Olufemi Aromolaran
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- Machine Learning in Bioinformatics 6
- Bioinformatics and Genomic Networks 5
- Microbial Metabolic Engineering and Bioproduction 4
- Genomics and Phylogenetic Studies 3
- vaccines and immunoinformatics approaches 1
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- Computational Drug Discovery Methods 2
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- BIM and Construction Integration 1
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- Scheduling and Optimization Algorithms 1
- Co-authors
- Jelili OyeladeItunuoluwa IsewonEzekiel AdebiyiOlufunke OladipupoRainer KoenigMarcus OswaldGregor BucherPatience I. Adamu
- Journals
- Computational and Structural Biotechnology Journal (2 papers)Briefings in Bioinformatics (2 papers)BioMed Research International (1 paper)
- Partner nations
- NigeriaGermanyUnited Kingdom
In The Last Decade
Olufemi Aromolaran
14 papers receiving 315 citations
Peers
Comparison fields: 5 of 107
- Aging 5
- Molecular Biology 169
- Health Informatics 3
- Computational Theory and Mathematics 33
- Artificial Intelligence 66
Countries citing papers authored by Olufemi Aromolaran
This map shows the geographic impact of Olufemi Aromolaran's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Olufemi Aromolaran with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Olufemi Aromolaran more than expected).
Fields of papers citing papers by Olufemi Aromolaran
This network shows the impact of papers produced by Olufemi Aromolaran. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Olufemi Aromolaran. The network helps show where Olufemi Aromolaran may publish in the future.
Co-authorship network
The 12 scholars most cited alongside Olufemi Aromolaran, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2023 | 3 | |
| 2 | 2021 | 15 | |
| 3 | 2021 | 3 | |
| 4 | 2021 | 1 | |
| 5 | 2021 | 3 | |
| 6 | 2021 | 63 | |
| 7 | 2020 | 28 | |
| 8 | 2019 | 59 | |
| 9 | 2019 | 10 | |
| 10 | 2018 | 8 | |
| 11 | Machine Learning Priority Rule (MLPR) For Solving Resource-Constrained Project Scheduling Problems | 2018 | 4 |
| 12 | Machine Learning and Sentiment Analysis: Examining the Contextual Polarity of Public Sentiment on Malaria Disease in Social Networks | 2018 | 1 |
| 13 | 2017 | 1 | |
| 14 | 2016 | 129 |
About Olufemi Aromolaran
Olufemi Aromolaran is a scholar working on Molecular Biology, Computational Theory and Mathematics and Industrial and Manufacturing Engineering, having authored 14 papers that have together received 328 indexed citations. Recurring topics across this work include Machine Learning in Bioinformatics (6 papers), Bioinformatics and Genomic Networks (5 papers), Microbial Metabolic Engineering and Bioproduction (4 papers), Genomics and Phylogenetic Studies (3 papers), Computational Drug Discovery Methods (2 papers), vaccines and immunoinformatics approaches (1 paper), BIM and Construction Integration (1 paper) and Scheduling and Optimization Algorithms (1 paper). The work is most often cited by research in Aging (5 citations), Molecular Biology (169 citations) and Health Informatics (3 citations). Olufemi Aromolaran has collaborated with scholars based in Nigeria, Germany and United Kingdom. Frequent co-authors include Jelili Oyelade, Itunuoluwa Isewon, Ezekiel Adebiyi, Olufunke Oladipupo, Rainer Koenig, Marcus Oswald, Gregor Bucher, Patience I. Adamu, Jürgen Dönitz and Titilope M. Dokunmu. Their work appears in journals such as Computational and Structural Biotechnology Journal, Briefings in Bioinformatics, BioMed Research International, NAR Genomics and Bioinformatics and PLoS ONE.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.