Author

T. Kuzmina

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

Biology Disciplines

Click to filter author papers

Ecology· 2

Signature Assays, Organisms & Methods

Click to filter · or open tag

Approach:statistical model· 2 Research Focus:benchmarking· 1 Research Focus:cell type annotation· 1 Research Focus:clustering· 1 Research Focus:differential expression· 1 Research Focus:ecology & biodiversity· 1 Approach:experimental assay· 1 Organism:human· 1

Frequent Co-Authors

G. Salle· 2 shared M. Basiaga· 2 shared M. Boisseau· 2 shared N. Mach· 2 shared A. Gesbert· 1 shared C. Kuchly· 1 shared C. Laugier· 1 shared D. Serreau· 1 shared

Activity by Year

2021-2022 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 40 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

G. Salle

Mutual co-authors in cluster

Author profile →

2 papers

Recent·Most cited

Evaluation of the nemabiome approach for the study of equine strongylid communities

E. Courtot, M. Boisseau, S. Dhorne-Pollet, D. Serreau, A. Gesbert, F. Reigner, M. Basiaga, T. Kuzmina, J. Lluch, G. Annonay, C. Kuchly, I. Diekmann, J. Krücken, G. von Samson-Himmelstjerna, N. Mach, G. Salle

This study evaluates the nemabiome approach for equine strongylid species identification using ITS-2 and a new COI barcode, finding COI less effective due to amplification biases and lower sensitivity.

bioRxiv · Jul 22, 2022 · PreprintEcology

Species turnover between age groups of horses and positive network of co-occurrences define the structure of horse strongylid communities: a meta-analysis

M. Boisseau, N. Mach, M. Basiaga, S. Kornas, T. Kuzmina, C. Laugier, G. Salle

This study analyzes horse strongylid communities using a meta-analysis to identify factors shaping their diversity and structure, finding that species turnover between age groups and positive co-occurrence networks are key.

bioRxiv · May 17, 2021 · PreprintEcology