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Dr HO, Joshua Wing Kei 何永基

Dr HO, Joshua Wing Kei 何永基

  • BSc (Hon), PhD (Sydney)
  • Associate Professor
L4-44, Laboratory Block, 21 Sassoon Road, Hong Kong
+852 3917 9512
+852 2855 9730
  • Bioinformatics
  • Single-cell RNA-seq analysis
  • Gene regulation
  • Systems biology
  • Gut microbiome metagenomics
  • Artificial intelligence and IoT in medicine
  • Big data for biomedical sciences

Dr Ho is an Associate Professor in the School of Biomedical Sciences at the University of Hong Kong (HKU). He completed his BSc (Hon 1, Medal) and PhD in Bioinformatics from the University of Sydney, and undertook postdoctoral training a the Harvard Medical School. Prior to joining HKU, Dr Ho was the Head of Bioinformatics and Systems Medicine Laboratory at the Victor Chang Cardiac Research Institute, in Sydney Australia. His research focuses on developing and applying cutting-edge computational methods for single cell RNA-seq analysis, metagenomics, and digital health. Dr Ho has over 90 publications, including first or senior papers in leading journals such as Nature, Genome Biology, Nucleic Acids Research and Science Signaling. Dr Ho is also currently the Academic Lead of the Bioinformatics Core of the Centre for PanorOmic Sciences (CPOS) at HKU. He is an Executive Editor of the journal Biophysical Reviews.

The Ho Laboratory focuses on the use of bioinformatics and systems biology approaches to tackle longstanding problems in basic and translational medicine. A range of specific research projects can be developed within the broad theme of scalable big data analytics for healthcare translation. Here are some major research themes. Multiple projects are available under each theme:

  • Scalable single cell data analytics. Single-cell RNA sequencing (scRNA-Seq) enables researchers to study heterogeneity among tens of thousands of individual cells and define cell types from a transcriptomic perspective. However, fast and reliable analysis of these large and noisy data requires new statistical and computational considerations. In this project we will develop scalable bioinformatics methods to analyze a range of scRNA-seq data to answer important biological questions.
  • Microbiome functional systems biology through metagenomic and multi-omic data analysis. Our laboratory is developing computational and statistical tools that can efficient process large metagenomic data, and integrate them with other omics or deep phenotyping data. Our goal is to understand how the microbiome found in specific location of the body, e.g., the gut, can affect a person's health.
  • Medical artificial intelligence, mobile health and wearable devices. Being able to track the changes of a person's physiological parameters in real time is now increasingly feasible due to the wide availability of consumer-grade smartphones and wearable devices (e.g., fitbit, AppleWatch, etc). Our group is developing new big data machine-learning algorithms extract, de-noise, analyze and correlate physical activity data and heart rate dynamics. Our long-term goal is to establish new non-invasive screening tools to monitor a person's health status.
  1. Tam PPL, Ho JWK (2020) Cellular diversity and lineage trajectory: insights from mouse single cell transcriptomesDevelopment, 147, dev179788
  2. Yang A, Kishore A, Phipps B, Ho JWK (2019) Cloud accelerated alignment and assembly of full-length single-cell RNA-seq data using FalcoBMC Genomics, 20, 927
  3. Wang Q, Ye J, Fang D, Lv L, Wu W, Shi D, Li Y, Yang L, Bian X, Wu J, Jiang X, Wang K, Wang W, Hodson MP, Thibaut LM, Ho JWK, Giannoulatou E^, Li L^ (2020) Multi-omic profiling reveals associations between the gut mucosal microbiome, the metabolome, and host DNA methylation associated gene expression in patients with colorectal cancerBMC Microbiology, 20, 83
  4. Humphreys DT, Fossat N, Demuth M, Tam PPL, Ho JWK (2019) Ularcirc: Visualisation and enhanced analysis of circular RNAs via back and canonical forward splicingNucleic Acids Research, 47(20), e123
  5. Lin P, Troup M, Ho JWK (2017) CIDR: Ultrafast and accurate clustering through imputation for single-cell RNA-seq data. Genome Biology, 18, 59
  6. Szot PS, Yang A, Wang X, Parsania C, Röhm W, Wong KH, Ho JWK (2017) PBrowse: A web-based platform for real-time collaborative exploration of genomic dataNucleic Acids Research, 45 (9): e67
  7. Shi H, Enriquez A, Rapadas M, Martin EMMA, Wang R, Moreau J, Lim CK, Szot JO, Ip E, Hughes J, Sugimoto K, Humphreys D, McInerney-Leo AM, Leo PJ, Maghzal GJ, Halliday J, Smith J, Colley A, Mark PR, Collins F, Sillence DO, Winlaw DS, Ho JWK, Guillemin GJ, Brown MA, Kikuchi K, Thomas PQ, Stocker R, Giannoulatou E, Chapman G, Duncan EL, Sparrow DB, Dunwoodie SL (2017) NAD Deficiency, Congenital Malformations and Niacin SupplementationNew England Journal of Medicine, 377, 544-552
  8. Yang A, Troup M, Lin P, Ho JWK (2017) Falco: A quick and flexible single-cell RNA-seq processing framework on the cloudBioinformatics, 33(5), 767-769
  9. Ho JWK*, Jung YL*, Liu T*, Alver BH, Lee S, Ikegami K, Sohn KA, Minoda A, Tolstorukov MY, Appert A, Parker SCJ, Gu T, Kundaje A, Riddle NC, Bishop E, Egelhofer TA, Hu SS, Alekseyenko AA, Rechtsteiner A, Asker D, Belsky JA, Bowman SA, Chen QB, Chen RAJ , Day DS, Dong Y, Dose AC, Duan X, Epstein CB, Ercan S, Feingold EA, Ferrari F, Garrigues JM, Gehlenborg N, Good PJ, Haseley P, He D, Herrmann M, Hoffman MM, Jeffers TE, Kharchenko PV, Kolasinska-Zwierz P, Kotwaliwale CV, Kumar N, Langley SA, Larschan EN, Latorre I, Libbrecht MW, Lin X, Park R, Pazin MJ, Pham HN, Plachetka A, Qin B, Schwartz YB, Shoresh N, Stempor P, Vielle A, Wang C, Whittle CM, Xue H, Kingston RE, Kim JH, Bernstein BE, Dernburg AF, Pirrotta V, Kuroda MI, Noble WS, Tullius TD, Kellis M, MacAlpine DM, Strome S, Elgin SCR, Liu XS, Lieb JD, AhringerJ, Karpen GH, Park PJ (2014) Comparative analysis of metazoan chromatin organizationNature, 512(7515), 449-52 (*co-first author)
  10. O'Connell DJ*, Ho JWK*, Mammoto T, Turbe-Doan A, O'Connell JT, Haseley PS, Koo S, Kamiya N, Ingber DE, Park PJ, Maas RL (2012) A Wnt-Bmp feedback circuit controls intertissue signaling dynamics in tooth organogenesisScience Signaling, 5, ra4 (*co-first author)

As PI:

  • NHMRC Career Development Fellowship: Discovering the genetic causes of congenital heart disease using systems biology
  • Human Frontier Science Program Young Investigator Grant: Predicting cell type specific signaling pathway response
  • Ramaciotti Establishment Grant: Epigenomic and transcriptomic analysis of host-pathogen interactions at the single-cell level
  • Amazon Web Service (AWS) in Education Grant: Scalable and collaborative single-cell genomic analysis on the cloud

As Co-I:

  • NHMRC Project Grant: Identifying gene required for vertebral column and heart formation
  • NSW Genomics Collaborative Grant: Discovering the genetic causes of inherited heart diseases in babies
  • Best Paper Award, International Conference on Quality Software (2009)
  • Ruth K Kirschstein National Research Service Award, NIH, USA (2010)
  • Rod Richards Fellowship, Australian Academy of Science (2014)
  • Illumina Early Career Researcher Award, Australian Epigenetics Alliance (2015)
  • NSW Ministerial Award for Rising Stars in Cardiovascular Research (2015)
  • Young Tall Poppy Science Award, Australian Institute of Policy and Science (2016)
  • Career Development Fellowship, National Health and Medical Research Council (2016)
    Future Leader Fellowship, National Heart Foundation of Australia (2016)
  • Winner, The Bioinformatics Peer Prize II, The Thinkable Academy (2017)

Last updated: 2020-07-03