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

Correcting gradient-based interpretations of deep neural networks for genomics

Antonio Majdandzic, Chandana Rajesh, View ORCID ProfilePeter K. Koo
doi: https://doi.org/10.1101/2022.04.29.490102
Antonio Majdandzic
1Simons Center for Quantitative Biology, Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Chandana Rajesh
1Simons Center for Quantitative Biology, Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Peter K. Koo
1Simons Center for Quantitative Biology, Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Peter K. Koo
  • For correspondence: koo@cshl.edu
  • Abstract
  • Full Text
  • Info/History
  • Metrics
  • Supplementary material
  • Data/Code
  • Preview PDF
Loading

Article Information

doi 
https://doi.org/10.1101/2022.04.29.490102
History 
  • August 23, 2022.

Article Versions

  • Version 1 (May 1, 2022 - 10:38).
  • You are viewing 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-ND 4.0 International license.

Author Information

  1. Antonio Majdandzic1,
  2. Chandana Rajesh1 and
  3. Peter K. Koo1,*
  1. 1Simons Center for Quantitative Biology, Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA
  1. ↵*koo{at}cshl.edu
Back to top
PreviousNext
Posted August 23, 2022.
Download PDF

Supplementary Material

Data/Code
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.
Correcting gradient-based interpretations of deep neural networks for genomics
(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
Correcting gradient-based interpretations of deep neural networks for genomics
Antonio Majdandzic, Chandana Rajesh, Peter K. Koo
bioRxiv 2022.04.29.490102; doi: https://doi.org/10.1101/2022.04.29.490102
Reddit logo Twitter logo Facebook logo LinkedIn logo Mendeley logo
Citation Tools
Correcting gradient-based interpretations of deep neural networks for genomics
Antonio Majdandzic, Chandana Rajesh, Peter K. Koo
bioRxiv 2022.04.29.490102; doi: https://doi.org/10.1101/2022.04.29.490102

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

  • Bioinformatics
Subject Areas
All Articles
  • Animal Behavior and Cognition (4237)
  • Biochemistry (9148)
  • Bioengineering (6788)
  • Bioinformatics (24029)
  • Biophysics (12141)
  • Cancer Biology (9548)
  • Cell Biology (13796)
  • Clinical Trials (138)
  • Developmental Biology (7642)
  • Ecology (11718)
  • Epidemiology (2066)
  • Evolutionary Biology (15519)
  • Genetics (10650)
  • Genomics (14333)
  • Immunology (9493)
  • Microbiology (22858)
  • Molecular Biology (9103)
  • Neuroscience (49034)
  • Paleontology (355)
  • Pathology (1485)
  • Pharmacology and Toxicology (2572)
  • Physiology (3850)
  • Plant Biology (8339)
  • Scientific Communication and Education (1472)
  • Synthetic Biology (2296)
  • Systems Biology (6197)
  • Zoology (1302)