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Temitope Ibukunoluwa Adegbenro · Peerford

University of Lagos / Scholars

TA

Temitope Ibukunoluwa Adegbenro

University of Lagos

Publishing since 2024, latest 2026

Computational Theory and Mathematics
Molecular Biology
Infectious Diseases
Oncology
Analytical Chemistry
Biochemistry

ORCID 0009-0001-3105-8147
Their record on OpenAlex

Publications: 72024–2026
Citations: 38to those papers
h-index: 4i10-index 1
Field-weighted impact: 2.031.00 is the world average
World top 10%: 43%3 of 7 scored papers
Open access: 57%4 papers free to read

2 other works — preprints, datasets and the like — are listed but not counted.

By year

Papers, and the citations to them

Publications, left axisCitations to that year’s papers, right axis2026 still in progress

Citations received each year

Peerford

To all their work, old papers included. Google Scholar also counts citations from theses, books and web pages, so its line runs higher.

What they work on

From the classification of each paper

Subfields

Computational Theory and Mathematics457%
Molecular Biology343%

Career

On their papers

University of Lagos9 works
Nigerian Defence Academy2 works
Akatsi College of Education1 work
Lagos State Health Service Commission1 work

Every institution they have given on a paper.

Publications

7 in all

Newest Most cited Oldest Title

Search their publications by title

Drug Repurposing: A Computational Prediction of the Inhibitory Activity of Antidepressants on Cyclooxygenase-2 for the Management of Rheumatoid Arthritis.
2026Zenodo (CERN European Organization for Nuclear Research)JournalOpen access0 citations10.5281/zenodo.22818670
De novo design and bioactivity prediction of mitotic kinesin Eg5 inhibitors using MPNN and LSTM-based transfer learning

Download CV:PDF · Word

Who they write with Where their co-authors are Every publication

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Infectious Diseases229%

Oncology229%

Analytical Chemistry114%

Biochemistry114%

Epidemiology114%

General Health Professions114%

Pharmacology114%

Spectroscopy114%

Health Sciences
Life Sciences
Physical Sciences

Topics most written on

Computational Drug Discovery Methods4
HIV/AIDS drug development and treatment2
Analytical Chemistry and Chromatography1
Analytical Methods in Pharmaceuticals1
Bioinformatics and Genomic Networks1
Cancer Research and Treatment1
Cervical Cancer and HPV Research1
Diverse Scientific Research Studies1
Global Cancer Incidence and Screening1
Hepatitis B Virus Studies1
Machine Learning in Bioinformatics1
Pharmacological Effects of Natural Compounds1

Who they write with

Their most frequent co-authors, and the papers those co-authors share

Where their co-authors are

57% of their papers have a co-author abroad

papers co-written1122223Home

Most frequent partner countries

United States3
Kenya2
United Kingdom1
Philippines1

Papers with at least one author in that country.

Institutions written with most

Obafemi Awolowo UniversityNG4 papers
University of Arkansas at Little RockUS3 papers
University of Arkansas for Medical SciencesUS3 papers
Bayero University KanoNG3 papers
Adekunle Ajasin UniversityNG3 papers
Covenant UniversityNG3 papers
Babcock UniversityNG2 papers
Nigerian Defence AcademyNG2 papers
University of IbadanNG2 papers
University of EmbuKE2 papers

Where they publish

Biology Methods and Protocols1
ChemistrySelect1
Computers in Biology and Medicine1
Discover Chemistry.1
Journal of Computational Biophysics and Chemistry1
Journal of Global Health Science1
Zenodo (CERN European Organization for Nuclear Research)1

How it can be read

57% free to read

Diamond 2 · 29%Free to read and to publish
Gold 1 · 14%In an open-access journal
Green 1 · 14%A copy in a repository
Closed 3 · 43%Behind a paywall

Development goals addressed

From each paper’s title and abstract

3Good health and well-being1
17Partnerships for the goals1

Most cited

Machine Learning-Based Drug Repositioning of Novel Human Aromatase Inhibitors Utilizing Molecular Docking and Molecular Dynamic Simulation
Journal of Computational Biophysics and Chemistry
202414 citationsWorld top 10%
De novo design and bioactivity prediction of mitotic kinesin Eg5 inhibitors using MPNN and LSTM-based transfer learning
Computers in Biology and Medicine
20259 citationsWorld top 10%
HPLC characterization, molecular docking, QSAR and molecular dynamics simulation of Alstonia boonei phytochemical analogs as potent 5-alpha reductase inhibitors
Discover Chemistry.
20257 citationsOpen access · Diamond
Barriers to HPV vaccination and cervical cancer screening in developing countries
Journal of Global Health Science17
20254 citationsOpen access · Diamond
In-silico identification of phytochemical compounds from various medicinal plants as potent HIV-1 non-nucleoside reverse transcriptase inhibitors utilizing molecular docking and molecular dynamics simulations
Biology Methods and Protocols
20254 citationsOpen access · Gold

2025

Computers in Biology and Medicine

Journal

9 citations

10.1016/j.compbiomed.2025.110672

HPLC characterization, molecular docking, QSAR and molecular dynamics simulation of Alstonia boonei phytochemical analogs as potent 5-alpha reductase inhibitors

2025Discover Chemistry.JournalOpen access7 citations10.1007/s44371-025-00209-9

Barriers to HPV vaccination and cervical cancer screening in developing countries

2025Journal of Global Health ScienceJournalOpen access4 citations10.35500/jghs.2025.7.e5

In-silico identification of phytochemical compounds from various medicinal plants as potent HIV-1 non-nucleoside reverse transcriptase inhibitors utilizing molecular docking and molecular dynamics simulations

2025Biology Methods and ProtocolsJournalOpen accessSenior author4 citations10.1093/biomethods/bpaf081

Design and Discovery of New HIV‐1 RT Inhibitors Using Generative AI, Virtual Screening, and Molecular Dynamics Simulations

2025ChemistrySelectJournalCorresponding0 citations10.1002/slct.202504102

Machine Learning-Based Drug Repositioning of Novel Human Aromatase Inhibitors Utilizing Molecular Docking and Molecular Dynamic Simulation

2024Journal of Computational Biophysics and ChemistryJournal14 citations10.1142/s2737416524410035