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Hepatotoxicity Prediction by Systems Biology Modeling of Disturbed Metabolic Pathways Using Gene Expression Data

  • Oriol López-Massaguer
  • Manuel Pastor
  • Ferran Sanz
  • Pablo Carbonell
Protocol
Part of the Methods in Molecular Biology book series (MIMB, volume 1800)

Abstract

The present method describes a systems biology approach for the in silico predictive modeling of drug toxicity. The data from LINCS were used to determine the type and number of pathways disturbed by each compound and to estimate the extent of disturbance (network perturbation elasticity). Moreover, the most frequently disturbed metabolic pathways and reactions were determined across the studied toxicants. The process was exemplified by successful predictions on various statins. In conclusion, an entirely new approach linking gene expression alterations to the prediction of complex organ toxicity was developed.

Key words

Systems biology Predictive modeling Drug toxicity Hepatotoxicity Gene regulation 

Notes

Acknowledgment

This work was supported by the Innovative Medicines Initiative (IMI) Joint Undertaking under grant agreement no. 115002 (eTOX), resources of which are composed of financial contribution from the European Union’s Seventh Framework Programme (FP7/2007-2013) and EFPIA companies’ in-kind contributions.

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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  • Oriol López-Massaguer
    • 1
  • Manuel Pastor
    • 1
  • Ferran Sanz
    • 1
  • Pablo Carbonell
    • 2
  1. 1.Research Programme on Biomedical Informatics (GRIB), Institut Hospital del Mar d’Investigacions Mèdiques (IMIM), Dept. of Experimental and Health SciencesUniversitat Pompeu FabraBarcelonaSpain
  2. 2.Manchester Centre for Fine and Speciality Chemicals (SYNBIOCHEM), Manchester Institute of BiotechnologyUniversity of ManchesterManchesterUK

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