Shuyi Yang

ORCID: 0009-0004-1604-8874
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About
Contact & Profiles
Research Areas
  • Single-cell and spatial transcriptomics
  • Advanced Breast Cancer Therapies
  • Polyomavirus and related diseases
  • Bioinformatics and Genomic Networks
  • Gene Regulatory Network Analysis
  • Cancer Genomics and Diagnostics
  • Monoclonal and Polyclonal Antibodies Research
  • Gene expression and cancer classification
  • Cancer Immunotherapy and Biomarkers
  • Bacteriophages and microbial interactions

University of South Carolina
2024-2025

Chinese Academy of Medical Sciences & Peking Union Medical College
2025

Peking Union Medical College Hospital
2025

Henan Cancer Hospital
2022

Zhengzhou University
2022

The rapid advancements of single-cell RNA sequencing (scRNAseq) technology provide high-resolution views transcriptomic activity within a single cell. Most routine analyses scRNAseq data focus on individual genes; however, the one-gene-at-a-time analysis is likely to miss meaningful genetic interactions. Gene co-expression addresses this issue by identifying coordinated gene expression changes in response cellular conditions, such as developmental or temporal trajectory. Identifying...

10.1101/2025.01.23.634392 preprint EN bioRxiv (Cold Spring Harbor Laboratory) 2025-01-26

Plasma microbial cell-free DNA (mcfDNA) is a key biomarker for diagnosing bloodstream infections (BSIs), which contribute significantly to morbidity and mortality, particularly in patients with severe trauma, chronic illnesses, or immunosuppressive conditions. However, the baseline distribution of mcfDNA different populations remains unclear. This study characterizes plasma profiles across various human populations. A total 300 blood samples were collected from 10 groups: healthy individuals...

10.3389/fmicb.2025.1578820 article EN cc-by Frontiers in Microbiology 2025-04-29

Abstract The advancements in high-throughput technologies provide exciting opportunities to obtain multi-omics data from the same individuals a biomedical study, and joint analyses of multiple sources offer many benefits. However, occurrence missing values is an inevitable issue because measurements such as mRNA gene expression levels often require invasive tissue sampling patients. Common approaches for addressing include based on observations with complete or imputation methods. In this...

10.1007/s13253-024-00603-3 article EN cc-by Journal of Agricultural Biological and Environmental Statistics 2024-02-28
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