Author

Mike Vella

Oxford Nanopore Technologies (United Kingdom)

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Bioinformatics· 3

Signature Assays, Organisms & Methods

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Assay:whole-genome sequencing· 3 Research Focus:genome assembly· 2 Organism:human· 2 Approach:statistical model· 2 Research Focus:benchmarking· 1 Approach:experimental assay· 1 Organism:plant (other)· 1 Research Focus:variant calling· 1

Frequent Co-Authors

Katherine R. Lawrence· 2 shared Adam M. PhillippyiD· 1 shared Alexander H. J. WittenbergiD· 1 shared Ammal AbbasiiD· 1 shared Andrea GuarracinoiD· 1 shared Andreas J GruberiD· 1 shared Arang RhieiD· 1 shared Azhar KhandekariD· 1 shared

Activity by Year

2022-2026 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 21 mutual co-author links

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2 shared papersBioinformatics

Katherine R. Lawrence

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3 papers

Recent·Most cited

Efficient near telomere-to-telomere assembly of Nanopore Simplex reads

Haoyu Cheng, Han Qu, Sean K. McKenzie, Katherine R. Lawrence, Rhydian Windsor, Mike Vella, Peter J. Park, Heng Li

The paper introduces hifiasm (ONT), an algorithm that enables near telomere-to-telomere genome assembly using standard ONT Simplex reads, reducing computational demands and improving chromosome reconstruction.

Nature · Feb 4, 2026Peer-reviewedBioinformatics

Gapless assembly of complete human and plant chromosomes using only nanopore sequencing

Sergey Koren, Zhigui Bao, Andrea Guarracino, Shujun Ou, Sara Goodwin, Katharine M. Jenike, Julian Lucas, Brandy McNulty, Jimin Park, Mikko Rautiainen, Arang Rhie, Dick Roelofs, Harrie Schneiders, Ilse Vrijenhoek, Koen Nijbroek, , Adam M. Phillippy

This paper demonstrates that ONT Duplex sequencing combined with Pore-C data can assemble complete, high-quality human and plant chromosomes with base accuracy over 99.999%.

Genome Research · Nov 1, 2024Peer-reviewedBioinformatics

Uncovering novel mutational signatures by de novo extraction with SigProfilerExtractor

S. M. Ashiqul Islam, Marcos Díaz‐Gay, Yang Wu, Mark D. Barnes, Raviteja Vangara, Erik N. Bergstrom, Yudou He, Mike Vella, Jingwei Wang, Jon W. Teague, Peter Clapham, Sarah Moody, Sergey Senkin, Yun Rose Li, Laura Riva, , Ludmil B. Alexandrov

SigProfilerExtractor is a tool for de novo mutational signature extraction that outperforms existing methods and identifies four novel signatures, including one linked to tobacco smoking.

Cell Genomics · Sep 23, 2022Peer-reviewedBioinformatics