- Single-cell RNA-seq analysis
- Gene regulation
- Systems biology
- Artificial intelligence 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). Prior to joining HKU, he was the Head of Bioinformatics and Systems Medicine Laboratory at the Victor Chang Cardiac Research Institute in Sydney, Australia. He was also a Conjoint Senior Lecturer at the University of New South Wales (UNSW) in Sydney. Dr Ho completed his BSc (Hon 1, Medal) and PhD in Bioinformatics from the University of Sydney, and undertook postdoctoral research at the Harvard Medical School. His research focuses on developing fast and reliable bioinformatics methods to identify the genetic cause and mechanism of various human diseases using a range of approaches such as whole genome sequencing, single-cell RNA-seq, ChIP-seq, machine learning, systems biology, cloud computing, and software testing and quality assurance. Dr Ho has over 70 publications, including first or senior-author papers in leading journals such as Nature, Genome Biology, Nucleic Acids Research and Science Signaling. His research excellence has been recognized by the 2015 NSW Ministerial Award for Rising Star in Cardiovascular Research, the 2015 Australian Epigenetics Alliance’s Illumina Early Career Research Award, and the 2016 Young Tall Poppy Science Award.
The Ho Laboratory focuses on the use of bioinformatics and systems biology approaches to tackle longstanding problems in basic and translational medicine. Most projects in this laboratory involve integrative analysis next-generation sequencing (NGS) data such as single-cell RNA-seq, ChIP-seq, and whole genome sequencing data. Here are some major research themes. Multiple projects are available under each theme. Students interested in joining his lab please contact Dr Ho.
- Bioinformatics algorithms for single cell RNA-seq analysis. 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 cutting-edge bioinformatics methods to analyze a range of scRNA-seq data to answer important biological questions.
- Scalable 3D virtual reality visualization of biological data. Visualizations of biological data is critical in the analysis and interpretation of large biological data, such as single-cell RNA-seq data and 3D biomedical imaging data. In this project, we will use state-of-the-art virtual reality (VR) technology to construct effective and scalable 3D visualizations of various biological data. This project is ideally suited for students who have an interest in large-scale data visualization and virtual reality.
- Wearable device, physical activity and heart rate dynamics. Being able to track the change in cardiac function in real time under a person’s realistic physical activity profile is now feasible due to the wide availability of consumer-grade 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 cardiac function and disease risk.
- Causal disease mutation identification in whole genome sequencing data. Whole genome sequencing is now highly cost-effective. Nonetheless, while a large number of sequence or structural variants can be identified in each individual, it is often difficult to pin-point the disease causing genetic mutation. In this project, we will develop novel bioinformatics methods to integrate diverse functional genomic data to prioritize likely causal mutations that underlie a disease. Our group is particularly interested in the genetic cause of congenital heart disease.
- A cloud-based approach for incorporating scalability in genome informatics. NGS enables low-cost, high-throughput sequencing for a wide variety of genome-wide scale analysis of the genome, epigenome and the transcriptome. However, with this vast quantity of data, we are faced with unprecedented technical challenges in terms of computational analysis and storage of these data. The goal of this research project is to investigate the use of cloud computing technology to deal with these challenges.
- 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 organization. Nature, 512(7515), 449-52 (*co-first author)
- Lin P, Troup M, Ho JWK (2017) CIDR: Ultrafast and accurate clustering through imputation for single-cell RNA-seq data. Genome Biology, 18, 59
- 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 data. Nucleic Acids Research, 45 (9): e67
- Yang A, Troup M, Lin P, Ho JWK (2017) Falco: A quick and flexible single-cell RNA-seq processing framework on the cloud. Bioinformatics, 33(5), 767-769
- 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 Supplementation. New England Journal of Medicine, 377, 544-552
- Alekseyenko AA*, Ho JWK*, Peng S*, Gelbart M, Tolstorukov M, Plachetka A, Kharchenko PV, Jung YL, Gorchakov AA, Larschan E, Gu T, Minoda A, Riddle NC, Schwartz YB,Elgin SCR, Karpen GH, Pirrotta V, Kuroda MI, Park PJ (2012) Sequence-specific targeting of dosage compensation in Drosophila favors an active chromatin context. PLoS Genetics, 8, e1002646 (*co-first author)
- Lachke SA*, Ho JWK*, Kryukov GV*, O'Connell DJ, Aboukhalil A, Bulyk M, Park PJ, Maas RL (2012) iSyTE: integrated systems tool for eye gene discovery. Investigative Ophthalmology & Visual Sciences, 53, 1617-1627 (*co-first author)
- 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 organogenesis. Science Signaling, 5, ra4 (*co-first author)
- Ho JWK, Bishop E, Kharchenko PV, Negre N, White K, Park PJ (2011) ChIP-chip versus ChIP-seq: Lessons for experimental design and data analysis. BMC Genomics, 12, 134
- Chen TY, Ho JWK^, Liu H, Xie X (2009) An innovative approach for testing bioinformatics programs using metamorphic testing. BMC Bioinformatics, 10, 24 (^corresponding author)
- Ho JWK, Stefani M, dos Remedios CG, Charleston MA (2008) Differential variability analysis of gene expression and its application to human diseases, Bioinformatics, 24, i390-i398
- 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
- 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)