Software Open Access
Daniel Himmelstein
<?xml version='1.0' encoding='UTF-8'?> <record xmlns="http://www.loc.gov/MARC21/slim"> <leader>00000nmm##2200000uu#4500</leader> <datafield tag="653" ind1=" " ind2=" "> <subfield code="a">rephetio</subfield> </datafield> <datafield tag="653" ind1=" " ind2=" "> <subfield code="a">machine learning</subfield> </datafield> <datafield tag="653" ind1=" " ind2=" "> <subfield code="a">hetnet edge prediction</subfield> </datafield> <datafield tag="653" ind1=" " ind2=" "> <subfield code="a">drug repurposing</subfield> </datafield> <datafield tag="653" ind1=" " ind2=" "> <subfield code="a">Rephetio</subfield> </datafield> <controlfield tag="005">20200125072152.0</controlfield> <controlfield tag="001">268654</controlfield> <datafield tag="856" ind1="4" ind2=" "> <subfield code="s">13600419</subfield> <subfield code="z">md5:b83964d01c1a29fdd1867c41abec6f9f</subfield> <subfield code="u">https://zenodo.org/record/268654/files/dhimmel/learn-v1.0.0.zip</subfield> </datafield> <datafield tag="542" ind1=" " ind2=" "> <subfield code="l">open</subfield> </datafield> <datafield tag="260" ind1=" " ind2=" "> <subfield code="c">2017-02-04</subfield> </datafield> <datafield tag="909" ind1="C" ind2="O"> <subfield code="p">software</subfield> <subfield code="o">oai:zenodo.org:268654</subfield> </datafield> <datafield tag="100" ind1=" " ind2=" "> <subfield code="a">Daniel Himmelstein</subfield> </datafield> <datafield tag="245" ind1=" " ind2=" "> <subfield code="a">dhimmel/learn v1.0: the machine learning repository for Project Rephetio</subfield> </datafield> <datafield tag="540" ind1=" " ind2=" "> <subfield code="u">https://creativecommons.org/publicdomain/zero/1.0/legalcode</subfield> <subfield code="a">Creative Commons Zero v1.0 Universal</subfield> </datafield> <datafield tag="650" ind1="1" ind2="7"> <subfield code="a">cc-by</subfield> <subfield code="2">opendefinition.org</subfield> </datafield> <datafield tag="520" ind1=" " ind2=" "> <subfield code="a"><p>Project Rephetio is an open project to systematically repurpose drugs. This release contains the machine learning code and data for Project Rephetio. For more information on Project Rephetio, see https://thinklab.com/p/rephetio and https://doi.org/10.1101/087619.</p></subfield> </datafield> <datafield tag="773" ind1=" " ind2=" "> <subfield code="n">url</subfield> <subfield code="i">isSupplementTo</subfield> <subfield code="a">https://github.com/dhimmel/learn/tree/v1.0.0</subfield> </datafield> <datafield tag="024" ind1=" " ind2=" "> <subfield code="a">10.5281/zenodo.268654</subfield> <subfield code="2">doi</subfield> </datafield> <datafield tag="980" ind1=" " ind2=" "> <subfield code="a">software</subfield> </datafield> </record>
All versions | This version | |
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Downloads | 28 | 28 |
Data volume | 380.8 MB | 380.8 MB |
Unique views | 199 | 200 |
Unique downloads | 26 | 26 |