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Lana Garmire
PeerJ Author & Reviewer
220 Points

Contributions by role

Author 135
Preprint Author 70
Reviewer 15

Contributions by subject area

Bioinformatics
Genomics
Data Mining and Machine Learning
Data Science

Lana Garmire

PeerJ Author & Reviewer

Summary

Dr. Lana Garmire is a tenure track faculty in translational bioinformatics. She obtained the MA degree in Statistics (2005) and PhD degree in Comparartive Biochemistry (Computational Biology focus, 2007), both from UC-Berkeley. She then did her postdoctoral training (2008-2011) under the joint mentorship of Prof. Shankar Subramaniam in the Bioengineering Dept. and Prof. Christopher Glass in the Department of Cellular and Molecular Medicine, UC-San Diego. She worked for one year as a senior computational scientist in Asuragen Inc (a spin-off of Ambion, the RNA company), and won the first bioinformatics NIH SBIR grant for the company. She resumed the tenure-track faculty postion in the University of Hawaii Cancer Center since 2012. Dr. Garmire collaborates with a variety of top researchers nationally and internationally, and has published productively since the faculty appointment. She has received 2.3M funding provided by: Pilot Project Program of NIH/NIGMS COBRE III 5 P30 GM103341-02, Collaboration Enhancement Award from NIMHD 5 U54 MD008149-07, Hawaii Community Foundation, NIH/NIGMS P20 COBRE and NIH/BD2K K01 award.

Bioinformatics Computational Biology Data Science Epidemiology Genomics Statistics Women's Health

Past or current institution affiliations

University of Hawaii at Manoa

Work details

Tenure Track Assistant Professor

University of Hawaii at Manoa
September 2012

Websites

  • GarmireGroup

PeerJ Contributions

  • Articles 1
  • Preprints 1
January 19, 2017
Detecting heterogeneity in single-cell RNA-Seq data by non-negative matrix factorization
Xun Zhu, Travers Ching, Xinghua Pan, Sherman M. Weissman, Lana Garmire
https://doi.org/10.7717/peerj.2888 PubMed 28133571
March 9, 2016 - Version: 2
Detecting heterogeneity in single-cell RNA-Seq data by non-negative matrix factorization
Xun Zhu, Travers Ching, Xinghua Pan, Sherman Weissman, Lana Garmire
https://doi.org/10.7287/peerj.preprints.1839v2