| Clustering algorithms: their application to gene expression data J Oyelade, I Isewon, F Oladipupo, O Aromolaran, E Uwoghiren, F Ameh, ... Bioinformatics and Biology insights 10, BBI. S38316, 2016 | 227 | 2016 |
| Data clustering: Algorithms and its applications J Oyelade, I Isewon, O Oladipupo, O Emebo, Z Omogbadegun, ... 2019 19th international conference on computational science and its …, 2019 | 90 | 2019 |
| Machine learning approach to gene essentiality prediction: a review O Aromolaran, D Aromolaran, I Isewon, J Oyelade Briefings in bioinformatics 22 (5), bbab128, 2021 | 53 | 2021 |
| Essential gene prediction in Drosophila melanogaster using machine learning approaches based on sequence and functional features O Aromolaran, T Beder, M Oswald, J Oyelade, E Adebiyi, R Koenig Computational and structural biotechnology journal 18, 612-621, 2020 | 37 | 2020 |
| Computational Identification of Metabolic Pathways of Plasmodium falciparum using the k‐Shortest Path Algorithm J Oyelade, I Isewon, O Aromolaran, E Uwoghiren, T Dokunmu, S Rotimi, ... International Journal of Genomics 2019 (1), 1750291, 2019 | 13 | 2019 |
| In Silico Knockout Screening of Plasmodium falciparum Reactions and Prediction of Novel Essential Reactions by Analysing the Metabolic Network J Oyelade, I Isewon, E Uwoghiren, O Aromolaran, O Oladipupo BioMed Research International 2018 (1), 8985718, 2018 | 12 | 2018 |
| Identifying essential genes across eukaryotes by machine learning T Beder, O Aromolaran, J Dönitz, S Tapanelli, EO Adedeji, E Adebiyi, ... NAR Genomics and Bioinformatics 3 (4), lqab110, 2021 | 11 | 2021 |
| Machine learning priority rule (MLPR) for solving resource-constrained project scheduling problems PI Adamu, O Aromolaran Proceedings of the International MultiConference of Engineers and Computer …, 2018 | 6 | 2018 |
| Predicting host dependency factors of pathogens in Drosophila melanogaster using machine learning O Aromolaran, T Beder, E Adedeji, Y Ajamma, J Oyelade, E Adebiyi, ... Computational and Structural Biotechnology Journal 19, 4581-4592, 2021 | 5 | 2021 |
| Machine learning algorithms: their applications in plant omics and agronomic traits’ improvement I Isewon, O Apata, F Oluwamuyiwa, O Aromolaran, J Oyelade F1000Research 11, 1256, 2022 | 3 | 2022 |
| Performance evaluation of features for gene essentiality prediction O Aromolaran, J Oyelade, E Adebiyi IOP Conference Series: Earth and Environmental Science 655 (1), 012019, 2021 | 3 | 2021 |
| Machine learning and sentiment analysis: Examining the contextual polarity of public sentiment on malaria disease in social networks J Oyelade, E Uwoghiren, I Isewon, O Oladipupo, O Aromolaran, K Michael 10th International Conference on Bioinformatics and Computational Biology …, 2018 | 3 | 2018 |
| In Silico Knockout Screening of J Oyelade, I Isewon, E Uwoghiren, O Aromolaran, O Oladipupo Plasmodium falciparum, 1-11, 0 | 3 | |
| Corrigendum to: Machine learning approach to gene essentiality prediction: a review O Aromolaran, D Aromolaran, I Isewon, J Oyelade Briefings in Bioinformatics 23 (1), bbab419, 2022 | 2 | 2022 |
| Solving project delays and abandonment using hybrid resource-constrained project scheduling models PI Adamu, O Aromolaran, FA Aitsebaomo Proceedings of the International MultiConference of Engineers and Computer …, 2018 | 2 | 2018 |
| Heuristic-enabled active machine learning: A case study of predicting essential developmental stage and immune response genes in Drosophila melanogaster OT Aromolaran, I Isewon, E Adedeji, M Oswald, E Adebiyi, R Koenig, ... Plos one 18 (8), e0288023, 2023 | 1 | 2023 |
| Overview of the human genome J Oyelade, I Isewon, O Ogunlana, O Aworunse, O Oyesola, O Aromolaran, ... Genome Plasticity in Health and Disease, 9-26, 2020 | 1 | 2020 |
| Modeling of Metabolic Pathways Using Petri Net J Oyelade, I Isewon, O Ogunbona, O Aromolaran, J Soyemi 2017 International Conference on Computational Science and Computational …, 2017 | 1 | 2017 |
| In-silico validation of the essentiality of reactions in plasmodium falciparum metabolic network J Oyelade, E Uwoghiren, I Isewon, F Aromolaran, O Oladipupo Proceedings of the World Congress on Engineering and Computer Science 2, 2017 | 1 | 2017 |
| Correction: Heuristic-enabled active machine learning: A case study of predicting essential developmental stage and immune response genes in Drosophila melanogaster OT Aromolaran, I Isewon, E Adedeji, M Oswald, E Adebiyi, R Koenig, ... PloS one 19 (6), e0305979, 2024 | | 2024 |
