Please use this identifier to cite or link to this item: http://hdl.handle.net/20.500.12188/22372
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dc.contributor.authorK Schulze, Sabrinaen_US
dc.contributor.authorRamšak, Živaen_US
dc.contributor.authorHoang, Yenen_US
dc.contributor.authorZdravevski, Eftimen_US
dc.contributor.authorPfeil, Julianeen_US
dc.contributor.authorDuarte López, Arielen_US
dc.contributor.authorBaier, Uween_US
dc.contributor.authorZagoršcak, Majaen_US
dc.date.accessioned2022-08-17T09:20:42Z-
dc.date.available2022-08-17T09:20:42Z-
dc.date.issued2018-04-19-
dc.identifier.urihttp://hdl.handle.net/20.500.12188/22372-
dc.description.abstractOn 6th and 7th February 2018 a Think Tank took place in Ljubljana, Slovenia. It was a follow-up of the “Big Data Training School for Life Sciences” held in Uppsala, Sweden, in September 2017. The focus was on identifying topics of interest and optimising the programme for a forthcoming “Advanced” Big Data Training School for Life Science, that we hope is again supported by the COST Action CHARME (Harmonising standardisation strategies to increase efficiency and competitiveness of European life-science research - CA15110). The Think Tank aimed to go into details of several topics that were - to a degree - covered by the former training school. Likewise, discussions embraced the recent experience of the attendees in light of the new knowledge obtained by the first edition of the training school and how it comes from the perspective of their current and upcoming work. The 2018 training school should strive for and further facilitate optimised applications of Big Data technologies in life sciences. The attendees of this hackathon entirely organised this workshop.en_US
dc.relation.ispartofEMBnet. journalen_US
dc.titleProceedings of the “Think Tank Hackathon’’, Big Data Training School for Life Sciences Follow-up, Ljubljana 6th–7th February 2018en_US
dc.typeArticleen_US
item.fulltextWith Fulltext-
item.grantfulltextopen-
crisitem.author.deptFaculty of Computer Science and Engineering-
Appears in Collections:Faculty of Computer Science and Engineering: Journal Articles
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