Author

Xuechun Xu

KTH Royal Institute of TechnologyORCID 0000-0003-1850-0946Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 1 Systems Biology· 1

Signature Assays, Organisms & Methods

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Approach:statistical model· 2 Research Focus:benchmarking· 1 Approach:deep learning· 1 Organism:E. coli· 1 Assay:long-read sequencing· 1 Approach:machine learning (classical)· 1 Research Focus:software / tool· 1 Research Focus:variant calling· 1

Frequent Co-Authors

Avlant NilssoniD· 1 shared Douglas A. LauffenburgeriD· 1 shared Hratch BaghdassarianiD· 1 shared Joakim JaldéniD· 1 shared Nayanika BhallaiD· 1 shared Olof NordenstormiD· 1 shared Patrik L. StåhliD· 1 shared

Activity by Year

2023-2026 · peak 1/yr

Co-Author Collaboration Network

7 top collaborators · 9 mutual co-author links

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1 shared paperSystems Biology

Avlant NilssonORCID

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2 papers

Recent·Most cited

Systems BiologyBioinformaticsPeer-reviewedJul 24, 2026

Biologically informed neural network models are robust to spurious interactions via self-pruning

Olof Nordenstorm, Hratch Baghdassarian, Xuechun Xu…·Avlant Nilsson

This paper introduces a method to evaluate the robustness of biology-informed neural networks by measuring their ability to prune spurious interactions during training.

2 citations

deep learningstatistical model

𝕏 PostBluesky

BioinformaticsBMC BioinformaticsPeer-reviewedDec 7, 2023

Lokatt: A hybrid DNA nanopore basecaller with an explicit duration hidden Markov model and a residual LSTM network

Xuechun Xu, Nayanika Bhalla, Patrik L. Ståhl, Joakim Jaldén

Lokatt improves nanopore basecalling by combining an explicit duration HMM with a residual LSTM, achieving high accuracy and coverage on E. coli data.

10 citations

E. colilong-read sequencing

𝕏 PostBluesky