Author

Patrik Waldmann

University of OuluORCID 0000-0003-2390-6609Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Approach:Bayesian inference· 1 Approach:matrix factorization· 1 Approach:statistical model· 1 Research Focus:variant calling· 1 Assay:whole-genome sequencing· 1

Frequent Co-Authors

Jon AhlinderiD· 2 shared

Activity by Year

2026-2026 · peak 2/yr

2 papers

Recent·Most cited

BioinformaticsbioRxivPreprintOct 11, 2026

Exploiting Low-Rank Structure in Genomic Relationship Matrices for Computationally Efficient Optimum Contribution Selection

Jon Ahlinder, Patrik Waldmann

This paper introduces a method to accelerate optimum contribution selection by approximating genomic relationship matrices with low-rank structures, achieving significant speedups while maintaining accuracy.

DOI 10.64898/2026.10.07.757325

whole-genome sequencingmatrix factorization

𝕏 PostBluesky

GeneticsGeneticsPeer-reviewedAug 3, 2026

Uncertainty-aware breeding decisions: MCMC-based optimum contribution selection increases breeding decision robustness

Jon Ahlinder, Patrik Waldmann

The paper introduces CVaR-OCS, a method that improves breeding decisions by incorporating uncertainty in genetic evaluations, leading to more robust selection outcomes.

DOI 10.1093/genetics/iyag205

statistical modelBayesian inference

𝕏 PostBluesky