Dr. ZHANG, Eric Lu
Dr. ZHANG, Eric Lu

BEng, MPhil, PhD
Assistant Professor, Department of Computer Science


Dr. Lu (Eric) Zhang is an Assistant Professor of Computer Science at Hong Kong Baptist University (HKBU). Before joining HKBU, he was a postdoctoral fellow in the Department of Computer Science and Pathology at Stanford University, supervised by Prof. Serafim Batzoglou and Prof. Arend Sidow. He received an MPhil degree from Li Ka Shing Faculty of Medicine at The University of Hong Kong and a Ph.D. degree in Computer Science from City University of Hong Kong in 2012 and 2016, respectively. In 2008, he received a B.Eng in Software Engineering from Tianjin University. In 2015, he was a visiting scholar in the Department of Mathematics at UC Berkeley and worked with Prof. Stephen Smale. He has an interdisciplinary background in genomics, statistics and computer science. His primary research interests are computational genomics, bioinformatics and machine learning. His team works specifically on 1. developing computational tools to analyze advanced high-throughput sequencing data from metagenome and human genome; 2. developing deep learning models to understand metagenome and single-cell multiomics data. His work has been published in several top-tier journals, such as PNAS, Briefings in Bioinformatics, NAR Genomics and Bioinformatics, GigaScience, Nature Communications, Nature Genetics, Genome Biology, Bioinformatics, etc.

Research Interests

  • Computational Genomics
  • Algorithms for the advanced high-throughput sequencing technologies
  • Deep learning in Genomics
  • Network Biology
  • Machine Learning

Selected Publications

  • Yu Xu, Jiaxing Chen, Aiping Lyu*, William K Cheung*Lu Zhang*. dynDeepDRIM: a dynamic deep learning model to infer direct regulatory interactions using single cell time-course gene expression data. Briefings in Bioinformatics 2022(*Corresponding Author)
  • Jiaxing Chen, Chinwang Cheong, Liang Lan, Xin Zhou, Jiming Liu, Aiping Lyu, William K Cheung*, Lu Zhang*. DeepDRIM: a deep neural network to reconstruct cell-type-specific gene regulatory network using single-cell RNA-Seq Data. RECOMB-Seq 2021 and Briefings in Bioinformatics 2021. (*Corresponding Author)
  • Xin Zhou, Lu Zhang, Ziming Weng, David L. Dill, Arend Sidow. Aquila enables reference-assisted diploid personal genome assembly and comprehensive variant detection based on linked reads. Nature Communications 2021.
  • Chao Yang, Debajyoti Chowdhury, Zhenmiao Zhang, William K. Cheung, Aiping Lu, ZhaoXiang Bian, Lu Zhang*. A review of computational tools for generating metagenome-assembled genomes from metagenomic sequencing data. Computational and Structural Biotechnology Journal 2021.
  • Lu Zhang*, Xiaodong Fang et al. A Comprehensive Investigation of Metagenome Assembly by Linked-Read Sequencing. Microbiome(*Corresponding Author)
  • Lu Zhang, Xin Zhou, Ziming Weng, Arend Sidow. De novo diploid genome assembly for genome-wide structural variant detection. NAR Genomics and Bioinformatics 2020.
  • Lu Zhang, Xin Zhou, Ziming Weng, Arend Sidow. Assessment of human diploid genome assembly with 10x Linked-Reads data. GigaScience 2019.
  • JiFeng Guo, Lu Zhang et al. De novo coding mutations contribute to early onset Parkinson's disease. Proceedings of the National Academy of Sciences of the United States of America, 2018 (Joint First Author).
  • Xin Zhou, Serafim Batzoglou, Arend Sidow, Lu Zhang*. HAPDeNovo: a haplotype-based approach for filtering and phasing de novo mutations in linked read sequencing data. BMC Genomics, 2018 (Corresponding Author).
  • Lu Liu, Lu Zhang et al. The SNP-set based association study identifies ITGA1 as a susceptiblity gene of attention-deficit/hyperactivity disorder in Han Chinese. Translational Psychiatry, 2017 (Joint First Author).
  • Xueyan Li, Dingding Fan, Wei Zhang, Guichun Liu, Lu Zhang, et al. Outbred genome sequencing and CRISPR/Cas9 gene editing in butterflies. Nature Communications, 2015 (Joint First Author).