Constructing a compound Mode-of-Action network for personalized drug effectiveness prediction

Chifeng Ma, Hung I.Harry Chen, Yufei Huang, Yidong Chen

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations

Abstract

The problem of large scale computational drug screening is considered in this paper. A new concept of Mode-of-Action (MoA) network, or MoNet, is introduced to model the relationship of therapeutic effectiveness between different drugs. A new algorithm for constructing Mode-of-Action groups and subsequently MoNet based on gene expression profile of drug treatment is proposed. The algorithm has been applied to the data from the Connectivity Map (cMap) project and a cMap MoNet was obtained. A new drug effectiveness prediction algorithm based on MoNet is also developed and applied to an independent breast cancer data set. The prediction result shows improvement in precision over cMap.

Original languageEnglish (US)
Title of host publication2010 ACM International Conference on Bioinformatics and Computational Biology, ACM-BCB 2010
Pages520-528
Number of pages9
DOIs
StatePublished - Oct 25 2010
Event2010 ACM International Conference on Bioinformatics and Computational Biology, ACM-BCB 2010 - Niagara Falls, NY, United States
Duration: Aug 2 2010Aug 4 2010

Publication series

Name2010 ACM International Conference on Bioinformatics and Computational Biology, ACM-BCB 2010

Other

Other2010 ACM International Conference on Bioinformatics and Computational Biology, ACM-BCB 2010
CountryUnited States
CityNiagara Falls, NY
Period8/2/108/4/10

Keywords

  • Connectivity map
  • Drug effectiveness prediction
  • MoA networks
  • Mode of Action (MoA)

ASJC Scopus subject areas

  • Biomedical Engineering
  • Health Information Management

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  • Cite this

    Ma, C., Chen, H. I. H., Huang, Y., & Chen, Y. (2010). Constructing a compound Mode-of-Action network for personalized drug effectiveness prediction. In 2010 ACM International Conference on Bioinformatics and Computational Biology, ACM-BCB 2010 (pp. 520-528). (2010 ACM International Conference on Bioinformatics and Computational Biology, ACM-BCB 2010). https://doi.org/10.1145/1854776.1854876