Abstract
Transcriptional interactions in the cell are modulated by a variety of posttranscriptional and posttranslational mechanisms that make them highly dependent on the molecular context of the specific cell. These include, among others, microRNA-mediated control of transcription factor (TF) mRNA translation and degradation, transcription factor activation by phosphorylation and acetylation, formation of active complexes with one or more cofactors, and mRNA/protein degradation and stabilization processes. Thus, the ability of a transcription factor to regulate its targets depends on a variety of genetic and epigenetic mechanisms, resulting in highly context-dependent regulatory networks. In this chapter, we introduce a step-by-step guide on how to use the MINDy systems biology algorithm (Modulator Inference by Network Dynamics) that we recently developed, for the genome-wide, context-specific identification of posttranscriptional and posttranslational modulators of transcription factor activity.
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Acknowledgments
We would like to thank Pavel Sumazin for providing the insight into the application of MINDy on miRNAs and providing the Figure for it and Paolo Guarnieri for proof reading the document.
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MINDy executables and MATLAB scripts to compute mutual information, kernel width and the statistical threshold for mutual information and \( \Delta I\) can be downloaded from http://wiki.c2b2.columbia.edu/califanolab/index.php/Software.
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Bansal, M., Califano, A. (2012). Genome-Wide Dissection of Posttranscriptional and Posttranslational Interactions. In: Deplancke, B., Gheldof, N. (eds) Gene Regulatory Networks. Methods in Molecular Biology, vol 786. Humana Press. https://doi.org/10.1007/978-1-61779-292-2_8
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DOI: https://doi.org/10.1007/978-1-61779-292-2_8
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