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Bayesian feature selection for high-dimensional linear regression via the Ising approximation with applications to genomics.

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Title: Bayesian feature selection for high-dimensional linear regression via the Ising approximation with applications to genomics.
Authors: Fisher CK; Department of Physics, Boston University, Boston, MA 02215, USA., Mehta P; Department of Physics, Boston University, Boston, MA 02215, USA.
Source: Bioinformatics (Oxford, England) [Bioinformatics] 2015 Jun 01; Vol. 31 (11), pp. 1754-61. Date of Electronic Publication: 2015 Jan 24.
Publication Type: Journal Article; Research Support, Non-U.S. Gov't
Journal Info: Publisher: Oxford University Press Country of Publication: England NLM ID: 9808944 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1367-4811 (Electronic) Linking ISSN: 13674803 NLM ISO Abbreviation: Bioinformatics Subsets: MEDLINE
Database: MEDLINE Ultimate
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        Value: 10.1093/bioinformatics/btv037
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      – Code: eng
        Text: English
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        StartPage: 1754
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      – TitleFull: Bayesian feature selection for high-dimensional linear regression via the Ising approximation with applications to genomics.
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            NameFull: Fisher CK
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            NameFull: Mehta P
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              Text: 2015 Jun 01
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              Y: 2015
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              Value: 31
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              Value: 11
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