Author

Mariana Recamonde‐Mendoza

Universidade Federal do Rio Grande do SulORCID 0000-0003-2800-1032Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 1 Genetic & Genomic Medicine· 1 Genomics· 1

Signature Assays, Organisms & Methods

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Organism:human· 3 Approach:statistical model· 3 Research Focus:differential expression· 2 Research Focus:benchmarking· 1 Assay:bulk RNA-seq· 1 Research Focus:database / resource· 1 Approach:experimental assay· 1 Research Focus:variant calling· 1

Frequent Co-Authors

Rodrigo Haas BuenoiD· 2 shared Amanda G. LopesiD· 1 shared Andréia BioloiD· 1 shared Douglas dos Santos SoaresiD· 1 shared Felipe ColombelliiD· 1 shared Nadine ClauselliD· 1 shared Paola CarneiroiD· 1 shared Raquel Calloni· 1 shared

Activity by Year

2020-2025 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 24 mutual co-author links

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2 shared papersGenomics

Rodrigo Haas BuenoORCID

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3 papers

Recent·Most cited

GenomicsbioRxivPreprintFeb 15, 2025

Microarray, validation and gene-enrichment approach for assessing differentially expressed circulating miRNAs in obese and lean heart failure patients

Douglas dos Santos Soares, Amanda G. Lopes, Mariana Recamonde‐Mendoza…·Andréia Biolo

The paper identifies and validates differentially expressed circulating miRNAs in heart failure patients with and without obesity, finding three miRNAs upregulated in both groups and associated with biological processes related to HF.

DOI 10.1101/2025.02.15.638475

humanstatistical model

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BioinformaticsbioRxivPreprintJun 7, 2022

Pynoma, PyABraOM and BIOVARS: Towards genetic variant data acquisition and integration

Paola Carneiro, Felipe Colombelli, Mariana Recamonde‐Mendoza, Úrsula da Silveira Matte

The paper introduces three APIs for retrieving and integrating genetic variant data from genomic databases, demonstrating their use in a case study on ACE2, ADAM17, and TMPRSS2 genes.

DOI 10.1101/2022.06.07.495190

humanwhole-genome sequencing

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Genetic & Genomic MedicineMolecular Diagnosis & TherapyPeer-reviewedOct 23, 2020

Meta-analysis of Transcriptomic Data Reveals Pathophysiological Modules Involved with Atrial Fibrillation

Rodrigo Haas Bueno, Mariana Recamonde‐Mendoza

This study performs a meta-analysis of transcriptomic data to identify differentially expressed genes and functional modules associated with atrial fibrillation.

10 citations

humanbulk RNA-seq

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