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Joint analysis of multiple high-dimensional data types using sparse matrix approximations of rank-1 with applications to ovarian and liver cancer

  • Gordon Okimoto1Email authorView ORCID ID profile,
  • Ashkan Zeinalzadeh1,
  • Tom Wenska2,
  • Michael Loomis1,
  • James B. Nation3,
  • Tiphaine Fabre4,
  • Maarit Tiirikainen1,
  • Brenda Hernandez1,
  • Owen Chan1,
  • Linda Wong1 and
  • Sandi Kwee5
Contributed equally
BioData Mining20169:24

Received: 27 January 2016

Accepted: 5 July 2016

Published: 29 July 2016

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Open Peer Review reports

Pre-publication versions of this article are available by contacting

Original Submission
27 Jan 2016 Submitted Original manuscript
Author responded Author comments
Reviewed Reviewer Report
Resubmission - Version 2
Submitted Manuscript version 2
5 Jul 2016 Editorially accepted
29 Jul 2016 Article published 10.1186/s13040-016-0103-7

How does Open Peer Review work?

Open peer review is a system where authors know who the reviewers are, and the reviewers know who the authors are. If the manuscript is accepted, the named reviewer reports are published alongside the article. Pre-publication versions of the article are available by contacting

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Authors’ Affiliations

University of Hawaii Cancer Center, Honolulu, USA
SNR Analytics, Kaneohe, USA
Department of Mathematics, University of Hawaii, Manoa, Honolulu, USA
Interactive Biosoftware, Rouen, France
The Hamamatsu/Queen’s PET (Positron Emission Tomography) Imaging Center, Queen’s Medical Center, Honolulu, USA