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Predicting A/B compartments from histone modifications using deep learning

Suchen Zheng, Nitya Thakkar, Hannah L. Harris, Megan Zhang, Susanna Liu, Mark Gerstein, Erez Lieberman-Aiden, M. Jordan Rowley, William Stafford Noble, Gamze Gürsoy, Ritambhara Singh
doi: https://doi.org/10.1101/2022.04.19.488754
Suchen Zheng
1Department of Computer Science, Brown University
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Nitya Thakkar
1Department of Computer Science, Brown University
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Hannah L. Harris
2Department of Genetics, Cell Biology and Anatomy, University of Nebraska Medical Center
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Megan Zhang
5Data Science and Statistics, Yale University
6Molecular, Cellular, and Developmental Biology, Yale University
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Susanna Liu
5Data Science and Statistics, Yale University
6Molecular, Cellular, and Developmental Biology, Yale University
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Mark Gerstein
3Computational Biology and Bioinformatics, Yale University
4Molecular Biophysics & Biochemistry, Yale University
5Data Science and Statistics, Yale University
7Computer Science, Yale University
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Erez Lieberman-Aiden
8Department of Genetics, Baylor College of Medicine
9Department of Computer Science, Rice University
10Computational and Applied Mathematics, Rice University
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M. Jordan Rowley
2Department of Genetics, Cell Biology and Anatomy, University of Nebraska Medical Center
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William Stafford Noble
11Department of Genome Sciences, University of Washington
12Paul G. Allen School of Computer Science and Engineering, University of Washington
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Gamze Gürsoy
13Department of Biomedical Informatics, Columbia University
14New York Genome Center
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  • For correspondence: ritambhara@brown.edu
Ritambhara Singh
1Department of Computer Science, Brown University
15Center for Computational Molecular Biology, Brown University
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  • For correspondence: ritambhara@brown.edu
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Article Information

doi 
https://doi.org/10.1101/2022.04.19.488754
History 
  • April 19, 2022.

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  • You are currently viewing Version 1 of this article (April 19, 2022 - 09:32).
  • View Version 2, 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. It is made available under a CC-BY-NC 4.0 International license.

Author Information

  1. Suchen Zheng1,#,
  2. Nitya Thakkar1,#,
  3. Hannah L. Harris2,
  4. Megan Zhang5,6,
  5. Susanna Liu5,6,
  6. Mark Gerstein3,4,5,7,
  7. Erez Lieberman-Aiden8,9,10,
  8. M. Jordan Rowley2,
  9. William Stafford Noble11,12,
  10. Gamze Gürsoy13,14,* and
  11. Ritambhara Singh1,15,*
  1. 1Department of Computer Science, Brown University
  2. 2Department of Genetics, Cell Biology and Anatomy, University of Nebraska Medical Center
  3. 3Computational Biology and Bioinformatics, Yale University
  4. 4Molecular Biophysics & Biochemistry, Yale University
  5. 5Data Science and Statistics, Yale University
  6. 6Molecular, Cellular, and Developmental Biology, Yale University
  7. 7Computer Science, Yale University
  8. 8Department of Genetics, Baylor College of Medicine
  9. 9Department of Computer Science, Rice University
  10. 10Computational and Applied Mathematics, Rice University
  11. 11Department of Genome Sciences, University of Washington
  12. 12Paul G. Allen School of Computer Science and Engineering, University of Washington
  13. 13Department of Biomedical Informatics, Columbia University
  14. 14New York Genome Center
  15. 15Center for Computational Molecular Biology, Brown University
  1. ↵*Co-corresponding authors; ritambhara{at}brown.edu
  1. ↵# Equal contribution

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Predicting A/B compartments from histone modifications using deep learning
Suchen Zheng, Nitya Thakkar, Hannah L. Harris, Megan Zhang, Susanna Liu, Mark Gerstein, Erez Lieberman-Aiden, M. Jordan Rowley, William Stafford Noble, Gamze Gürsoy, Ritambhara Singh
bioRxiv 2022.04.19.488754; doi: https://doi.org/10.1101/2022.04.19.488754
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Predicting A/B compartments from histone modifications using deep learning
Suchen Zheng, Nitya Thakkar, Hannah L. Harris, Megan Zhang, Susanna Liu, Mark Gerstein, Erez Lieberman-Aiden, M. Jordan Rowley, William Stafford Noble, Gamze Gürsoy, Ritambhara Singh
bioRxiv 2022.04.19.488754; doi: https://doi.org/10.1101/2022.04.19.488754

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