Prediction of cardiac transcription networks based on molecular data and complex clinical phenotypes†‡
Abstract
We present an integrative approach combining sophisticated techniques to construct cardiac gene regulatory networks based on correlated
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* Corresponding authors
a
Department of Vertebrate Genomics, Max Planck Institute for Molecular Genetics, Ihnestr. 73, 14195 Berlin, Germany
E-mail:
sperling@molgen.mpg.de
Fax: +49-30-84131699
Tel: +49-30-84131232
b Department of Computational Molecular Biology, Max Planck Institute for Molecular Genetics, Berlin, Germany
c Department of Mathematics and Computer Science, Free University of Berlin, Berlin, Germany
d Department of Pediatric Cardiology, German Heart Center, Berlin, Germany
We present an integrative approach combining sophisticated techniques to construct cardiac gene regulatory networks based on correlated
M. Toenjes, M. Schueler, S. Hammer, U. J. Pape, J. J. Fischer, F. Berger, M. Vingron and S. Sperling, Mol. BioSyst., 2008, 4, 589 DOI: 10.1039/B800207J
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