associated with sugarcane yellow leaf virus resistance using genome-wide association analyses and machine learning.

DOI 10.1038/s41598-021-95116-1

whole-genome sequencingmachine learning (classical)

𝕏 PostBluesky