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Virtual ChIP-seq: predicting transcription factor binding by learning from the transcriptome

View ORCID ProfileMehran Karimzadeh, View ORCID ProfileMichael M. Hoffman
doi: https://doi.org/10.1101/168419
Mehran Karimzadeh
1Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada
2Princess Margaret Cancer Centre, Toronto, ON, Canada
3Vector Institute, Toronto, ON, Canada
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Michael M. Hoffman
1Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada
2Princess Margaret Cancer Centre, Toronto, ON, Canada
3Vector Institute, Toronto, ON, Canada
4Department of Computer Science, University of Toronto, Toronto, ON, Canada
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Article Information

doi 
https://doi.org/10.1101/168419
History 
  • February 13, 2019.

Article Versions

  • Version 1 (February 28, 2018 - 17:48).
  • Version 2 (May 11, 2018 - 11:06).
  • You are currently viewing Version 3 of this article (February 13, 2019 - 17:27).
  • View Version 4, the most recent version of this article.
Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. All rights reserved. No reuse allowed without permission.

Author Information

  1. Mehran Karimzadeh1,2,3 and
  2. Michael M. Hoffman1,2,3,4,5
  1. 1Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada
  2. 2Princess Margaret Cancer Centre, Toronto, ON, Canada
  3. 3Vector Institute, Toronto, ON, Canada
  4. 4Department of Computer Science, University of Toronto, Toronto, ON, Canada
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Posted February 13, 2019.
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Virtual ChIP-seq: predicting transcription factor binding by learning from the transcriptome
Mehran Karimzadeh, Michael M. Hoffman
bioRxiv 168419; doi: https://doi.org/10.1101/168419
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Virtual ChIP-seq: predicting transcription factor binding by learning from the transcriptome
Mehran Karimzadeh, Michael M. Hoffman
bioRxiv 168419; doi: https://doi.org/10.1101/168419

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