Author

Pegah Khazaeli

University of Glasgow

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· 1

Signature Assays, Organisms & Methods

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Approach:machine learning (classical)· 1

Frequent Co-Authors

Abdoulaye DiabatéiD· 1 shared Abdoulaye NiangiD· 1 shared Doreen Josen SiriaiD· 1 shared Elliott ReedyiD· 1 shared Finlay WaltoniD· 1 shared Francesco BaldiniiD· 1 shared Fredros O. OkumuiD· 1 shared Heather M. FergusoniD· 1 shared

Activity by Year

2019-2019 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 45 mutual co-author links

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1 shared paperBioinformatics

Abdoulaye DiabatéORCID

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1 paper

Recent·Most cited

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, Margaret Doyle, Finlay Walton, Elliott Reedy, Thomas Glew, Mafalda S. Viana, Lisa C Ranford-Cartwright, Abdoulaye Niang, Doreen Josen Siria, Fredros O. Okumu, Abdoulaye Diabaté, Heather M. Ferguson, Francesco Baldini, 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.

Wellcome Open Research · May 1, 2019Peer-reviewedBioinformatics