Author

E. A. Noguera-Urbano

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Ecology· 3

Signature Assays, Organisms & Methods

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Research Focus:ecology & biodiversity· 2 Approach:deep learning· 1 Approach:machine learning (classical)· 1 Assay:metagenomics· 1 Approach:statistical model· 1

Frequent Co-Authors

J. Espinosa· 2 shared J. M. Ochoa· 2 shared R. Rios· 2 shared A. Diaz-Pulido· 1 shared B. Gomez-Valencia· 1 shared C. Soto· 1 shared J. M. Ochoa-Quintero· 1 shared L. E. Pardo· 1 shared

Activity by Year

2021-2023 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 24 mutual co-author links

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2 shared papersEcology

J. Espinosa

Mutual co-authors in cluster

Author profile →

3 papers

Recent·Most cited

EcologybioRxivPreprintFeb 27, 2023

Forest cover is more important than habitat integrity or landscape configuration in determining habitat use by mammals in a human-modified landscape in Colombia

L. E. Pardo, B. Gomez-Valencia, N. Deere…·J. M. Ochoa-Quintero

The paper assesses the impact of land-use changes on mammalian habitat use in Colombia, finding that forest cover is more important than habitat integrity or landscape configuration.

DOI 10.1101/2023.02.27.530271

statistical modelecology & biodiversity

𝕏 PostBluesky

EcologybioRxivPreprintSep 6, 2021

A supervised learning algorithm to evaluate occurrence records in virtual species

R. Rios, E. A. Noguera-Urbano, J. Espinosa, J. M. Ochoa

The paper develops a supervised learning algorithm to evaluate occurrence records of virtual species using simulated data and expert knowledge.

DOI 10.1101/2021.09.06.459158

metagenomicsdeep learning

𝕏 PostBluesky

EcologybioRxivPreprintSep 5, 2021

Machine learning techniques to derive bioclimatic classifications for Colombia

R. Rios, E. A. Noguera-Urbano, J. Espinosa, J. M. Ochoa

The paper applies machine learning to create two new bioclimatic classifications for Colombia by redefining Lang categories using logistic regression on precipitation data.

DOI 10.1101/2021.09.05.459033

machine learning (classical)

𝕏 PostBluesky