Author

Marah Stoldt

Johannes Gutenberg University MainzORCID 0000-0003-2410-4413Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 1 Evolutionary Biology· 1

Signature Assays, Organisms & Methods

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Research Focus:gene regulatory network inference· 2 Research Focus:chromatin & epigenetic regulation· 1 Approach:comparative / phylogenetic analysis· 1 Research Focus:development & morphogenesis· 1 Organism:Drosophila· 1 Approach:machine learning (classical)· 1 Organism:mouse· 1 Organism:multiple species· 1

Frequent Co-Authors

Susanne FoitzikiD· 2 shared Alice C. SéguretiD· 1 shared Anna GrandchampiD· 1 shared Barbara FeldmeyeriD· 1 shared Carlotta MartelliiD· 1 shared Christopher FinkeiD· 1 shared Erich Bornberg‐BaueriD· 1 shared Evelien JongepieriD· 1 shared

Activity by Year

2021-2024 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 31 mutual co-author links

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2 shared papersEvolutionary Biology

Susanne FoitzikORCID

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2 papers

Recent·Most cited

Evolutionary BiologybioRxivPreprintDec 31, 2024

Convergent Evolutionary Traces of Genomic Innovations and Depletions in Socially Parasitic Ants

Mark C. Harrison, Alice C. Séguret, Christopher Finke…·Barbara Feldmeyer

This study identifies convergent genomic changes in socially parasitic ants, showing gene loss, innovation, and network rewiring in parasites compared to hosts.

2 citations

multiple specieswhole-genome sequencing

𝕏 PostBluesky

BioinformaticsbioRxivPreprintDec 10, 2021

Identification of functional residues using machine learning provides insights into the evolution of odorant receptor gene families in solitary and social insects

Pablo Mier, Jean−Fred Fontaine, Marah Stoldt…·Miguel Angel Andrade-Navarro

The paper uses machine learning to identify functional residues in odorant receptors across insect species, revealing conservation patterns linked to social behavior.

DOI 10.1101/2021.12.10.472060

Drosophilamouse

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