Skip to main content
bioRxiv
  • Home
  • About
  • Submit
  • ALERTS / RSS
Advanced Search
New Results

An optimal set of inhibitors for Reverse Engineering via Kinase Regularization

Scott Rata, Jonathan Scott Gruver, Natalia Trikoz, View ORCID ProfileAlexander Lukyanov, Janelle Vultaggio, Michele Ceribelli, Craig Thomas, View ORCID ProfileTaran Singh Gujral, View ORCID ProfileMarc W. Kirschner, View ORCID ProfileLeonid Peshkin
doi: https://doi.org/10.1101/2020.09.26.312348
Scott Rata
1Department of Systems Biology, Harvard Medical School, Boston, MA 02115, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Jonathan Scott Gruver
1Department of Systems Biology, Harvard Medical School, Boston, MA 02115, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Natalia Trikoz
1Department of Systems Biology, Harvard Medical School, Boston, MA 02115, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Alexander Lukyanov
1Department of Systems Biology, Harvard Medical School, Boston, MA 02115, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Alexander Lukyanov
Janelle Vultaggio
1Department of Systems Biology, Harvard Medical School, Boston, MA 02115, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Michele Ceribelli
4Division of Preclinical Innovation, NCATS/NIH, Rockville, MD 20850, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Craig Thomas
4Division of Preclinical Innovation, NCATS/NIH, Rockville, MD 20850, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Taran Singh Gujral
2Division of Human Biology, Fred Hutchinson Cancer Research Center, 1100 Fairview Ave N, Seattle, WA 98109, USA
3Department of Pharmacology, University of Washington, Seattle, WA 98195, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Taran Singh Gujral
Marc W. Kirschner
1Department of Systems Biology, Harvard Medical School, Boston, MA 02115, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Marc W. Kirschner
  • For correspondence: marc@hms.harvard.edu leonid_peshkin@hms.harvard.edu
Leonid Peshkin
1Department of Systems Biology, Harvard Medical School, Boston, MA 02115, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Leonid Peshkin
  • For correspondence: marc@hms.harvard.edu leonid_peshkin@hms.harvard.edu
  • Abstract
  • Full Text
  • Info/History
  • Metrics
  • Preview PDF
Loading

Article Information

doi 
https://doi.org/10.1101/2020.09.26.312348
History 
  • September 28, 2020.
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. Scott Rata1,
  2. Jonathan Scott Gruver1,
  3. Natalia Trikoz1,
  4. Alexander Lukyanov1,
  5. Janelle Vultaggio1,
  6. Michele Ceribelli4,
  7. Craig Thomas4,
  8. Taran Singh Gujral2,3,
  9. Marc W. Kirschner1,* and
  10. Leonid Peshkin1,*
  1. 1Department of Systems Biology, Harvard Medical School, Boston, MA 02115, USA
  2. 2Division of Human Biology, Fred Hutchinson Cancer Research Center, 1100 Fairview Ave N, Seattle, WA 98109, USA
  3. 3Department of Pharmacology, University of Washington, Seattle, WA 98195, USA
  4. 4Division of Preclinical Innovation, NCATS/NIH, Rockville, MD 20850, USA
  1. ↵*Correspondence should be addressed to MWP and LP: marc{at}hms.harvard.edu and leonid_peshkin{at}hms.harvard.edu
Back to top
PreviousNext
Posted September 28, 2020.
Download PDF
Email

Thank you for your interest in spreading the word about bioRxiv.

NOTE: Your email address is requested solely to identify you as the sender of this article.

Enter multiple addresses on separate lines or separate them with commas.
An optimal set of inhibitors for Reverse Engineering via Kinase Regularization
(Your Name) has forwarded a page to you from bioRxiv
(Your Name) thought you would like to see this page from the bioRxiv website.
CAPTCHA
This question is for testing whether or not you are a human visitor and to prevent automated spam submissions.
Share
An optimal set of inhibitors for Reverse Engineering via Kinase Regularization
Scott Rata, Jonathan Scott Gruver, Natalia Trikoz, Alexander Lukyanov, Janelle Vultaggio, Michele Ceribelli, Craig Thomas, Taran Singh Gujral, Marc W. Kirschner, Leonid Peshkin
bioRxiv 2020.09.26.312348; doi: https://doi.org/10.1101/2020.09.26.312348
Digg logo Reddit logo Twitter logo CiteULike logo Facebook logo Google logo Mendeley logo
Citation Tools
An optimal set of inhibitors for Reverse Engineering via Kinase Regularization
Scott Rata, Jonathan Scott Gruver, Natalia Trikoz, Alexander Lukyanov, Janelle Vultaggio, Michele Ceribelli, Craig Thomas, Taran Singh Gujral, Marc W. Kirschner, Leonid Peshkin
bioRxiv 2020.09.26.312348; doi: https://doi.org/10.1101/2020.09.26.312348

Citation Manager Formats

  • BibTeX
  • Bookends
  • EasyBib
  • EndNote (tagged)
  • EndNote 8 (xml)
  • Medlars
  • Mendeley
  • Papers
  • RefWorks Tagged
  • Ref Manager
  • RIS
  • Zotero
  • Tweet Widget
  • Facebook Like
  • Google Plus One

Subject Area

  • Systems Biology
Subject Areas
All Articles
  • Animal Behavior and Cognition (2646)
  • Biochemistry (5269)
  • Bioengineering (3678)
  • Bioinformatics (15796)
  • Biophysics (7257)
  • Cancer Biology (5629)
  • Cell Biology (8099)
  • Clinical Trials (138)
  • Developmental Biology (4768)
  • Ecology (7518)
  • Epidemiology (2059)
  • Evolutionary Biology (10578)
  • Genetics (7733)
  • Genomics (10137)
  • Immunology (5194)
  • Microbiology (13914)
  • Molecular Biology (5387)
  • Neuroscience (30784)
  • Paleontology (215)
  • Pathology (879)
  • Pharmacology and Toxicology (1525)
  • Physiology (2254)
  • Plant Biology (5024)
  • Scientific Communication and Education (1041)
  • Synthetic Biology (1388)
  • Systems Biology (4148)
  • Zoology (812)