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princello/README.md

Zicheng Wang

I build models and pipelines that read biology end to end, from raw reads to learned structure.

┌────────────────────────────────────────────────────┐
│  computational biology   ·   machine learning      │
│                                                    │
│  single cell → spatial → pathology → protein       │
│  sequence · structure · whole-slide image → model  │
└────────────────────────────────────────────────────┘

I work close to the bench, with the people who generate the data. Single-cell and spatial genomics through QC, integration, and interpretation, and deep learning over sequence, structure, and imaging at cluster scale.

scholar · linkedin · github · orcid · email

Pinned Loading

  1. pathology-fibrosis-pipeline pathology-fibrosis-pipeline Public

    Computational pathology pipeline for tissue fibrosis quantification from whole-slide images using foundation model embeddings

    Jupyter Notebook 1

  2. ncountr ncountr Public

    Python pipeline for Nanostring nCounter gene expression analysis — parse, QC, normalize, DE, pathway scoring

    Python 2

  3. GePMI GePMI Public

    GePMI: A statistical model for personal intestinal microbiome identification

    Python 6

  4. G2VTCR G2VTCR Public

    Python 1

  5. scRNA-seq-TRM-paper scRNA-seq-TRM-paper Public

    R

  6. TCR-FOLD TCR-FOLD Public

    Python