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From the 1 of 5 linked papers with an AI index.

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5 papers

q-bio.QM2026

A vision foundation model for single-cell biology via spatial gene cartography

Ridvan Yesiloglu, Sakib Mostafa, James Zou +5

The paper introduces scVision, a vision foundation model that converts single-cell transcriptomic data into images by mapping genes onto a spatial layout, and uses a pretrained vis…

cs.LG2026

Knowledge Graph Modulated Deep Learning for Limited-Sample Clinical Data Analysis

Yuwei Xue, Sakib Mostafa, James Zou +5

Biological systems are governed by structured molecular interactions, where pathways, regulatory circuits, and functional gene relationships shape cellular behavior and disease pro…

cs.LG2026

Toward a universal foundation model for graph-structured data

Sakib Mostafa, Lei Xing, Md. Tauhidul Islam

Graphs are a central representation in biomedical research, capturing molecular interaction networks, gene regulatory circuits, cell--cell communication maps, and knowledge graphs.…

cs.LG2026

Vision-based Deep Learning Analysis of Unordered Biomedical Tabular Datasets via Optimal Spatial Cartography

Sakib Mostafa, Tarik Massoud, Maximilian Diehn +2

Tabular data are central to biomedical research, from liquid biopsy and bulk and single-cell transcriptomics to electronic health records and phenotypic profiling. Unlike images or…

cs.LG2025

Transformation of Biological Networks into Images via Semantic Cartography for Visual Interpretation and Scalable Deep Analysis

Sakib Mostafa, Lei Xing, Md. Tauhidul Islam

Complex biological networks are fundamental to biomedical science, capturing interactions among molecules, cells, genes, and tissues. Deciphering these networks is critical for und…