Author

Sajad Tavakoli

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

Biology Disciplines

Click to filter author papers

Bioinformatics· 1

Signature Assays, Organisms & Methods

Click to filter · or open tag

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

Click any collaborator node to inspect or filter shared papers

Focal author (center)Selected co-authorORCID co-authorUnlinked name

Curved chords = mutual co-authorship

1 shared paperBioinformatics

Marjan MansourvarORCID

Mutual co-authors in cluster

Author profile →

1 paper

Recent·Most cited

BioinformaticsbioRxivPreprintOct 10, 2025

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.

DOI 10.1101/2025.10.10.681591

humanwhole-genome sequencing

𝕏 PostBluesky