Lana Garmire, PhD
Associate Professor
DCMB
Medicine
Before joining University of Michigan DCMB department, she rapidly rose to tenure (Dec. 2012 to Jun. 2017) at University of Hawaii Cancer Center, and has become a nationally and internationally recognizable translational bioinformatics scientist leading a multidisciplinary team of computational and experimental human genomics. She has mentored over 40 MD fellows, postdocs, graduate students and undergraduates of various academic backgrounds, in Biology, Mathematics, Phyiscs, (bio)Statistics, Bioengineering, Computer Science and Electrical Engineering. She has served on various NIH study sections. She is an Associate Editor of BMC Bioinformatics and Guest Editor of PLoS Computational Biology.
Projects:
Prediction of diagnosis and delivery of patients with preeclampsia
Research Area(s)
Artificial Intelligence | Basic and Translational cancer research | Bioengineering | Bioinformatics | Biomarkers | Biostatistics | Breast cancer | Clinical research | Computational Biology | Computational Data Science | Critical Care | Data science / Analytics / AI | Deep neural networks | Disease Modeling | Epidemiology | Genetics / Genomics / other OMICS | Global Health | Head & neck cancer | Health Analytics | Health disparities | Infectious Diseases | Metabolic Systems Biology | Metastasis | Natural language processing | Pharmacogenomics | Population Health | Prostate cancer | Sensors and Wearables | Sleep | Systems biology | cardiovascular diseases | machine learning | medical imaging | mental health | mobile health | network analysis | next-gen genomic sequencing | patient outcomes | predictive modeling
Publications
- Alternative splicing promotes tumour aggressiveness and drug resistance in African American prostate cancer
- Corrigendum: Alternative splicing promotes tumour aggressiveness and drug resistance in African American prostate cancer
- Lowered circulating aspartate is a metabolic feature of human breast cancer
Grants
- Co-investigator of: Redefining mesenchymal stem cells: using their cellular and molecular phenotypes to determine their regenerative and therapeutic properties
- Principal investigator of: An Integrative Bioinformatics Platform with Application in Single Cancer Cells
- Principal investigator of: An Integrative Bioinformatics Approach to Study Single Cancer Cell Heterogeneity