Research Projects
Analysis of Genomic Data for Clinical Diagnosis and Personalised Treatment

Objective and Significance:

Genomic medicine promises molecular diagnosis, disease risk prediction, and personalized treatment. To fulfill this promise, being able to analyze large amount of sequencing and other genomic data and being able to connect the link between genotype and phenotype is essential. With the decrease in cost of genomic sequencing and other high-throughput platforms, data generation becomes easier everyday but valid analysis, interpretation and application of the data remain a huge challenge.

In this proposal, we plan to train students to apply data analysis tools to whole genome, whole exome sequencing data and other high throughput data and to learn to make a connection between data and clinical manifestations and personalized treatment.

Being able to interpret data is even more important for a future clinician than being able to master some techniques in a laboratory, and it is an area that requires the most investment in the post-genome era.

Research Plan and Methodology:

Our laboratory possesses data on SNP genotyping and whole exome sequencing from clinical samples. The student is going to work closely with students majoring in bioinformatics and genetics in the lab to learn to process genomic data and to make the connection between genomic changes and clinical diagnosis, disease risk prediction and personalized treatment.

Students with certain skills in computation and statistics is preferred but not required.

Prof W Yang, Department of Paediatrics and Adolescent Medicine

Prof Yang received medical training in China and research training in the US before joining the University of Hong Kong in 2006. His research focus on the genetics of complex diseases and Mendelian diseases, making use of data from SNP genotyping, whole exome/genome sequencing, RNA-seq, ATAC-seq, and CRISP-Cas9 screening. Incoming postgraduate students will be working in an environment allowing for learning of both bioinformatic data analysis skills and cutting-edge experimental technologies.

Biography
Laboratory Homepage
yangwl@hku.hk

For more information or to express interest for this project, please email the supervisor or the specified contact point in the project description.  Interested candidates are advised to enclose with your email:

1. your CV,
2. a brief description of your research interest and experience, and
3. two reference letters (not required for HKUMed UG students seeking MRes[Med]/URIS projects).

Information on the research programme, funding support and admission documentations could be referenced online at the Research Postgraduate Admissions website. General admission enquiries should be directed to rpgmed@hku.hk.

HKUMed MBBS students interested in the Master of Research in Medicine (MRes[Med]) programme may visit the programme website for more information.  

HKUMed UG students interested in the Undergraduate Research Internship Scheme (URIS) may visit the scheme’s website for more information.