Author

Maryam KafiKang

University of Connecticut

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

Biology Disciplines

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Bioinformatics· 2

Signature Assays, Organisms & Methods

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Approach:deep learning· 2 Approach:Bayesian inference· 1 Research Focus:benchmarking· 1 Research Focus:differential expression· 1 Research Focus:drug response / drug discovery· 1 Assay:scRNA-seq· 1 Approach:transformer / foundation model· 1

Frequent Co-Authors

Abdeltawab HendawiiD· 1 shared Pavel SkumsiD· 1 shared

Activity by Year

2023-2026 · peak 1/yr

Co-Author Collaboration Network

2 top collaborators · 0 mutual co-author links

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1 shared paperBioinformatics

Abdeltawab HendawiORCID

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2 papers

Recent·Most cited

Reconstructing intra-tumor fitness landscapes from scSeq CNA genotypes via simulation-based Bayesian inference and Deep Learning

Maryam KafiKang, Pavel Skums

This paper infers intra-tumor selection coefficients from clonal CNA profiles using a simulation-based Bayesian framework and deep learning, achieving better performance than baseline methods.

bioRxiv · Apr 14, 2026 · PreprintBioinformatics

Drug-Drug Interaction Extraction from Biomedical Text using Relation BioBERT with BLSTM

Maryam KafiKang, Abdeltawab Hendawi

This paper proposes a deep learning approach using Relation BioBERT and BLSTM to extract and classify drug-drug interactions from biomedical text, achieving higher F-scores on benchmark datasets.

Machine Learning and Knowledge Extraction · Jun 10, 2023Peer-reviewedBioinformatics