Author

Sebastián Michel-Mata

Princeton UniversityORCID 0000-0003-3424-6669Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

Click to filter author papers

Signature Assays, Organisms & Methods

Click to filter · or open tag

Research Focus:benchmarking· 1 Approach:deep learning· 1 Organism:Drosophila· 1 Research Focus:ecology & biodiversity· 1 Organism:human· 1 Assay:metagenomics· 1 Organism:mouse· 1 Approach:statistical model· 1

Frequent Co-Authors

Marco Tulio AnguloiD· 2 shared Jorge X. Velasco‐HernándeziD· 1 shared Pablo A. MarquetiD· 1 shared Serguei SaavedraiD· 1 shared Xu‐Wen WangiD· 1 shared Yang‐Yu LiuiD· 1 shared

Activity by Year

2022-2025 · peak 1/yr

Co-Author Collaboration Network

6 top collaborators · 9 mutual co-author links

Click any collaborator node to inspect or filter shared papers

Focal author (center)Selected co-authorORCID co-authorUnlinked name

Curved chords = mutual co-authorship

2 shared papersEcology

Marco Tulio AnguloORCID

Mutual co-authors in cluster

Author profile →

2 papers

Recent·Most cited

EcologybioRxivPreprintJun 13, 2025

A general allometric rule predicts sustainable growth across societies

Marco Tulio Angulo, Sebastián Michel-Mata, Jorge X. Velasco‐Hernández…·Pablo A. Marquet

The paper derives a general sustainability rule using allometric scaling laws and tests it against ethnographic data from hunter-gatherer societies, finding consistent alignment with predicted sustainability corridors.

DOI 10.1101/2025.06.13.659593

statistical modelecology & biodiversity

𝕏 PostBluesky

Systems BiologyiMetaPeer-reviewedMar 1, 2022

Predicting microbiome compositions from species assemblages through deep learning.

Sebastián Michel-Mata, Xu‐Wen Wang, Yang‐Yu Liu, Marco Tulio Angulo

The paper introduces a deep learning framework to predict microbial community compositions from species assemblages using synthetic and experimental data.

49 citationstop 3%

humanDrosophila

𝕏 PostBluesky