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

Identifying common transcriptome signatures of cancer by interpreting deep learning models

View ORCID ProfileAnupama Jha, View ORCID ProfileMathieu Quesnel-Vallières, View ORCID ProfileAndrei Thomas-Tikhonenko, Kristen W. Lynch, View ORCID ProfileYoseph Barash
doi: https://doi.org/10.1101/2021.11.11.467790
Anupama Jha
1Department of Computer and Information Science, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, PA 19104, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Anupama Jha
  • For correspondence: anupamaj@seas.upenn.edu mathieu.quesnel-vallieres@pennmedicine.upenn.edu yosephb@pennmedicine.upenn.edu
Mathieu Quesnel-Vallières
2Department of Biochemistry and Biophysics, University of Pennsylvania, Philadelphia, PA 19104, USA
3Department of Genetics, University of Pennsylvania, Philadelphia, PA 19104, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Mathieu Quesnel-Vallières
  • For correspondence: anupamaj@seas.upenn.edu mathieu.quesnel-vallieres@pennmedicine.upenn.edu yosephb@pennmedicine.upenn.edu
Andrei Thomas-Tikhonenko
4Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
5Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
6Division of Cancer Pathobiology, Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Andrei Thomas-Tikhonenko
Kristen W. Lynch
2Department of Biochemistry and Biophysics, University of Pennsylvania, Philadelphia, PA 19104, USA
3Department of Genetics, University of Pennsylvania, Philadelphia, PA 19104, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Yoseph Barash
1Department of Computer and Information Science, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, PA 19104, USA
3Department of Genetics, University of Pennsylvania, Philadelphia, PA 19104, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Yoseph Barash
  • For correspondence: anupamaj@seas.upenn.edu mathieu.quesnel-vallieres@pennmedicine.upenn.edu yosephb@pennmedicine.upenn.edu
  • Abstract
  • Full Text
  • Info/History
  • Metrics
  • Supplementary material
  • Preview PDF
Loading

Article Information

doi 
https://doi.org/10.1101/2021.11.11.467790
History 
  • November 12, 2021.
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-ND 4.0 International license.

Author Information

  1. Anupama Jha1,*,†,
  2. Mathieu Quesnel-Vallières2,3,*,†,
  3. Andrei Thomas-Tikhonenko4,5,6,
  4. Kristen W. Lynch2,3 and
  5. Yoseph Barash1,3,†
  1. 1Department of Computer and Information Science, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, PA 19104, USA
  2. 2Department of Biochemistry and Biophysics, University of Pennsylvania, Philadelphia, PA 19104, USA
  3. 3Department of Genetics, University of Pennsylvania, Philadelphia, PA 19104, USA
  4. 4Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
  5. 5Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
  6. 6Division of Cancer Pathobiology, Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA
  1. ↵†Correspondence to: Anupama Jha <anupamaj{at}seas.upenn.edu>, Mathieu Quesnel-Vallières <mathieu.quesnel-vallieres{at}pennmedicine.upenn.edu>, Yoseph Barash <yosephb{at}pennmedicine.upenn.edu>.
  1. ↵* Equal contribution

Back to top
PreviousNext
Posted November 12, 2021.
Download PDF

Supplementary Material

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.
Identifying common transcriptome signatures of cancer by interpreting deep learning models
(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
Identifying common transcriptome signatures of cancer by interpreting deep learning models
Anupama Jha, Mathieu Quesnel-Vallières, Andrei Thomas-Tikhonenko, Kristen W. Lynch, Yoseph Barash
bioRxiv 2021.11.11.467790; doi: https://doi.org/10.1101/2021.11.11.467790
Digg logo Reddit logo Twitter logo Facebook logo Google logo LinkedIn logo Mendeley logo
Citation Tools
Identifying common transcriptome signatures of cancer by interpreting deep learning models
Anupama Jha, Mathieu Quesnel-Vallières, Andrei Thomas-Tikhonenko, Kristen W. Lynch, Yoseph Barash
bioRxiv 2021.11.11.467790; doi: https://doi.org/10.1101/2021.11.11.467790

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

  • Cancer Biology
Subject Areas
All Articles
  • Animal Behavior and Cognition (3505)
  • Biochemistry (7346)
  • Bioengineering (5323)
  • Bioinformatics (20262)
  • Biophysics (10016)
  • Cancer Biology (7743)
  • Cell Biology (11300)
  • Clinical Trials (138)
  • Developmental Biology (6437)
  • Ecology (9951)
  • Epidemiology (2065)
  • Evolutionary Biology (13322)
  • Genetics (9361)
  • Genomics (12583)
  • Immunology (7701)
  • Microbiology (19021)
  • Molecular Biology (7441)
  • Neuroscience (41036)
  • Paleontology (300)
  • Pathology (1229)
  • Pharmacology and Toxicology (2137)
  • Physiology (3160)
  • Plant Biology (6860)
  • Scientific Communication and Education (1272)
  • Synthetic Biology (1896)
  • Systems Biology (5311)
  • Zoology (1089)