Assistant Professor

  Biomedical Sciences

  City University of Hong Kong

  Email: lingxi.chen@cityu.edu.hk

I am running CompBioClub at the City University of Hong Kong as an Assistant Professor in the Department of Biomedical Sciences, starting in Dec 2023. I obtained BSc and MSc in Computer Science from University of Nottingham and University College London. I completed my PhD and PostDoc in Computer Science from City University of Hong Kong.

My research primarily focuses on computational biology and computational veterinary medicine algorithms and platforms, specializing in Genome Structural Aberrations, Single-Cell and Spatial Multi-Omics, AI in Healthcare, and Online Biomedical Platforms. I am passionate about applying computer science and artificial intelligence to address critical open challenges in biomedical science.

1. Genomic Structural Aberrations
To develop specialized tools for the detection and analysis of genomic aberrations, such as single nucleotide variations (SNVs), copy number variations (CNVs), and complex structural variations (CSVs). To identify the aberration biomarkers associated with multiple cancers and complex diseases for precision medicine.
2. Single-Cell and Spatial Omics
To design computational algorithms tailored for the analysis of bulk, single-cell, and spatial omics data. To address the challenges such as imputing missing data, dimension reduction, clustering, data integration, and more.
3. AI in Healthcare
To build diagnostic and prognostic AI models for various conditions, including cancer and complex diseases in humans and animals.
4. Online Biomedical Platforms
To create user-friendly online webservers and databases that offer integrated analysis pipelines and interactive visualization interfaces. To enable non-bioinformaticians to explore complex biological data with simple mouse operations.

Deciphering complex breakage-fusion-bridge genome rearrangements with Ambigram
Chaohui Li†, Lingxi Chen†, Guangze Pan, Wenqian Zhang, and Shuai Cheng Li*
Nature Communications. 2023.
[Paper]  [Code] 

Smurf: embedding single-cell rna-seq data with matrix factorization preserving self-consistency
Juhua Pu† , Bingchen Wang† , Xingwu Liu* , Lingxi Chen* , and Shuai Cheng Li*
Briefings in Bioinformatics. 2023.
[Paper]  [Code] 

Incorporating cell hierarchy to decipher the functional diversity of single cells
Lingxi Chen, Shuai Cheng Li*
Nucleic Acids Research. 2022.
[Paper]  [Code] 

Somatic variant analysis suite: copy number variation clonal visualization online platform for large-scale single-cell genomics
Lingxi Chen†, Yuhao Qing†, Ruikang Li†, Chaohui Li†, Hechen Li, Xikang Feng, and Shuai Cheng Li*
Briefings in Bioinformatics. 2021.
[Paper]  [Website] 

Machine learning based early warning system enables accurate mortality risk prediction for covid-19
Yue Gao†, Guang-Yao Cai†, Wei Fang†, Hua-Yi Li†, Si-Yuan Wang†, Lingxi Chen†, Yang Yu, et al.
Nature Communications. 2020.
[Paper]  [Code] 

DeepMF: Deciphering the latent patterns in omics profiles with a deep learning method
Lingxi Chen†, Jiao Xu†, and Shuai Cheng Li∗
BMC Bioinformatics. 2019.
[Paper]  [Code]