Download Installer Version 1.3.1111 (16.6 MB)
Compatible with Windows/Mac/Linux. Source included. Java 6 or higher required to run.

Drug Pair Seeker (DPS) is a Java program that attempts to predict and prioritize pairs of drugs using the Connectivity Map dataset. Users can enter lists of up and down differentially expressed genes from their own experiments to receive a ranked list of drug combinations that would either reverse or aggravate the condition of their cells or tissue using a simple formula shown below.

Please acknowledge DPS in your publications by citing the following reference:
Zhong Y, Chen EY, Liu R, Chuang PY, Mallipattu SK, Tan CM, Clark NR, Deng Y, Klotman PE, Ma'ayan A, He JC. Renoprotective effect of combined inhibition of angiotensin-converting enzyme and histone deacetylase. J Am Soc Nephrol. 2013 Apr;24(5):801-11

(c) 2013 DPS was developed by the Ma'ayan Laboratory at the Icahn School of Medicine at Mount Sinai, New York, NY


Buy an I love DrugPairSeeker T-shirt from here.

Try these other tools developed by the Ma'ayan Lab:
Enrichr- Analyze Gene Lists with over 30 Gene Set Libraries Network2Canvas: a tools to visualize networks on a canvas with enrichment analysis ChIP-X Enrichment Analysis- Database of Transcription Factors and their Target Genes extracted from ChIP-seq and ChIP-chip studies Kinase Enrichment Analysis- Database of Literature-Based Kinase Substrate Interactions LINCS Canvas Browser- Query and Visualize 1000's of L1000 Experiments GATE- Desktop Application for Gene Expression Time-Series Data Analysis Genes2FANs- Tools to Build Networks from List of Genes Sets2Networks- Tool to Build Networks from Gene-Set Libraries Expression2Kinases- Tool to Infer Cell Signaling Pathways from Sets of Differentially Expressed Genes Lists2Networks- Web-Based Platform for Performing Gene Set Enrichment Analyses Genes2Networks- Tool to Build Protein-Protein Interaction Networks from Lists of Genes ESCAPE- Database that Collects, Organizes and Visualizes High-Content Data from Embryonic Stem Cell Research