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

New analysis framework incorporating mixed mutual information and scalable Bayesian networks for multimodal high dimensional genomic and epigenomic cancer data

Xichun Wang, Sergio Branciamore, Grigoriy Gogoshin, Shuyu Ding, Andrei S Rodin
doi: https://doi.org/10.1101/812446
Xichun Wang
Diabetes and Metabolism Research Institute and Beckman Research Institute of the City of Hope, Duarte, CA 91010
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Sergio Branciamore
Diabetes and Metabolism Research Institute and Beckman Research Institute of the City of Hope, Duarte, CA 91010
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Grigoriy Gogoshin
Diabetes and Metabolism Research Institute and Beckman Research Institute of the City of Hope, Duarte, CA 91010
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Shuyu Ding
Diabetes and Metabolism Research Institute and Beckman Research Institute of the City of Hope, Duarte, CA 91010
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Andrei S Rodin
Diabetes and Metabolism Research Institute and Beckman Research Institute of the City of Hope, Duarte, CA 91010
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • For correspondence: arodin@coh.org
  • Abstract
  • Full Text
  • Info/History
  • Metrics
  • Supplementary material
  • Preview PDF
Loading

Article Information

doi 
https://doi.org/10.1101/812446
History 
  • October 21, 2019.
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. Xichun Wang,
  2. Sergio Branciamore,
  3. Grigoriy Gogoshin,
  4. Shuyu Ding and
  5. Andrei S Rodin*
  1. Diabetes and Metabolism Research Institute and Beckman Research Institute of the City of Hope, Duarte, CA 91010
  1. ↵* Corresponding author arodin{at}coh.org, +1-626-218-3807. Diabetes and Metabolism Research Institute, Beckman Research Institute, City of Hope, 1500 East Duarte Road, Duarte, CA 91010-3000, USA
Back to top
PreviousNext
Posted October 21, 2019.
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.
New analysis framework incorporating mixed mutual information and scalable Bayesian networks for multimodal high dimensional genomic and epigenomic cancer data
(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
New analysis framework incorporating mixed mutual information and scalable Bayesian networks for multimodal high dimensional genomic and epigenomic cancer data
Xichun Wang, Sergio Branciamore, Grigoriy Gogoshin, Shuyu Ding, Andrei S Rodin
bioRxiv 812446; doi: https://doi.org/10.1101/812446
Reddit logo Twitter logo Facebook logo LinkedIn logo Mendeley logo
Citation Tools
New analysis framework incorporating mixed mutual information and scalable Bayesian networks for multimodal high dimensional genomic and epigenomic cancer data
Xichun Wang, Sergio Branciamore, Grigoriy Gogoshin, Shuyu Ding, Andrei S Rodin
bioRxiv 812446; doi: https://doi.org/10.1101/812446

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

  • Genomics
Subject Areas
All Articles
  • Animal Behavior and Cognition (4369)
  • Biochemistry (9543)
  • Bioengineering (7068)
  • Bioinformatics (24765)
  • Biophysics (12559)
  • Cancer Biology (9923)
  • Cell Biology (14296)
  • Clinical Trials (138)
  • Developmental Biology (7929)
  • Ecology (12073)
  • Epidemiology (2067)
  • Evolutionary Biology (15952)
  • Genetics (10901)
  • Genomics (14704)
  • Immunology (9841)
  • Microbiology (23580)
  • Molecular Biology (9453)
  • Neuroscience (50691)
  • Paleontology (369)
  • Pathology (1535)
  • Pharmacology and Toxicology (2674)
  • Physiology (3996)
  • Plant Biology (8638)
  • Scientific Communication and Education (1505)
  • Synthetic Biology (2388)
  • Systems Biology (6413)
  • Zoology (1344)