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Miracle Olatilewa Olapade · Peerford

University of Ibadan / Scholars

MO

Miracle Olatilewa Olapade

University of Ibadan

Publishing since 2025, latest 2026

Computational Theory and Mathematics
Pharmacology
Genetics
Molecular Biology

Their record on OpenAlex
Download CV:PDF Word
Who they write with Where their co-authors are Every publication
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Publications: 22025–2026
Citations: 0to those papers
h-index: 0i10-index 0
Field-weighted impact: 0.001.00 is the world average
World top 10%: 0%0 of 2 scored papers
Open access: 100%2 papers free to read

By year

Papers, and the citations to them

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

What they work on

From the classification of each paper

Subfields

Computational Theory and Mathematics2100%
Pharmacology2100%
Genetics150%

Publications

2 in all

Newest Most cited Oldest Title

Search their publications by title

An integrated machine learning and structure-based framework for identifying natural inhibitors of estrogen receptor alpha using curated MCF-7 cytotoxicity data
2026Discover Chemistry.JournalOpen accessSenior author0 citations10.1007/s44371-026-00729-y
Stacked Ensemble Machine Learning for Human Carbonic Anhydrase II Binding Affinity Prediction

Molecular Biology

150%

Health Sciences
Life Sciences
Physical Sciences

Topics most written on

Computational Drug Discovery Methods2
Cholinesterase and Neurodegenerative Diseases1
Enzyme function and inhibition1
Estrogen and related hormone effects1
Microbial Natural Products and Biosynthesis1

Who they write with

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

Where their co-authors are

0% of their papers have a co-author abroad

Most frequent partner countries

Papers with at least one author in that country.

Institutions written with most

Federal University Oye EkitiNG1 paper
Dominion University, IbadanNG1 paper

Where they publish

Discover Chemistry.1

How it can be read

100% free to read

Diamond 1 · 50%Free to read and to publish
Gold 1 · 50%In an open-access journal

Development goals addressed

From each paper’s title and abstract

3Good health and well-being1

Most cited

An integrated machine learning and structure-based framework for identifying natural inhibitors of estrogen receptor alpha using curated MCF-7 cytotoxicity data
Discover Chemistry.3
20260 citationsOpen access · Diamond
Stacked Ensemble Machine Learning for Human Carbonic Anhydrase II Binding Affinity Prediction
20250 citationsOpen access · Gold

2025

Publication

Open access

First author

0 citations

10.55455/acsnigeria.1.2.149-154