Ziqi Zhang

I’m a Ph.D. student in the School of Computational Science and Engineering, Georgia Institute of Technology. My advisor is Dr. Xiuwei Zhang.

I’m generally interested in developing machine learning algorithms to study cell regulatory mechanisms. My main research focuses are:

Integrating biological information from single-cell multi-omics datasets and single-cell datasets across experimental conditions, and obtaining new biological insight from the integration study.
Studying cell regulatory mechanisms including gene regulatory network, cross-modalities association network with graph learning algorithms.

My contact information:

Email: ziqi.zhang@gatech.edu
Address: CODA Building, IDEaS, Georgia Tech

My CV: Download through the link.

News

May 20, 2024	I will be interning at Genentech South San Francisco office this summer, I will be primarily working on spatial transcriptomics. Looking forward to meeting you there.
Jan 30, 2024	Our paper scDisInFact: disentangled learning for integration and prediction of multi-batch multi-condition single-cell RNA-sequencing data is accepted by Nature Communications, please check it out with the link.
Jan 14, 2023	Our paper scMoMaT jointly performs single cell mosaic integration and multi-modal bio-marker detection is accepted by Nature Communications, please check it out with the link.
Jun 28, 2022	Our paper scDART: integrating unmatched scRNA-seq and scATAC-seq data and learning cross-modality relationship simultaneously is accepted by Genome Biology, please check it out with the link.
Nov 3, 2021	Our abstract Integrating unmatched scRNA-seq and scATAC-seq data and learning cross-modality relationship simultaneously is accepted as Spotlight presentation in MLCB 2021. Look forward to see you there!

Selected publications

scDisInFact

scDisInFact: disentangled learning for integration and prediction of multi-batch multi-condition single-cell RNA-sequencing data

Ziqi Zhang, Xinye Zhao, Mehak Bindra, and 2 more authors

Nature Communications 2024

Bib

@article{zhang2024scdisinfact,
  title = {scDisInFact: disentangled learning for integration and prediction of multi-batch multi-condition single-cell RNA-sequencing data},
  author = {Zhang, Ziqi and Zhao, Xinye and Bindra, Mehak and Qiu, Peng and Zhang, Xiuwei},
  journal = {Nature Communications},
  volume = {15},
  number = {1},
  pages = {912},
  year = {2024},
  publisher = {Nature Publishing Group UK London},
}

scMoMaT

scMoMaT jointly performs single cell mosaic integration and multi-modal bio-marker detection

Ziqi Zhang, Haoran Sun, Ragunathan Mariappan, and 7 more authors

Nature Communications 2023

Bib

@article{zhang2023scmomat,
  title = {scMoMaT jointly performs single cell mosaic integration and multi-modal bio-marker detection},
  author = {Zhang, Ziqi and Sun, Haoran and Mariappan, Ragunathan and Chen, Xi and Chen, Xinyu and Jain, Mika S and Efremova, Mirjana and Teichmann, Sarah A and Rajan, Vaibhav and Zhang, Xiuwei},
  journal = {Nature Communications},
  volume = {14},
  number = {1},
  pages = {384},
  year = {2023},
  publisher = {Nature Publishing Group UK London},
}

CeSpGRN

Inferring cell-specific gene regulatory networks from single cell gene expression data

Ziqi Zhang, Jongseok Han, Le Song, and 1 more author

BioRxiv 2022

Bib

@article{zhang2022GRN,
  title = {Inferring cell-specific gene regulatory networks from single cell gene expression data},
  author = {Zhang, Ziqi and Han, Jongseok and Song, Le and Zhang, Xiuwei},
  journal = {BioRxiv},
  year = {2022},
  publisher = {Cold Spring Harbor Laboratory},
}

CellPath

Inference of high-resolution trajectories in single-cell RNA-seq data by using RNA velocity

Ziqi Zhang, and Xiuwei Zhang

Cell Reports Methods 2021

Bib

@article{zhang2021inference,
  title = {Inference of high-resolution trajectories in single-cell RNA-seq data by using RNA velocity},
  author = {Zhang, Ziqi and Zhang, Xiuwei},
  journal = {Cell Reports Methods},
  volume = {1},
  number = {6},
  pages = {100095},
  year = {2021},
  publisher = {Elsevier},
}

scDART

scDART: integrating unmatched scRNA-seq and scATAC-seq data and learning cross-modality relationship simultaneously

Ziqi Zhang, Chengkai Yang, and Xiuwei Zhang

Genome Biology Jun 2022

Bib

@article{Zhang2022scDART,
  title = {scDART: integrating unmatched scRNA-seq and scATAC-seq data and learning cross-modality relationship simultaneously},
  author = {Zhang, Ziqi and Yang, Chengkai and Zhang, Xiuwei},
  journal = {Genome Biology},
  year = {2022},
  month = jun,
  day = {27},
  volume = {23},
  number = {1},
  pages = {139},
  issn = {1474-760X},
  doi = {10.1186/s13059-022-02706-x},
  url = {https://doi.org/10.1186/s13059-022-02706-x},
}

VeloSim

VeloSim: Simulating single cell gene-expression and RNA velocity

Ziqi Zhang, and Xiuwei Zhang

BioRxiv Jun 2021

Bib

@article{zhang2021velosim,
  title = {VeloSim: Simulating single cell gene-expression and RNA velocity},
  author = {Zhang, Ziqi and Zhang, Xiuwei},
  journal = {BioRxiv},
  year = {2021},
  publisher = {Cold Spring Harbor Laboratory},
}