Author

Matthew Sinnott

Wellcome Sanger InstituteORCID 0000-0002-3054-7846Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Approach:statistical model· 3 Research Focus:benchmarking· 2 Organism:human· 2 Research Focus:variant calling· 2 Organism:bacteria (other)· 1 Approach:benchmark study· 1 Research Focus:deconvolution· 1 Assay:DNA methylation· 1

Frequent Co-Authors

Kevin HoweiD· 2 shared Abdoulaye Sadio· 1 shared Adrianne Lignes· 1 shared Albert Yao Kudakpo· 1 shared Alfred Amambua‐NgwaiD· 1 shared Ambroise Dioum AhouidiiD· 1 shared Andrea Frick-Kretschmer· 1 shared Andrew Mains· 1 shared

Activity by Year

2020-2026 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 31 mutual co-author links

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2 shared papersGenomics

Kevin HoweORCID

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Author profile →

3 papers

Recent·Most cited

GenomicsbioRxivPreprintFeb 23, 2026

Characterising recent antimalarial resistance in West Africa: Insights from amplicon sequencing of 17,384 Plasmodium falciparum infection samples

Joyce Mwongeli Ngoi, Eniyou Cheryll Oriero, Eyyüb S. Ünlü…·Lucas N. Amenga-Etego (16916177)

The paper analyzes amplicon sequencing data from 17,384 Plasmodium falciparum samples in West Africa to characterize antimalarial resistance patterns and their geographic distribution.

3 citations

humanDNA methylation

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GenomicsCell Reports MethodsPeer-reviewedNov 1, 2025

Benchmarking of Human ReadRemoval Strategies for Viral andMicrobial Metagenomics

Matthew Forbes, Duncan Y. K. Ng, Róisín M. Boggan…·Ewan M. Harrison

The paper benchmarks human read removal methods in metagenomics, finding that high-sensitivity Bowtie2 with T2T-CHM13 reference improves removal while preserving microbial data.

8 citations

humanvirus

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BioinformaticsStructurePeer-reviewedJun 11, 2020

Combining Information from Crosslinks and Monolinks in the Modelling of Protein Structures

Matthew Sinnott, Sony Malhotra, Mallur Srivatsan Madhusudhan…·Maya Topf

The paper introduces MoDS, a score for assessing protein structure models using monolink data, and shows combining it with MNXL improves model scoring, supporting the use of monolink data in integrative structure determination.

24 citations

proteomicsstatistical model

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