Author

Miguel P. Machado

University of LisbonORCID 0000-0002-1786-8522Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Approach:experimental assay· 3 Research Focus:software / tool· 2 Research Focus:variant calling· 2 Organism:bacteria (other)· 1 Assay:DNA methylation· 1 Research Focus:gene regulatory network inference· 1 Organism:human· 1 Assay:metagenomics· 1

Frequent Co-Authors

Diogo Nuno SilvaiD· 2 shared João André CarriçoiD· 2 shared Mário RamireziD· 2 shared Adriana TamiiD· 1 shared António Sebastião RodriguesiD· 1 shared Catarina Inês MendesiD· 1 shared Catarina SilvaiD· 1 shared Erley LizarazoiD· 1 shared

Activity by Year

2018-2022 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 25 mutual co-author links

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2 shared papersBioinformatics

Diogo Nuno SilvaORCID

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Author profile →

3 papers

Recent·Most cited

Whole human genome 5'-mC methylation analysis using long read nanopore sequencing

Catarina Silva, Miguel P. Machado, José Ferrão, António Sebastião Rodrigues, Luı́s Vieira

This study demonstrates that low coverage depth nanopore sequencing reliably captures 5-mC methylation patterns in the human genome, comparable to microarray and digital restriction enzyme analysis.

Epigenetics · Jul 20, 2022Peer-reviewedGenomics

DEN-IM: Dengue Virus identification from shotgun and targeted metagenomics

Catarina Inês Mendes, Erley Lizarazo, Miguel P. Machado, Diogo Nuno Silva, Adriana Tami, Mário Ramirez, Natacha Couto, John W. A. Rossen, João André Carriço

DEN-IM is a workflow for analyzing DENV sequencing data from shotgun and targeted metagenomics, enabling CDS inference, serotype/genotype identification, and phylogenetic tree generation.

bioRxiv · May 6, 2019 · PreprintBioinformatics

chewBBACA: A complete suite for gene-by-gene schema creation and strain identification

Mickael Silva, Miguel P. Machado, Diogo Nuno Silva, Mirko Rossi, Jacob Moran‐Gilad, Sérgio M. Santos, Mário Ramirez, João André Carriço

The paper introduces chewBBACA, a software suite for creating gene-by-gene schemas and identifying bacterial strains, offering scalable and open-source solutions for genomic epidemiology.

Microbial Genomics · Mar 1, 2018Peer-reviewedBioinformatics