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Molecular Interaction Networks to Select Factors for Cell Conversion

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Computational Stem Cell Biology

Part of the book series: Methods in Molecular Biology ((MIMB,volume 1975))

Abstract

The process of identifying sets of transcription factors that can induce a cell conversion can be time-consuming and expensive. To help alleviate this, a number of computational tools have been developed which integrate gene expression data with molecular interaction networks in order to predict these factors. One such approach is Mogrify, an algorithm which ranks transcriptions factors based on their regulatory influence in different cell types and tissues. These ranks are then used to identify a nonredundant set of transcription factors to promote cell conversion between any two cell types/tissues. Here we summarize the important concepts and data sources that were used in the implementation of this approach. Furthermore, we describe how the associated web resource (www.mogrify.net) can be used to tailor predictions to specific experimental scenarios, for instance, limiting the set of possible transcription factors and including domain knowledge. Finally, we describe important considerations for the effective selection of reprogramming factors. We envision that such data-driven approaches will become commonplace in the field, rapidly accelerating the progress in stem cell biology.

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Change history

  • 10 July 2019

    This chapter was published without including the “Conflict of Interest” section given by the author along with the corrected proof.

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Conflict of Interest

Owen Rackham, Julian Gough and Jose Polo are founders and directors of Cell Mogrify Ltd. The other authors do not declare any conflict of interest.

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Authors and Affiliations

  1. Program in Cardiovascular and Metabolic Disorders, Duke-NUS Medical School, Singapore, Singapore

    John F. Ouyang, Uma S. Kamaraj & Owen J. L. Rackham

  2. Department of Anatomy and Developmental Biology, Monash University, Clayton, VIC, Australia

    Jose M. Polo

  3. Development and Stem Cells Program, Monash Biomedicine Discovery Institute, Clayton, VIC, Australia

    Jose M. Polo

  4. Australian Regenerative Medicine Institute, Monash University, Clayton, VIC, Australia

    Jose M. Polo

  5. Medical Research Council (MRC) Laboratory of Molecular Biology, Cambridge Biomedical Campus, Cambridge, UK

    Julian Gough

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  1. John F. Ouyang
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  2. Uma S. Kamaraj
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  3. Jose M. Polo
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Correspondence to Owen J. L. Rackham .

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  1. Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA

    Patrick Cahan

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Ouyang, J.F., Kamaraj, U.S., Polo, J.M., Gough, J., Rackham, O.J.L. (2019). Molecular Interaction Networks to Select Factors for Cell Conversion. In: Cahan, P. (eds) Computational Stem Cell Biology. Methods in Molecular Biology, vol 1975. Humana, New York, NY. https://doi.org/10.1007/978-1-4939-9224-9_16

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  • DOI: https://doi.org/10.1007/978-1-4939-9224-9_16

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