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Naomi Kayeri · Peerford

University of Health and Allied Sciences / Scholars

NK

Naomi Kayeri

University of Health and Allied Sciences

Publishing since 2026

Computational Theory and Mathematics
Molecular Biology
Oncology

ORCID 0009-0005-5269-1653
Their record on OpenAlex
Download CV:PDF Word
Who they write with Where their co-authors are Every publication
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Publications: 22026
Citations: 3to those papers
h-index: 1i10-index 0
Field-weighted impact: 7.031.00 is the world average
World top 10%: 50%1 of 2 scored papers
Open access: 100%2 papers free to read

By year

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 Mathematics2100%
Molecular Biology2100%
Oncology150%

Health Sciences
Life Sciences

Publications

2 in all

Newest Most cited Oldest Title

Search their publications by title

A computational pipeline combining machine learning and molecular simulations identifies repurposed PI3Kα inhibitors from FDA-approved drugs
2026Artificial Intelligence ChemistryJournalOpen access3 citations10.1016/j.aichem.2026.100111
Discovery of novel MDM2 inhibitors from a Penicillium metabolome library: An integrated phylogenetic, machine learning, and molecular simulation approach

Physical Sciences

Topics most written on

Computational Drug Discovery Methods2
Cancer-related Molecular Pathways1
Metabolomics and Mass Spectrometry Studies1
PI3K/AKT/mTOR signaling in cancer1
Protein Degradation and Inhibitors1

Who they write with

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

Where their co-authors are

100% of their papers have a co-author abroad

papers co-written1111222Home

Most frequent partner countries

Pakistan2
United States1

Papers with at least one author in that country.

Institutions written with most

University of OkaraPK2 papers
University of ToledoUS1 paper
Kwame Nkrumah University of Science and TechnologyGH1 paper

Where they publish

Artificial Intelligence Chemistry1
Journal of Molecular Graphics and Modelling1

How it can be read

100% free to read

Gold 1 · 50%In an open-access journal
Green 1 · 50%A copy in a repository

Who funds it

2 of 2 papers name a funder

University of Health and Allied Sciences2

Most cited

A computational pipeline combining machine learning and molecular simulations identifies repurposed PI3Kα inhibitors from FDA-approved drugs
Artificial Intelligence Chemistry
20263 citationsWorld top 10%Open access · Gold
Discovery of novel MDM2 inhibitors from a Penicillium metabolome library: An integrated phylogenetic, machine learning, and molecular simulation approach
Journal of Molecular Graphics and Modelling
20260 citationsOpen access · Green

2026

Journal of Molecular Graphics and Modelling

Journal

Open access

0 citations

10.1016/j.jmgm.2026.109426