Countries
Institutions
Fields
Rankings
Compare

Search institutions, scholars, countries and publications

Sankore

Named after the University of Sankore in Timbuktu — one of the world’s oldest centres of learning. Every figure here is computed from work-level records in our own graph, never copied from a source’s summary count.

Built from

OpenAlex — works, authorships, subject classification
ROR — institutional identity
ORCID — researcher identity
Crossref — publisher confirmation

Browse

Countries
Institutions
Fields
Rankings
What we cover

Coverage is partial and says so. A country appears with its research output only once its works have been swept; until then the portal shows whatever the graph happens to hold for it and labels it as exactly that.

Breast cancer prediction based on gene expression data using interpretable machine learning techniques

2025Scientific ReportsJournalOpen access

10.1038/s41598-025-85323-5 Full text21 citations

Authors

9 authors across 6 institutions in 3 countries.

Gabriel Kallah-DagaduFirst author
- University of KwaZulu-Natal (ZA)
- University of Ghana (GH)
Mohanad Mohammed
- University of KwaZulu-Natal (ZA)
Justine B Nasejje
- University of the Witwatersrand (ZA)
Nobuhle Nokubonga Mchunu
- South African Medical Research Council (ZA)
Halima S Twabi
- University of Malawi (MW)
Jesca Mercy Batidzirai
- University of KwaZulu-Natal (ZA)
Geoffrey Chiyuzga Singini
- University of Malawi (MW)
Portia Nevhungoni
- South African Medical Research Council (ZA)
Innocent MaposaSenior authorCorresponding
- Stellenbosch University (ZA)

Fields

Assignment is probabilistic — a work belongs to several fields in proportions.

Gene expression and cancer classificationlevel 3 · 1.00
Bioinformatics and Genomic Networkslevel 3 · 0.98
AI in cancer detectionlevel 3 · 0.98

Sources

Several sources describing one work is the point — it means the record rests on more than one authority.

openalexseen September 8, 2026
2025 · Scientific Reports · 21 citations
https://openalex.org/W4408158633

Breast cancer prediction based on gene expression data using interpretable machine learning techniques · Sankore