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Joint Research Seminar (11 Dec 2013)



Joint Research Seminar

Genomics Strategic Research Theme
Centre for Genomic Sciences

Analyzing RNA-seq Experiments Using Machine
Learning Tools


Dr Fanny Yuk Yee Leung

Postdoctoral Researcher
Department of Pathology and Laboratory Medicine
Institute for Biomedical Informatics, University of Pennsylvania

11 December 2013 (Wed)

5:00 – 6:00pm

Seminar Room 2, G/F
The Hong Kong Jockey Club Building for Interdisciplinary Research
5 Sassoon Road, Pokfulam, Hong Kong


Recent advances in high-throughput sequencing allow researchers to examine the transcriptome in more detail than ever before. Using a method known as small RNA-sequencing, we can now profile the expression of small regulatory RNAs such as microRNAs and small interfering RNAs with a great deal of sensitivity. However, there are many other types of small RNAs (<50nt) present in the cell, including fragments derived from small nucleolar RNAs, small nuclear RNAs, transfer RNAs, and transposon-derived RNAs. In this talk, I will introduce a machine learning tool called CoRAL (Classification of RNAs by Analysis of Length), a computational method for discriminating between different classes of RNA using small RNA-sequencing data. Not only can CoRAL distinguish between RNA classes with high accuracy, but it also uses features that are relevant to small RNA biogenesis pathways. By doing so, CoRAL can give biologists a glimpse into the characteristics of different RNA processing pathways and how these might differ between tissue types, biological conditions, or even different species.
About the Speaker: 

Fanny Yuk Yee Leung received the BEng degree in Medical Engineering from the University of Hong Kong in 2005. She obtained her PhD degree in the Department of Electrical and Electronic Engineering at the same university in 2009, under the supervision of Prof Y.S. Hung. In 2010, she started her postdoctoral research in Li-San Wang’s lab in the Department of Pathology and Laboratory Medicine, Institute for Biomedical Informatics at the University of Pennsylvania. Her research focuses on developing statistical, machine learning and data mining algorithms for data obtained from RNA-seq experiments, proteomics datasets as well as imaging and clinical records. She is involved in developing tools to better understand the biology of small RNAs, a rising type of non-coding RNA. Besides she also works closely with clinicians on different biomarker discovery projects, including a multi-modal biomarker discovery project for neurodegenerative diseases. She is particularly interested in identifying potential targets for diagnosis and prognosis of different neurodegenerative diseases, such as Alzheimer’s disease and depression, a neuropsychiatric symptom commonly found in the elderly population.



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