You are here
Ms Yunli (Lily) Shao
Contacts
Yunli Shao (Lily) is a PhD scholar at Australia National University. Her doctoral research interest centres around the eHealth enhanced Chronic Disease Management in a large regional health service. She takes a multidisciplinary approach that encompasses the fields of public health, health informatics and health ICT.
She holds a Bachelor of Science (Honours) degree from Australia National University, that majors in bioinformatics and genetics. During her honours study she investigated the existence of non-embeddability when modelling sequence evolution with Markov models. Lily has worked as a bioinformatician in John Curtin School of Medical Research at Australia National University, where she assisted immunogenomics group in developing systems to gather data using high-performance computing infrastructure that allow processing of massive genomic data.
Lily also has experience working in the public health sector where she plans and undertakes digital health project related tasks. She has coordinated an array of collaborative projects with stakeholders including health professionals, health service managers, software developer, research centres and state government.
Research interests
Lily’s doctoral research investigates the user of eHealth tools and their impact on the chronic care management in ACT Health. The objective is to provide insights into the development of sustainable eHealth solution in chronic care. Her PhD fieldwork consists of three case studies that require close observation and interaction with care coordinators, clinical nurses, allied health professionals and local administrators from chronic disease management unit to provide a rich insight. Her study used qualitative data analysis where all the transcripts from interview were coded to small sections of meaning and result in descriptive themes, categories through an iterative process.
Lily’s research identifies the rationales behind the slow adoption of eHealth implementation in current health care setting, the eHealth innovation impact on people, environment and contexts in which they exit, and necessary steps for preparing the future IT innovation in a similar healthcare setting. The result supports the continued improvement of better chronic care provided in ACT health and the changing needs of stakeholders.
- Massively parallel sequencing of the mouse exome to accurately identify rare, induced mutations: an immediate source for thousands of new mouse models. Andrews TD, Whittle B, Field MA, Balakishnan B, Zhang Y, Shao Y, Cho V, Kirk M, Singh M, Xia Y, Hager J, Winslade S, Sjollema G, Beutler B, Enders A, Goodnow CC. Open Biol. 2012 May;2(5):120061. doi: 10.1098/rsob.120061.
- Rasgrp1 mutation increases naive T-cell CD44 expression and drives mTOR-dependent accumulation of Helios⁺ T cells and autoantibodies. Daley SR, Coakley KM, Hu DY, Randall KL, Jenne CN, Limnander A, Myers DR, Polakos NK, Enders A, Roots C, Balakishnan B, Miosge LA, Sjollema G, Bertram EM, Field MA, Shao Y, Andrews TD, Whittle B, Barnes SW, Walker JR, Cyster JG, Goodnow CC, Roose JP. Elife. 2013 Dec 12;2:e01020. doi: 10.7554/eLife.01020.
- The embedding problem for markov models of nucleotide substitution. Verbyla KL, Yap VB, Pahwa A, Shao Y, Huttley GA. PLoS One. 2013 Jul 30;8(7):e69187. doi: 10.1371/journal.pone.0069187. Print 2013.
