de.mpg.escidoc.pubman.appbase.FacesBean
English
 
Help Guide Disclaimer Contact us Login
  Advanced SearchBrowse

Item

ITEM ACTIONSEXPORT

Released

Journal Article

Expression profiling of drug response-from genes to pathways

MPS-Authors
http://pubman.mpdl.mpg.de/cone/persons/resource/persons50202

Herwig,  Ralf
Bioinformatics (Ralf Herwig), Dept. of Vertebrate Genomics (Head: Hans Lehrach), Max Planck Institute for Molecular Genetics, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons50409

Lehrach,  Hans
Dept. of Vertebrate Genomics (Head: Hans Lehrach), Max Planck Institute for Molecular Genetics, Max Planck Society;

Locator
There are no locators available
Fulltext (public)

Herwig.pdf
(Any fulltext), 2MB

Supplementary Material (public)
There is no public supplementary material available
Citation

Herwig, R., & Lehrach, H. (2006). Expression profiling of drug response-from genes to pathways. Dialogues in Clinical Neuroscience, 8(3), 283-293.


Cite as: http://hdl.handle.net/11858/00-001M-0000-0010-8506-A
Abstract
Understanding individual response to a drug—what determines its efficacy and tolerability—is the major bottleneck in current drug development and clinical trials. Intracellular response and metabolism, for example through cytochrome P- 450 enzymes, may either enhance or decrease the effect of different drugs, dependent on the genetic variant. Microarrays offer the potential to screen the genetic composition of the individual patient. However, experiments are “noisy” and must be accompanied by solid and robust data analysis. Furthermore, recent research aims at the combination of highthroughput data with methods of mathematical modeling, enabling problem-oriented assistance in the drug discovery process. This article will discuss state-of-the-art DNA array technology platforms and the basic elements of data analysis and bioinformatics research in drug discovery. Enhancing single-gene analysis, we will present a new method for interpreting gene expression changes in the context of entire pathways. Furthermore, we will introduce the concept of systems biology as a new paradigm for drug development and highlight our recent research—the development of a modeling and simulation platform for biomedical applications. We discuss the potentials of systems biology for modeling the drug response of the individual patient.