Applications:
Bioinformatics, Clinical Research, Epidemiology, Genetics, Genomics, Medical Imaging, Medical Informatics, Population Sciences, Public Health, Research Reproducibility
Methodologies:
Artificial Intelligence, Classification, Computational Tools for Data Science, Deep Learning, Heterogeneous Data Integration, High-Dimensional Data Analysis, Image Data Processing and Analysis, Machine Learning, Missing Data and Imputation, Network Analysis, Predictive Modeling, Sparse Data Analysis, Spatio-Temporal Data Analysis

Lana Garmire

Associate Professor

Computational medicine and Bioinformatics


Affiliation(s):

Biostatistics

My research interest lies in applying data science for actionable transformation of human health from the bench to bedside. Current research focus areas include cutting edge single-cell sequencing informatics and genomics; precision medicine through integration of multi-omics data types; novel modeling and computational methods for biomarker research; public health genomics. I apply my biomedical informatics and analytical expertise to study diseases such as cancers, as well the impact of pregnancy/early life complications on later life diseases.