Author

Klaas Wynne

University of GlasgowORCID 0000-0002-5305-5940Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Approach:machine learning (classical)· 3 Research Focus:benchmarking· 1 Approach:deep learning· 1 Organism:Drosophila· 1

Frequent Co-Authors

Mario González‐JiméneziD· 3 shared Doreen Josen SiriaiD· 2 shared Francesco BaldiniiD· 2 shared Fredros O. OkumuiD· 2 shared Simon A. BabayaniD· 2 shared Abdoulaye DiabatéiD· 1 shared Abdoulaye NiangiD· 1 shared Adam J DobsoniD· 1 shared

Activity by Year

2019-2026 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 27 mutual co-author links

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3 shared papersBioinformatics

Mario González‐JiménezORCID

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3 papers

Recent·Most cited

Systems BiologybioRxivPreprintMar 25, 2026

Barcoding biology: Chemotype predicts variation in genotype, physiology, and stress response

Rita Ibrahim, Mario González‐Jiménez, Jonathan H. H. Booth…·Adam J Dobson

The paper uses chemotypes derived from FTIR spectroscopy and machine learning to predict biological variation and stress response in Drosophila melanogaster.

DOI 10.64898/2026.03.22.713522

Drosophilamachine learning (classical)

𝕏 PostBluesky

BioinformaticsBMC BioinformaticsPeer-reviewedJan 9, 2023

Using transfer learning and dimensionality reduction techniques to improve generalisability of machine-learning predictions of mosquito ages from mid-infrared spectra

Emmanuel P. Mwanga, Doreen Josen Siria, Joshua Mitton…·Simon A. Babayan

This study improves mosquito age prediction from mid-infrared spectra using transfer learning and dimensionality reduction, achieving high accuracy across different populations.

29 citations

machine learning (classical)deep learning

𝕏 PostBluesky

BioinformaticsWellcome Open ResearchPeer-reviewedMay 1, 2019

Prediction of malaria mosquito species and population age structure using mid-infrared spectroscopy and supervised machine learning

Mario González‐Jiménez, Simon A. Babayan, Pegah Khazaeli…·Klaas Wynne

This paper uses mid-infrared spectroscopy and machine learning to accurately predict malaria mosquito species and age structure, offering a fast and cost-effective alternative to traditional methods.

64 citations

machine learning (classical)

𝕏 PostBluesky