Berger AH, Brooks AN, Wu X et al. High-throughput phenotyping of lung cancer somatic mutations. Cancer Cell. 2016;30(2):214–228.
Howe EA, de Souza A, Lahr DL et al. BioAssay Research Database (BARD): chemical biology and probe-development enabled by structured metadata and result types. Nucleic Acids Res. 2015;43(Database issue):D1163-70.
Mulrooney CA, Lahr DL, Quintin MJ et al. An informatic pipeline for managing high-throughput screening experiments and analyzing data from stereochemically diverse libraries. J Comput Aided Mol Des. 2013;27(5):455-68.
David Lahr, Ph.D.
David Lahr is a principal software engineer in the Cancer Program at the Broad Institute of MIT and Harvard, working under the direction of Aravind Subramanian on the Connectivity Map (CMap) project. He is tasked with running, extending, and maintaining the software that converts the raw data to gene expression measurements and other, more easily interpretable results. He also leads a team of associate computational biologists who work on various related projects, giving them exposure to this process and the CMap tools.
Lahr joined the Broad Institute in 2011 as an application engineer. He became a group leader in data analysis and alliance management before moving to his current post in 2014. Prior to that, he worked for data science/analytics company Tessella as a senior analyst programmer after completing his postdoctoral fellowship with the National Institute of Standards and Technology.
Lahr holds a Ph.D. from MIT in physical chemistry and a B.Sc. in chemistry from the University of Rochester (New York).
Contact David Lahr at firstname.lastname@example.org.