Dr. Ruibang Luo

Assistant Professor

Tel: (+852) 2859 2186
Fax: (+852) 2559 8447
Email: rbluo<at>

Dr. Luo joined HKUCS in Jan 2018. He received his B.E. degree in bio-engineering from the South China University of Technology in 2010 and his Ph.D. degree in computational biology from the University of Hong Kong in 2015. He was a postdoctoral fellow in the Center of Computational Biology, McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine. Dr. Luo is a researcher working on bioinformatics software and biological, clinical and pharmaceutical projects. His interdisciplinary research results have been published in peer-reviewed journals such as Nature, Nature Biotechnology, and Bioinformatics. His research covers a diversity of topics in computational biology, from technique-driven research, whose aim is to develop algorithms for two fundamental sequence-analysis problems, 'genome assembly' and 'genome alignment', to hypothesis-driven investigations, such as studying the genetic background of hundreds of cancer cell lines, where the primary aim is to discover and advance clinical knowledge. His research also includes engineering problems for which the accuracy and efficiency of algorithms are crucial, as well as problems for which innovative modeling and analysis of data are more important.

Research Interests

Computational Biology, Cancer Genomics, Parallel Computing

Selected Publications

  • Luo et al., First Draft Genome Sequence of the Pathogenic Fungus Lomentospora prolificans (formerly Scedosporium prolificans), G3: Genes, Genomics, Genetics
  • Luo et al., LRSim: a Linked Reads Simulator generating insights for better genome partitioning, Computational and Structural Biotechnology
  • Luo et al., 16GT: a fast and sensitive variant caller using a 16-genotype probabilistic model, Oxford GigaScience
  • Lee et al., Serine peptidase inhibitor, Kazal type 1 (SPINK1) as a novel downstream effector of the tumorigenic cadherin-17/beta-catenin axis in hepatocellular carcinoma, Cellular Oncology
  • Luo et al., MICA: A fast short-read aligner that takes full advantage of Intel Many Integrated Core Architecture (MIC), BMC Bioinformatics
  • Li et al., MEGAHIT: An ultra-fast single-node solution for large and complex metagenomics assembly via succinct de Bruijn graph, Bioinformatics
  • Ou et al., a web application for interpreting human variations, Bioinformatics
  • Cao et al., De novo assembly of a haplotype-resolved human genome, Nature Biotechnology
  • Ramos et al., Exome sequencing of tumor cell lines: Optimizing for cancer variants, Cancer Research
  • Luo et al., BALSA: integrated secondary analysis for whole-genome and whole-exome sequencing, accelerated by GPU, PeerJ
  • Liu et al., GPU-Accelerated BWT Construction for Large Collection of Short Reads, Arxiv
  • Xie et al., SOAPdenovo-Trans: de novo transcriptome assembly with short RNA-Seq reads, Bioinformatics
  • Luo et al., SOAP3-dp: Fast, Accurate and Sensitive GPU-based Short Read Aligner, PLoS ONE
  • Zhang et al., Oyster genome reveals stress adaptation and shell formation complexity, Nature
  • Liu et al., COPE: an accurate k-mer-based pair-end reads connection tool to facilitate genome assembly, Bioinformatics
  • Luo et al., SOAPdenovo2: An empirically improved memory-efficient short-read de novo assembler, Oxford GigaScience
  • Li et al., Structural variation in two human genomes mapped at single-nucleotide resolution by whole genome de novo assembly, Nature Biotechnology
  • Li et al. , Building the sequence map of the human pan-genome, Nature Biotechnology