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DNA REPAIR (2019)
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Buru Chang et al.
GENES (2019)
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Christos Davatzikos
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Martin Walter et al.
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Dominic B. Dwyer et al.
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Daniel Moreno-De-Luca et al.
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Maryam Akhavan Aghdam et al.
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Malgorzata Maciukiewicz et al.
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Travers Ching et al.
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Murray B. Stein et al.
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Mikaela Qvarfordt et al.
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Eugene Lin et al.
FRONTIERS IN PSYCHIATRY (2018)
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Dibyendu Dana et al.
MOLECULES (2018)
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Ramon Casanova et al.
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Eugene Lin et al.
FRONTIERS IN PSYCHIATRY (2018)
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Dmitry Grapov et al.
OMICS-A JOURNAL OF INTEGRATIVE BIOLOGY (2018)
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Danilo Bzdok et al.
BIOLOGICAL PSYCHIATRY-COGNITIVE NEUROSCIENCE AND NEUROIMAGING (2018)
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Geert Litjens et al.
MEDICAL IMAGE ANALYSIS (2017)
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Choong-Wan Woo et al.
NATURE NEUROSCIENCE (2017)
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Mohammad R. Arbabshirani et al.
NEUROIMAGE (2017)
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ONCOTARGET (2017)
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Jui-Chu Lin et al.
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FRONTIERS IN PSYCHIATRY (2017)
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PLOS ONE (2017)
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Eugene Lin et al.
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Brisa S. Fernandes et al.
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Eugene Lin et al.
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Yongli Hu et al.
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Chien-Hsiun Chen et al.
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Raquel Iniesta et al.
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Lasse Folkersen et al.
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Shareefa Dalvie et al.
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Eugene Lin et al.
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R. Iniesta et al.
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Eugene Lin et al.
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Walter H. L. Pinaya et al.
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Adam Mourad Chekroud et al.
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Abdellah Tebani et al.
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Zakariya Yahya Algamal et al.
COMPUTERS IN BIOLOGY AND MEDICINE (2015)
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Alexander Kautzky et al.
EUROPEAN NEUROPSYCHOPHARMACOLOGY (2015)
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Meenal J. Patel et al.
INTERNATIONAL JOURNAL OF GERIATRIC PSYCHIATRY (2015)
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Hilleke Hulshoff Pol et al.
EUROPEAN NEUROPSYCHOPHARMACOLOGY (2013)
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Bayasgalan Gombojav et al.
TWIN RESEARCH AND HUMAN GENETICS (2013)
Biomarker robustness reveals the PDGF network as driving disease outcome in ovarian cancer patients in multiple studies
Rotem Ben-Hamo et al.
BMC SYSTEMS BIOLOGY (2012)
Assessing Gene-Gene Interactions in Pharmacogenomics
Hsien-Yuan Lane et al.
MOLECULAR DIAGNOSIS & THERAPY (2012)
Regularization Paths for Generalized Linear Models via Coordinate Descent
Jerome Friedman et al.
JOURNAL OF STATISTICAL SOFTWARE (2010)
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Hui Zou et al.
ANNALS OF STATISTICS (2009)
Automatic classification of MR scans in Alzheimers disease
Stefan Kloeppel et al.
BRAIN (2008)
Pattern-recognition techniques with haplotype analysis in pharmacogenomics
Eugene Lin et al.
PHARMACOGENOMICS (2007)
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