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Molecular pathological epidemiology: new developing frontiers of big data science to study etiologies and pathogenesis

Published Online: 2016-10-13

Published Print: 2017-03

Authors

Hamada, Tsuyoshi

Keum, NaNa

Nishihara, Reiko

Ogino, Shuji https://orcid.org/0000-0002-3909-2323
Funding

Funding for this research was provided by:

the Uehara Memorial Foundation (a fellowship grant)

The Friends of the Dana-Farber Cancer Institute

the Mochida Memorial Foundation (a fellowship grant)

U.S. National Institutes of Health (R01 CA151993)

U.S. National Institutes of Health (R35 CA197735)

U.S. National Institutes of Health (K07 CA190673)

the Dana-Farber Harvard Cancer Center (Nodal Award)
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Text and Data Mining valid from 2016-10-13

Version of Record valid from 2016-10-13
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Article History

Received: 16 September 2016

Accepted: 22 September 2016

First Online: 13 October 2016

Compliance with ethical standards

:

: All authors declare that they have no conflicts of interest.

Free to read: This content has been made available to all.

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