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Author

Fabiana S. Paula

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Universidade de São PauloORCID 0000-0002-0010-1552Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Microbiology· 2

Signature Assays, Organisms & Methods

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Approach:machine learning (classical)· 2Assay:metagenomics· 2Research Focus:cell type annotation· 1Research Focus:clustering· 1

Frequent Co-Authors

Alice de Moura EmilioiD· 2 sharedAmanda Gonçalves BendiaiD· 2 sharedAugusto Miliorini AmendolaiD· 2 sharedCélio Roberto JönckiD· 2 sharedDaniel Leite MoreiraiD· 2 sharedDanilo Cândido VieiraiD· 2 sharedFrancielli Vilela PeresiD· 2 sharedFrederico Pereira BrandiniiD· 2 shared

Activity by Year

2026-2026 · peak 2/yr
0122026: 2 papers (click to filter)22026

Co-Author Collaboration Network

10 top collaborators · 45 mutual co-author links
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PaulaAlice de Moura Emilio · 2 shared papersEmilio · 2Amanda Gonçalves Bendia · 2 shared papersBendia · 2Augusto Miliorini Amendola · 2 shared papersAmendola · 2Célio Roberto Jönck · 2 shared papersJönck · 2Daniel Leite Moreira · 2 shared papersMoreira · 2Danilo Cândido Vieira · 2 shared papersVieira · 2Francielli Vilela Peres · 2 shared papersPeres · 2Frederico Pereira Brandini · 2 shared papersBrandini · 2Gustavo Fonseca · 2 shared papersFonseca · 2Júlio Cezar Fornazier Moreira · 2 shared papersMoreira · 2
Focal author (center)Selected co-authorORCID co-authorUnlinked name
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2 shared papersMicrobiology
Alice de Moura EmilioORCID

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2 papers

Recent·Most cited

Microbial signatures define the ecosystem functions of the pelagic microbiome in a basin-scale, Southwest Atlantic Ocean

Natascha Menezes Bergo, Francielli Vilela Peres, Danilo Cândido Vieira, Fluvio Mondolon, Júlio Cezar Fornazier Moreira, Rebeca Graciela Matheus Lizarraga, Renato Gamba Romano, Amanda Gonçalves Bendia, Leandro Nascimento Lemos, Alice de Moura Emilio, Augusto Miliorini Amendola, Diana Carolina Duque Castano, Mateus G. Chuqui, Fabiana S. Paula, William William Soares Gattaz Brandao, , Vivian H. Pellizari

The paper analyzes the pelagic microbiome of the Santos Basin using metagenomics and machine learning to identify microbial signatures and ecosystem functions shaped by local oceanographic processes.

Scientific Reports · Apr 22, 2026Peer-reviewedMicrobiology

A Machine Learning Approach Elucidates Spatial Patterns of Environmental Properties Driving Microbial Composition Over Santos Basin, South Atlantic

Júlio Cezar Fornazier Moreira, Flúvio Modolon, Natascha Menezes Bergo, Danilo Cândido Vieira, Gustavo Fonseca, Francielli Vilela Peres, Rebeca Graciela Matheus Lizarraga, Diana Carolina Duque Castaño, Alice de Moura Emilio, Augusto Miliorini Amendola, Renato Gamba Romano, Mateus G. Chuqui, Fabiana S. Paula, Daniel Leite Moreira, Célio Roberto Jönck, , Vivian H. Pellizari

This study uses machine learning to identify microbial assemblages in the Santos Basin, finding that environmental factors like temperature, salinity, and nutrients drive community structure across different depths.

FEMS Microbes · Jan 1, 2026Peer-reviewedMicrobiology