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Lei Chen et al.
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Michael Kuhn et al.
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BIOMED RESEARCH INTERNATIONAL (2013)
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Yoshihiro Yamanishi et al.
JOURNAL OF CHEMICAL INFORMATION AND MODELING (2012)
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Mei Liu et al.
JOURNAL OF THE AMERICAN MEDICAL INFORMATICS ASSOCIATION (2012)
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Lei Chen et al.
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Yu-Fei Gao et al.
PLOS ONE (2012)
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Edouard Pauwels et al.
BMC BIOINFORMATICS (2011)
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Nir Atias et al.
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Le-Le Hu et al.
PLOS ONE (2011)
A side effect resource to capture phenotypic effects of drugs
Michael Kuhn et al.
MOLECULAR SYSTEMS BIOLOGY (2010)
SIMCOMP/SUBCOMP: chemical structure search servers for network analyses
Masahiro Hattori et al.
NUCLEIC ACIDS RESEARCH (2010)
Walking the interactome for prioritization of candidate disease genes
Sebastian Koehler et al.
AMERICAN JOURNAL OF HUMAN GENETICS (2008)
STITCH: interaction networks of chemicals and proteins
Michael Kuhn et al.
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M Hattori et al.
JOURNAL OF THE AMERICAN CHEMICAL SOCIETY (2003)