Author

S. Derkarabetian

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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Evolutionary Biology· 3

Signature Assays, Organisms & Methods

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Research Focus:cell type annotation· 2 Assay:DNA methylation· 2 Approach:machine learning (classical)· 2 Research Focus:clustering· 1 Research Focus:database / resource· 1 Research Focus:differential expression· 1 Approach:experimental assay· 1 Research Focus:gene regulatory network inference· 1

Frequent Co-Authors

M. Hedin· 2 shared G. Giribet· 1 shared J. C. Geburzi· 1 shared J. Starrett· 1 shared P. C. Rodriguez Flores· 1 shared P. K. Koo· 1 shared S. Castillo· 1 shared S. Ovchinnikov· 1 shared

Activity by Year

2018-2023 · peak 1/yr

Co-Author Collaboration Network

8 top collaborators · 10 mutual co-author links

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2 shared papersEvolutionary Biology

M. Hedin

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Author profile →

3 papers

Recent·Most cited

From the shallows to the depths: A new probe set to target ultraconserved elements for Malacostraca

J. C. Geburzi, P. C. Rodriguez Flores, S. Derkarabetian, G. Giribet

The paper introduces a new UCE probe set for Malacostraca, demonstrating its effectiveness in recovering UCEs from diverse crustacean species and historical specimens.

bioRxiv · Jun 30, 2023 · PreprintEvolutionary Biology

The challenge of delimiting cryptic species, and a supervised machine learning solution

S. Derkarabetian, J. Starrett, M. Hedin

The paper addresses the challenge of delimiting cryptic species by introducing a supervised machine learning approach that uses a custom training dataset derived from a well-studied lineage.

bioRxiv · Aug 5, 2021 · PreprintEvolutionary Biology

An Empirical Demonstration of Unsupervised Machine Learning in Species Delimitation

S. Derkarabetian, S. Castillo, P. K. Koo, S. Ovchinnikov, M. Hedin

This study demonstrates that unsupervised machine learning methods can effectively identify species-level divergences in genetic data, outperforming traditional model-based approaches in avoiding over-splitting species.

bioRxiv · Sep 28, 2018Evolutionary Biology