Author

Jurriaan H. Spaaks

Netherlands eScience CenterORCID 0000-0002-7064-4069Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Research Focus:benchmarking· 2 Assay:metagenomics· 2 Approach:deep learning· 1 Research Focus:software / tool· 1 Approach:statistical model· 1

Frequent Co-Authors

F. DibleniD· 2 shared Florian HuberiD· 2 shared Justin J. J. van der HooftiD· 2 shared Simon RogersiD· 2 shared Stefan VerhoeveniD· 2 shared Adam S. Z. BelloumiD· 1 shared Christiaan MeijeriD· 1 shared Cunliang GengiD· 1 shared

Activity by Year

2020-2021 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 45 mutual co-author links

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2 shared papersBioinformatics

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2 papers

Recent·Most cited

Spec2Vec: Improved mass spectral similarity scoring through learning of structural relationships

Florian Huber, Lars Ridder, Stefan Verhoeven, Jurriaan H. Spaaks, F. Diblen, Simon Rogers, Justin J. J. van der Hooft

Spec2Vec improves spectral similarity scoring by learning fragmental relationships, showing better correlation with structural similarity than cosine-based scores in metabolomics analyses.

PLoS Computational Biology · Feb 16, 2021Peer-reviewedBioinformatics

matchms - processing and similarity evaluation of mass spectrometry data

Florian Huber, Stefan Verhoeven, Christiaan Meijer, Hanno Spreeuw, Efraín Manuel Villanueva Castilla, Cunliang Geng, Justin J. J. van der Hooft, Simon Rogers, Adam S. Z. Belloum, F. Diblen, Jurriaan H. Spaaks

The paper introduces matchms, a tool for processing and evaluating similarity in mass spectrometry data, addressing challenges in dataset consistency and metadata quality.

The Journal of Open Source Software · Aug 31, 2020Peer-reviewedBioinformatics