David L. Lahr

The paper creates a proteomic resource profiling 90 drugs in six cell lines, revealing cell-specific responses and enabling integration with transcriptional data to identify therapeutic opportunities.

The paper introduces the GCTx format and associated software packages for efficiently storing and analyzing large dense matrices of perturbation data and annotations.

The paper evaluates RNAi and CRISPR technologies by analyzing gene expression profiles in the Connectivity Map, finding that RNAi has strong off-target effects while CRISPR is more accurate.

The paper introduces the L1000 platform, a high-throughput gene expression profiling method, and reports 1.3 million perturbational profiles expanding the Connectivity Map for drug mechanism discovery and functional annotation.