Author

Pedro Gabriel Nachtigall

Instituto ButantanORCID 0000-0002-3196-0173Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Research Focus:gene regulatory network inference· 2 Approach:statistical model· 2 Assay:ChIP-seq· 1 Approach:experimental assay· 1 Research Focus:genome assembly· 1 Assay:Hi-C· 1 Research Focus:spatial domain detection· 1

Frequent Co-Authors

Alan Mitchell DurhamiD· 1 shared Ana Paula C. A. LimaiD· 1 shared André Yoshiaki KashiwabaraiD· 1 shared Claudia RabuffoiD· 1 shared Danielle Bruno de CarvalhoiD· 1 shared David da Silva PiresiD· 1 shared Herbert Guimarães de Sousa SilvaiD· 1 shared Júlia Pinheiro Chagas da CunhaiD· 1 shared

Activity by Year

2019-2025 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 29 mutual co-author links

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1 shared paperBioinformatics

Alan Mitchell DurhamORCID

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2 papers

Recent·Most cited

GenomicsbioRxivPreprintSep 26, 2025

First Genome-Wide Centromere Map of Trypanosoma cruzi Reveals Linear and 3D Compartment Boundaries and Spatial Clustering

Natália Karla Bellini, Pedro Gabriel Nachtigall, Pedro Leonardo Carvalho de Lima…·Júlia Pinheiro Chagas da Cunha

The paper generates a high-quality genome assembly and centromere map for T. cruzi using Hi-C and ChIP-seq, revealing structural boundaries and 3D clustering of centromeres.

DOI 10.1101/2025.09.26.678825

Hi-CChIP-seq

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BioinformaticsbioRxivPreprintOct 7, 2019

CodAn: predictive models for the characterization of mRNA transcripts in Eukaryotes

Pedro Gabriel Nachtigall, André Yoshiaki Kashiwabara, Alan Mitchell Durham

CodAn improves CDS and UTR prediction in both strand-blind and partial sequences, enhancing accuracy and matching gold-standard results in strand-specific stop codon prediction.

DOI 10.1101/794107

statistical modelgene regulatory network inference

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