Author

Monica Kapasa

University of Zambia

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

Click to filter author papers

Bioinformatics· 1 Microbiology· 1

Signature Assays, Organisms & Methods

Click to filter · or open tag

Organism:human· 2 Research Focus:clustering· 1 Approach:deep learning· 1 Approach:machine learning (classical)· 1 Assay:metagenomics· 1

Frequent Co-Authors

Alexander P. KeiliD· 1 shared Alyse WheelockiD· 1 shared Arnfinn SundsfjordiD· 1 shared Bellington VwalikaiD· 1 shared Benard Ngoma· 1 shared Bwalya MulengaiD· 1 shared Charles Chimoga· 1 shared Chibamba N. MumbaiD· 1 shared

Activity by Year

2019-2026 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 29 mutual co-author links

Click any collaborator node to inspect or filter shared papers

Focal author (center)Selected co-authorORCID co-authorUnlinked name

Curved chords = mutual co-authorship

1 shared paperBioinformatics

Alexander P. KeilORCID

Mutual co-authors in cluster

Author profile →

2 papers

Recent·Most cited

Genomic analysis of Klebsiella pneumoniae causing community-acquired respiratory deaths among Zambian infants and children using targeted RNA-probe hybridization-capture metagenomics

Kenneth Lindstedt, Alyse Wheelock, Mulemba Samutela, Wasifa Kabir, Mwelwa Chasaya, Natasha Namuziya, Emilia Jumbe Marsden, Monica Kapasa, Chibamba N. Mumba, Bwalya Mulenga, Kafula Lisa Nkole, Rachel C Pieciak, Victor C. Mudenda, Chilufya Chikoti, Benard Ngoma, , Christopher John Gill

This study uses metagenomic sequencing to analyze Klebsiella pneumoniae from lung biopsies of Zambian children, identifying genetic sublineages, antimicrobial resistance, and potential vaccine targets.

bioRxiv · Apr 15, 2026 · PreprintMicrobiology

Improving preterm newborn identification in low-resource settings with machine learning

Katelyn Rittenhouse, Bellington Vwalika, Alexander P. Keil, Jennifer Winston, Marie C. D. Stoner, Joan T. Price, Monica Kapasa, Mulaya Mubambe, Vanilla Banda, Whyson Muunga, Jeffrey S. A. Stringer

The paper develops a machine learning model to improve preterm newborn identification in low-resource settings using readily available maternal and birth data.

PLoS ONE · Feb 27, 2019Peer-reviewedBioinformatics