Author

Sajad Tavakoli

Technical University of DenmarkORCID 0000-0002-0510-6491Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 1

Signature Assays, Organisms & Methods

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Approach:deep learning· 1 Organism:human· 1 Research Focus:variant calling· 1 Assay:whole-genome sequencing· 1

Frequent Co-Authors

Marjan MansourvariD· 1 shared Rasmus John Normand FrandseniD· 1 shared Sina MajidianiD· 1 shared

Activity by Year

2025-2025 · peak 1/yr

Co-Author Collaboration Network

3 top collaborators · 3 mutual co-author links

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1 shared paperBioinformatics

Marjan MansourvarORCID

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1 paper

Recent·Most cited

Accurate and Robust Characterization of Structural Variants at Low Coverages with ARCLID

Sajad Tavakoli, Rasmus John Normand Frandsen, Sina Majidian, Marjan Mansourvar

ARCLID is a deep learning-based structural variant caller that achieves high accuracy at low sequencing coverages, outperforming existing tools and enabling cost-effective SV discovery.

bioRxiv · Oct 10, 2025 · PreprintBioinformatics