Author

Ricardo Z. N. Vêncio

Universidade de São PauloORCID 0000-0003-0425-7877Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Approach:statistical model· 2 Organism:bacteria (other)· 1 Assay:bulk RNA-seq· 1 Assay:DNA methylation· 1 Research Focus:gene regulatory network inference· 1 Approach:machine learning (classical)· 1 Assay:proteomics· 1

Frequent Co-Authors

Adrián López García de LomanaiD· 1 shared Alan P. R. LorenzettiiD· 1 shared Atlas KhaniD· 1 shared João Paulo P. de AlmeidaiD· 1 shared José Vicente Gomes‐FilhoiD· 1 shared Livia Soares ZaramelaiD· 1 shared M. A. S. FonsecaiD· 1 shared Nitin S. BaligaiD· 1 shared

Activity by Year

2017-2023 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 28 mutual co-author links

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1 shared paperSystems Biology

Adrián López García de LomanaORCID

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3 papers

Recent·Most cited

Systems BiologymSystemsPeer-reviewedMar 13, 2023

A genome-scale atlas reveals complex interplay of transcription and translation in an archaeon

Alan P. R. Lorenzetti, Ulrike Kusebauch, Livia Soares Zaramela…·Nitin S. Baliga

This study integrates omics data to reveal post-transcriptional regulation mechanisms in Halobacterium salinarum NRC-1, showing 54% of genes are regulated by multiple mechanisms and 7% show conditional regulation.

12 citations

DNA methylationproteomics

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BioinformaticsbioRxivPreprintJul 14, 2017

Intragenic differential expression in archaea transcriptomes revealed by computational analysis of tiling microarrays

Atlas Khan, Ricardo Z. N. Vêncio

DOI 10.1101/163436

statistical model

𝕏 PostBluesky

BioinformaticsbioRxivPreprintJun 23, 2017

In silico identification of non-coding RNAs in Halobacterium salinarum NRC-1 model archeon organism

M. A. S. Fonseca, Ricardo Z. N. Vêncio

The paper identifies 42 new non-coding RNAs in Halobacterium salinarum NRC-1 using machine learning models and data integration.

1 citation

bacteria (other)machine learning (classical)

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