Data Analysis in Chemistry and Bio-Medical Sciences
dc.contributor.author | Todeschini, Roberto | |
dc.contributor.author | Pazos, Alejandro | |
dc.contributor.author | Arrasate Gil, Sonia | |
dc.contributor.author | González Díaz, Humberto | |
dc.date.accessioned | 2018-05-24T17:46:39Z | |
dc.date.available | 2018-05-24T17:46:39Z | |
dc.date.issued | 2016-12-14 | |
dc.identifier.citation | International Journal of Molecular Sciences 17(12) : (2016) // Article ID 2105 | es_ES |
dc.identifier.issn | 1422-0067 | |
dc.identifier.uri | http://hdl.handle.net/10810/27086 | |
dc.description.abstract | There is an increasing necessity for multidisciplinary collaborations in molecular science between experimentalists and theoretical scientists, as well as among theoretical scientists from different fields. One of the more important forces driving this necessity is the accumulation of large amounts of data as a result of important advances in Cheminformatics and Molecular Sciences Experimental Techniques of data acquisition in general. In this context, we decided to create the MOL2NET International Conference Series on Multidisciplinary Sciences (http://sciforum.net/conferences/mol2net). The official publication platform for this conference series is SciForum, MDPI, Basel, Switzerland, and Beijing, China. The headquarters of the conference are in the Department of Organic Chemistry, University of Basque Country (UPV/EHU), Biscay, Spain. | es_ES |
dc.description.sponsorship | The authors acknowledge partial financial support from CTQ2013-41229-P, CTQ2013-41229-P/BQU, and CTQ2016-74881-P funded by MINECO, Spain as well as grant IT1045-16 of Basque Government (Eusko Jaurlaritza). The guest editors of this issue sincerely thank the kind support of both the SciForum team and the IJMS Editorial staff. | es_ES |
dc.language.iso | eng | es_ES |
dc.publisher | MDPI | es_ES |
dc.relation | info:eu-repo/grantAgreement/MINECO/CTQ2013-41229-P | es_ES |
dc.relation | info:eu-repo/grantAgreement/MINECOCTQ2013-41229-P/BQU | es_ES |
dc.relation | info:eu-repo/grantAgreement/MINECO/CTQ2016-74881-P | es_ES |
dc.rights | info:eu-repo/semantics/openAccess | es_ES |
dc.rights.uri | http://creativecommons.org/licenses/by/3.0/es/ | * |
dc.subject | binding affinities | es_ES |
dc.subject | acid-derivatives | es_ES |
dc.subject | prediction | es_ES |
dc.subject | model | es_ES |
dc.title | Data Analysis in Chemistry and Bio-Medical Sciences | es_ES |
dc.type | info:eu-repo/semantics/article | es_ES |
dc.rights.holder | © 2016 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons by Attribution (CC-BY) license (http://creativecommons.org/licenses/by/4.0/). | es_ES |
dc.rights.holder | Atribución 3.0 España | * |
dc.relation.publisherversion | http://www.mdpi.com/1422-0067/17/12/2105/htm | es_ES |
dc.identifier.doi | 10.3390/ijms17122105 | |
dc.departamentoes | Química orgánica II | es_ES |
dc.departamentoeu | Kimika organikoa II | es_ES |
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Except where otherwise noted, this item's license is described as © 2016 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons by Attribution (CC-BY) license (http://creativecommons.org/licenses/by/4.0/).