Author

Finn Lindgren

University of EdinburghORCID 0000-0002-5833-2011Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Approach:statistical model· 4 Research Focus:variant calling· 2 Research Focus:benchmarking· 1 Research Focus:genome assembly· 1 Assay:imaging· 1 Organism:multiple species· 1 Research Focus:spatial domain detection· 1 Assay:spatial transcriptomics· 1

Frequent Co-Authors

Gregor GorjanciD· 3 shared Ivan PocrnićiD· 2 shared Alfredo Rodrigues· 1 shared Appolinaire DjikengiD· 1 shared Athumani Shabani NgulumaiD· 1 shared Chinyere Charlotte Ekine-DzivenuiD· 1 shared Daniel J. TolhurstiD· 1 shared Eva Lavrencic· 1 shared

Activity by Year

2020-2026 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 20 mutual co-author links

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3 shared papersGenomics

Gregor GorjancORCID

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Author profile →

4 papers

Recent·Most cited

Spatial modelling improves genomic evaluation in Tanzanian smallholder admixed dairy cattle

Isidore Houaga, Raphael Mrode, Julie M.K. Ojango, Chinyere Charlotte Ekine-Dzivenu, Mwai A. Okeyo, Zabron Cuthibert Nziku, Athumani Shabani Nguluma, Eva Lavrencic, Finn Lindgren, Ivan Pocrnić, Appolinaire Djikeng, Gregor Gorjanc

This paper improves genomic evaluation in Tanzanian smallholder dairy cattle by incorporating spatial modelling to better separate genetic and environmental effects.

Genetics Selection Evolution · Jan 21, 2026Peer-reviewedGenomics

Data integration with uneven spatiotemporal coverage: A point-process approach for dynamic species distribution models

Moritz Klaassen, Marc Fernández, Finn Lindgren, Virginia Morera‐Pujol, Len Thomas, N. Oliveira, Joana Castro, Francisco Martinho, Sara Magalhães, Alfredo Rodrigues, Maria Martins, Filipe Alves, Tiago André Marques

This paper integrates structured and opportunistic species distribution data using a spatiotemporal model to improve predictions for mobile species.

bioRxiv · Nov 7, 2025 · PreprintEcology

Optimisation of the core subset for the APY approximation of genomic relationships

Ivan Pocrnić, Finn Lindgren, Daniel J. Tolhurst, William O. Herring, Gregor Gorjanc

The paper optimizes the core subset selection in the APY approximation to improve stability and repeatability of genomic predictions.

Genetics Selection Evolution · Nov 22, 2022Peer-reviewedGenetics

Hierarchical modeling of haplotype effects based on a phylogeny

Maria Lie Selle, Ingelin Steinsland, Finn Lindgren, Vladimir Brajković, Vlatka Čubrić-Ćurik, Gregor Gorjanc

This paper introduces a hierarchical model to estimate haplotype effects using phylogenetic relationships, showing improved estimates with sparse modeling and better performance in low-observation scenarios.

bioRxiv · Jan 31, 2020 · PreprintGenomics