Author

Saishi Cui

Drexel UniversityORCID 0000-0003-1108-920XUnclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Approach:statistical model· 3 Research Focus:cell type annotation· 2 Research Focus:differential expression· 2 Organism:human· 2 Approach:machine learning (classical)· 2 Assay:scRNA-seq· 2 Research Focus:benchmarking· 1 Approach:deep learning· 1

Frequent Co-Authors

Issa ZakeriiD· 2 shared Sina NassiriiD· 2 shared Wei SuniD· 2 shared David WongiD· 1 shared Kristina A. MatkowskyjiD· 1 shared Ming YuiD· 1 shared Neeti SwarupiD· 1 shared Qianchuan HeiD· 1 shared

Activity by Year

2024-2026 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 19 mutual co-author links

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2 shared papersBioinformatics

Issa ZakeriORCID

Mutual co-authors in cluster

Author profile →

4 papers

Recent·Most cited

mFrag: Integrating External DNA Methylation References Improves Lung Cancer Early Detection by Fragmentomics

Saishi Cui, Neeti Swarup, Qianchuan He, William Hsu, David Wong, Yingye Zheng, Robert B Scharpf, Wei Sun

mFrag improves lung cancer early detection using fragmentomics by integrating DNA methylation data and combining two models to enhance prediction accuracy.

bioRxiv · Nov 9, 2026 · PreprintBioinformatics

Translating Histopathology Foundation Model Embeddings into Cellular and Molecular Features for Clinical Studies

Saishi Cui, Zhining Sui, Ziyi Li, Kristina A. Matkowskyj, Ming Yu, William M. Grady, Wei Sun

STpath translates histopathology image embeddings into cell-type composition and gene expression estimates for clinical applications.

bioRxiv · Mar 23, 2026 · PreprintBioinformatics

Mcadet: a feature selection method for fine-resolution single-cell RNA-seq data based on multiple correspondence analysis and community detection

Saishi Cui, Sina Nassiri, Issa Zakeri

Mcadet improves feature selection in scRNA-seq by integrating MCA and community detection, showing better performance on fine-resolution and rare cell type datasets.

PLoS Computational Biology · Oct 28, 2024Peer-reviewedBioinformatics

Imbalance and Composition Correction Ensemble Learning Framework (ICCELF): A novel framework for automated scRNA-seq cell type annotation

Saishi Cui, Sina Nassiri, Issa Zakeri

The paper introduces ICCELF, a framework for automated scRNA-seq cell type annotation that addresses class imbalance and data compositionality, improving annotation accuracy.

bioRxiv · Apr 21, 2024 · PreprintBioinformatics