Sung Rye Park

COMPUTATIONAL BIOLOGIST
Specializing in Translational Drug Discovery

Computational Biologist with 7+ years of experience in multi-omics integration and translational biomarker analysis. Proven track record of pharma collaborations (BMS, Takeda, Japan Tobacco) and contributions to biological insights in oncology, immunology, and metabolic disease. Currently at Battelle, applying AI/ML to analytical pipelines and developing scalable workflows.

Develops analytical frameworks that integrate biology, machine learning, and multi-omics data to drive systems-level insights from complex, heterogeneous datasets.

Domains: Immuno-oncology · Metabolic disease (NAFLD) · Neurodegeneration (AD, TBI)
Expertise: Single cell · Multi-omics integration · Machine Learning · Pipeline development · Analytical templates · Interactive reports


CV   GitHub   LinkedIn


Featured Projects

2024- Present

Novel function of Tle3: Multi-omics approach

  • Four modalities with pair-wise integration
  • scRNA-seq, RNA-seq, ATAC-seq, Cut&Run (TLE3)
  • Nature Immunology (2024); co-first author

    Hackensack Meridian Health Pair-wise integration Immunology T cell Lineage

STING Agonist Response: BMS Collaboration

  • Responding cell type stratification
  • scRNA-seq + scTCR-seq
  • Cell Reports Medicine (2025)

    Dana Farber Single-cell RNA-seq scTCR-seq Immunology Oncology Deconvolution

Virtual Patient Cohort Generation (MicroIRAD)

  • CVAE framework learning TCGA-LUAD
  • 400+ synthetic patients
  • Patient-Model cell line pair similarity score (10,000+)
  • Preclinical go/no-go decision support

    Battelle Deep Learning PyTorch/Tensorflow CVAE TCGA LUAD AutoEncoder

Cell image + RNA-seq by MOFA2

  • Phenotypic profiling + Transcriptome
  • Large scale compound response study
  • End-to-end integration pipeline

    Battelle MOFA2 Cell Painting Transcriptome Drug response Human lung cancer Multiomics

Selected Publications

Nature Immunology 2024
The transcriptional cofactor Tle3 reciprocally controls effector and central memory CD8+ T cell fates.
Co-first author  ·  View Paper →
Cell Reports Medicine 2025
Immune targeting of triple-negative breast cancer through a clinically actionable STING agonist-CAR T cell platform.
Cell 2021
Seq-Scope: Microscopic examination of spatial transcriptome.
Cell Reports 2021
Single cell transcriptome analysis of colon cancer cell response to 5-fluorouracil-induced DNA damage.
First author  ·  View Paper →
AJP-Endocrinology and Metabolism 2020
Holistic Characterization of Single Hepatocyte Transcriptome Responses to High Fat Diet.
First author  ·  View Paper →

Analysis Workflows

Single Cell RNA-seq
QC, integration (Harmony), UMAP/clustering, cell type annotation, trajectory, AUC, scTCR-seq preprocessing
Bulk RNA-seq
PCA, TPM, DEG analysis, GSEA/ssGSEA, K-means clustering, feature selection
NK cell identification using ML
Elastic Net for feature selection, K-means + DEG-based pattern identification (bulk RNA-seq)
Chromatin & Epigenomics
ChIP-seq, ATAC-seq, CUT&RUN pipelines — peak calling, motif analysis
Omics Analytical Pipelines
Pipelines Collections; scRNAseq, RNA-seq, DNA-seq, ML

Experience

  • Battelle (2025-Present) : Data Scientist II, Bioinformatics
  • Dana Farber Cancer Institute (2022-2024) : Senior Bioinformatics Scientist
  • Hackensack Meridian Health (2021-2022) : Postdoctral fellow
  • University of Michigan (2017-2020) : Postdoctral fellow

GitHub Repositories

Repository Description
tle3-multiomics-NI2024 Multi-omics analysis for the TLE3 study (Nature Immunology, 2024), integrating RNA-seq, ATAC-seq, and ChIP-seq.
pubmed-local-rag Local RAG pipeline for querying PubMed literature using LLMs — offline, context-aware search without API calls.
lung-tme-deconv-profiler Bulk RNA-seq deconvolution pipeline for tumor microenvironment (TME) profiling in lung cancer.
rnaseq_local_chat Local LLM chat interface for interactive RNA-seq exploration — query DEG and pathway results in natural language.