Author

Kolapo Muyiwa Oyebola

Mountain Top UniversityORCID 0000-0002-1003-2570Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 2

Signature Assays, Organisms & Methods

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Research Focus:benchmarking· 1 Research Focus:cell type annotation· 1 Approach:deep learning· 1 Research Focus:drug response / drug discovery· 1 Organism:human· 1 Assay:imaging· 1 Approach:machine learning (classical)· 1 Research Focus:software / tool· 1

Frequent Co-Authors

Afolabi J. OwoloyeiD· 2 shared Emmanuel Taiwo IdowuiD· 2 shared Funmilayo C. LigaliiD· 2 shared Ojochenemi A. EnejohiD· 2 shared Oluwagbemiga Olanrewaju AinaiD· 2 shared Adesola Zaidat MusaiD· 1 shared Adesola Zaidat MusaiD· 1 shared Adetunji P. AdewoleiD· 1 shared

Activity by Year

2022-2026 · peak 1/yr

Co-Author Collaboration Network

9 top collaborators · 33 mutual co-author links

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2 shared papersBioinformatics

Afolabi J. OwoloyeORCID

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2 papers

Recent·Most cited

BioinformaticsNext research.Peer-reviewedJul 1, 2026

Plasmo3Net: A Convolutional Neural Network-Based Algorithm for Detecting Malaria Parasites in Thin Blood Smear Images

Afolabi J. Owoloye, Funmilayo C. Ligali, Ojochenemi A. Enejoh…·Kolapo Muyiwa Oyebola

This paper develops Plasmo3Net, a CNN-based algorithm for detecting malaria parasites in thin blood smears, achieving high accuracy and precision.

2 citations

BioinformaticsPLoS ONEPeer-reviewedAug 26, 2022

Molecular docking, simulation and binding free energy analysis of small molecules as PfHT1 inhibitors

Afolabi J. Owoloye, Funmilayo C. Ligali, Ojochenemi A. Enejoh…·Kolapo Muyiwa Oyebola

The paper identifies five small molecules that inhibit PfHT1, a potential malaria drug target, through molecular docking, simulation, and binding energy analysis.

144 citationstop 1%

machine learning (classical)drug response / drug discovery