6 papers · 1 filter
Language-encoded network topology enables large language models to reason about complex networks
Ucchwas Talukder Utsha, Sakib Mostafa, James Zou +1
Networks describe systems in biology and beyond, from protein interactions and social relationships to power grids and citation records. Reasoning about such systems requires under…
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…
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…
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…