From the 1 of 8 linked papers with an AI index.
8 papers
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…
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…
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.…
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…
Redefining the Down-Sampling Scheme of U-Net for Precision Biomedical Image Segmentation
Mingjie Li, Yizheng Chen, Md Tauhidul Islam +1
U-Net architectures have been instrumental in advancing biomedical image segmentation (BIS) but often struggle with capturing long-range information. One reason is the conventional…
Uncovering spatial tissue domains and cell types in spatial omics through cross-scale profiling of cellular and genomic interactions
Rui Yan, Xiaohan Xing, Xun Wang +3
Cellular identity and function are linked to both their intrinsic genomic makeup and extrinsic spatial context within the tissue microenvironment. Spatial transcriptomics (ST) offe…