Yuchao Jiang

Assistant Professor

University of North Carolina at Chapel Hill

United States

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Yuchao Jiang is an Assistant Professor at the University of North Carolina at Chapel Hill, USA. His research areas include personalized brain cancer diagnosis, single-cell multiomic characterization, and the analysis of non-coding regulatory variants. Recent works focus on innovative computational frameworks and integrative analyses for genomic studies, exploring transcription factors, target genes, and DNA damage repair mechanisms.

Articles (15)

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2023

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2023

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2023

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2022

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2020

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2020

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2020

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2020

Collaborators (3)

Li Chen

Associate Professor

University of Florida

UNITED STATES

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Laura Lindsey-Boltz

Associate Research Professor

University of North Carolina at Chapel Hill

UNITED STATES

View details

Wentao Li

Assistant Professor

University of Georgia

UNITED STATES

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Yuchao Jiang

Research Interests

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Articles (15)

TIVAN-indel: a computational framework for annotating and predicting non-coding regulatory small insertions and deletions

A living ex vivo platform for functional, personalized brain cancer diagnosis.

Destin2: Integrative and cross-modality analysis of single-cell chromatin accessibility data.

EPIC: Inferring relevant cell types for complex traits by integrating genome-wide association studies and single-cell RNA sequencing.

Joint gene network construction by single-cell RNA sequencing data.

Nonparametric single-cell multiomic characterization of trio relationships between transcription factors, target genes, and cis-regulatory regions.

Copy Number Variation Detection by Single-Cell DNA Sequencing with SCOPE.

Genome-wide circadian rhythm detection methods: systematic evaluations and practical guidelines

Single-Cell RNA Sequencing Reveals Endothelial Cell Transcriptome Heterogeneity Under Homeostatic Laminar Flow.

WEVar: a novel statistical learning framework for predicting noncoding regulatory variants.

Super-hotspots and -coldspots in the repair of UV-induced DNA damage in the human genome.

A novel deep learning method for predictive modeling of microbiome data.

SCOPE: A Normalization and Copy-Number Estimation Method for Single-Cell DNA Sequencing.

SCDC: bulk gene expression deconvolution by multiple single-cell RNA sequencing references.

SAME-clustering: Single-cell Aggregated Clustering via Mixture Model Ensemble.

Collaborators (3)

Li Chen

Laura Lindsey-Boltz

Wentao Li

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