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Research Interest:
Research Interest:
Genetic Epidemiology | Causal Inference | Machine Learning | Data Analytics | Biomedical Informatics | Systems Biology | Multi-omics and Diseases
Genetic Epidemiology | Causal Inference | Machine Learning | Data Analytics | Biomedical Informatics | Systems Biology | Multi-omics and Diseases
Diseases of Interest: Aging | Cardiovascular Diseases | Brain Diseases | Cancer
Diseases of Interest: Aging | Cardiovascular Diseases | Brain Diseases | Cancer
1. One of Dr. Liu's research interests lies in modeling the rapidly-accumulating big data in biology and medicine for precision medicine. Her unique expertise in both biology and informatics not only allows her to identify interesting biomedical problems to model, but also helps build a better model or develop a new tool with molecular-level biological understanding of the complex data. One main theme of her research is to infer from the multi-omics data the activation states of signaling pathways and utilize such information in precision medicine. She is committed to advancing precision medicine through her work.
1. One of Dr. Liu's research interests lies in modeling the rapidly-accumulating big data in biology and medicine for precision medicine. Her unique expertise in both biology and informatics not only allows her to identify interesting biomedical problems to model, but also helps build a better model or develop a new tool with molecular-level biological understanding of the complex data. One main theme of her research is to infer from the multi-omics data the activation states of signaling pathways and utilize such information in precision medicine. She is committed to advancing precision medicine through her work.
Examples of ongoing projects under this research direction:
Examples of ongoing projects under this research direction:
- Causal discovery of novel genomic variants for diseases using an instance-specific machine learning framework https://biodatacatalyst.nhlbi.nih.gov/fellows/cohort2/
- Supported by the NHLBI BioData Catalyst Fellowship award
- A novel framework for estimating personalized genomic variants of hypertension for precision medicine
- Investigation and deployment of novel Bayesian inference algorithms in the cloud-computing platform of CAVATICA to identify the genomic causes underlying congenital heart defects using Kids First and INCLUDE datasets https://kidsfirstdrc.org/
- Supported by the NHLBI R03 grant
- Supported by the NIH INCLUDE Cloud Credit Program
- Supported by the Center for Biomedical Research at Missouri S&T
- Multi-omics data analysis to reveal the causal signaling networks underlying diseases
2. Dr. Liu is also interested in collaborating with investigators from various disciplines who need help with data analytics and decision making. Her expertise in statistical analysis and machine learning techniques can help identify the pattern in your data for extracting useful knowledge or helping with prediction.
2. Dr. Liu is also interested in collaborating with investigators from various disciplines who need help with data analytics and decision making. Her expertise in statistical analysis and machine learning techniques can help identify the pattern in your data for extracting useful knowledge or helping with prediction.
Examples of ongoing collaborations:
Examples of ongoing collaborations:
- Machine learning-assisted material design
Supported by the Intelligent Systems Center at Missouri S&T
- Machine learning-assisted sensor design
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