Computational Genomics & Systems Immunology

Decoding Dark Genome & Immune Dynamics

We uncover how hidden regions of our DNA reshape cellular identiy, immune responses, and disease evolution.

Explore Our Research Open Positions

Research Program

Core Scientific Pillars

01

Repetitive genome

We develop computational approaches to resolve the hidden, repetitive regions of the genome and measure when and how they become active.

#LongReadSeq #RepeatGenomics #Epigenomics
02

Cellular identity & Microenvironment

We study how repeat-derived nucleic acids reshape cell states, plasticity, immune signaling, and tissue homeostasis.

#scRNAseq #SpatialGenomics #TumorEcology
03

Disease evolution

We trace these programs across cancer, aging, and neurodegeneration to reveal shared mechanisms and new therapeutic opportunities.

#Nextflow #Python #HighThroughputBio
HOW WE WORK

Algorithms
grounded in
biology.

We combine statistical learning, AI, single-cell and spatial genomics, evolutionary modeling, and experimental collaboration. Every model begins with a biological question—and ends with a testable prediction.

01 · Single-cell (epi)genomics →
02 · Machine learning/AI →
03 · Evolutionary modeling →
04 · Functional validation →
TRANSLATIONAL IMPACT

Bridging Computation &
Clinical Oncology.

We partner closely with oncologists, cancer immunologists, and clinical trial teams to translate non-coding genomic discoveries into therapeutic strategies. By pairing high-resolution computational pipelines with patient biospecimens, we engineer actionable interventions and precision immunotherapy platforms.

01

Personalized Repeat Vaccines

Identifying tumor-specific cryptic peptides and neoantigens derived from transposable element activation to design custom mRNA and peptide immunotherapies.

#NeoantigenDiscovery
#CancerVaccines
02

Patient Cohort Multi-Omics

Directly profiling patient biopsies via single-cell RNA-seq and spatial transcriptomics to map native tumor heterogeneity and repeat-induced immune niches.

#TranslationalCohorts
#SpatialProfiling
03

Biomarker Stratification

Leveraging transposable element reactivation profiles and dsRNA sensor levels as predictive biomarkers for checkpoint inhibitor response and tumor recurrence.

#Immunotherapy
#PredictiveSignatures
04

Trial-Embedded Workflows

Deploying scalable, reproducible analysis pipelines on longitudinal clinical trial cohorts to monitor dynamic immune activation and escape mechanisms.

#ClinicalTrials
#TherapeuticResistance

Translational Collaboration & Trial Inquiries

We actively collaborate on clinical trial correlative studies, neoantigen discovery projects, and translational grant proposals.

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Scientific Output

Selected Publications

Immunostimulatory Repeats Cell Genomics

Characterization and immunogenic potential of repetitive element transcripts in human disease

Cell Genomics (2025)

Article ↗
Repeat Regulation Immunity

Epigenetic and transcriptional regulation of repetitive elements in tumor progression and immunity

Immunity (2024)

Article ↗
Viral Mimicry Cancer Discovery

Viral Mimicry by Repeats Mediates Evolutionary Plasticity in Cancer

Cancer Discovery (2024)

Article ↗
Therapeutic Targeting Cancer Discovery

LINE-1 ORF1p Mimics Viral Innate Immune Evasion Strategies

Cancer Discovery (2025)

Article ↗
Cell Identity Cell

Non-coding genomic elements and repeat architectures control cell identity and lineage commitment

Cell (2024)

Article ↗

People

Meet the Sun Lab

Siyu Sun, Ph.D.

Siyu Sun, Ph.D.

PI

Assistant Professor • Computational Biology & Cancer Genomics

Focuses on understanding non-coding genomic regulation, retrotransposon biology, and computational oncology through single-cell and high-throughput methodologies.

siyu_sun@urmc.rochester.edu • Google Scholar ↗ • GitHub ↗
Recruiting
Postdoctoral Fellow

Computational biology, repeat genomics, and single-cell analysis.

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Recruiting
Bioinformatician

Pipeline orchestration, HPC management, and genomic data science.

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Accepting
Graduate Students

Ph.D. rotations and Master's thesis projects in systems biology.

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Careers

Join Our Team

We are building a supportive, rigorous, and collaborative research environment where computational and quantitative scientists tackle high-impact problems in cancer biology.

Postdoctoral Fellow (Computational / Systems Biology)

Open

Candidates must hold or be completing a Ph.D. in System Biology, Evolutionrayr Biology, Computational Biology, Bioinformatics, Computer Science, or a related field. Strong programming proficiency in Python/R, experience with high-throughput sequencing datasets (RNA-seq, single-cell multi-omics), and first-author publications are required.

Bioinformatician / Data Engineer

Open

B.S. or M.S. in Bioinformatics, Computer Science, or Data Science. Responsible for maintaining scalable data analysis workflows (Nextflow/Snakemake), managing genomic data pipelines, and contributing to primary collaborative manuscripts and grant writing.

How to Apply

Please email your inquiry directly to Dr. Sun at siyu_sun@urmc.rochester.edu with the subject line format:
[Sun Lab Application] - [Position] - [Your Name]

  • Curriculum Vitae (CV)
  • Brief cover letter detailing your research interests and career goals
  • Links to GitHub / code repositories or representative publications
  • Contact information for 2–3 references
Email Application