Sui Huang

Modeling healthy proteomic profiles for anomaly detection using subspace learning based one-class classification

This paper develops a subspace one-class classification framework for proteomics-driven anomaly detection using healthy reference data to identify disease patterns across multiple conditions.

Blocking Osteoprotegerin Reprograms Cancer Associated Fibroblast to Promotes Immune Infiltration into the Tumor Microenvironment

This study identifies OPG-secreting CAFs as immunosuppressive stromal cells and shows that blocking OPG promotes immune infiltration and tumor regression in mouse models.

Alterations of the composition and spatial organization of the microenvironment following non-dysplastic Barrett's esophagus through progression to cancer

This study identifies immune cell changes and gene expression patterns in Barrett's esophagus progression to cancer using spatial and multi-omic analyses.

Fokker-Planck diffusion maps of multiple single cell microglial transcriptomes reveals radial differentiation into substates associated with Alzheimer's pathology

The paper uses Fokker-Planck diffusion maps to analyze microglial transcriptomes, revealing substates associated with Alzheimer's pathology.

Gene Regulatory Network topology governs resistance and treatment escape in glioma stem-like cells

The paper shows how gene regulatory network topology in glioma stem-like cells influences drug resistance and treatment escape, suggesting strategies to overcome resistance through combinatorial therapies.

Single cell gene set scoring with nearest neighborgraph smoothed data (gssnng).

The paper introduces a method to compute gene set scores for single-cell data by smoothing expression values using a nearest neighbor graph, improving accuracy over bulk methods.

Fast and simple comparison of semi-structured data, with emphasis on electronic health records

The paper introduces a fast hashing method for comparing semi-structured data, demonstrating its use on electronic health records for duplicate detection and clustering.

Extracting Intercellular Signaling Network Of Cancer Tissues Using Ligand-Receptor Expression Patterns From Whole-Tumor And Single-Cell Transcriptomes

The paper constructs intercellular signaling networks in cancer tissues using ligand-receptor expression patterns from whole-tumor and single-cell transcriptomes to identify cell communication structures influencing cancer behaviors.

Cell fate-decision as high-dimensional critical state transition

The paper identifies early-warning signals for cell fate transitions by analyzing high-dimensional gene expression data from differentiating blood progenitor cells.