Paper Info
Title
Nanopublications for exposing experimental data in the life-sciences: a Huntington's Disease case study.
Abstract
Data from high throughput experiments often produce far more results than can ever appear in the main text or tables of a single research article. In these cases, the majority of new associations are often archived either as supplemental information in an arbitrary format or in publisher-independent databases that can be difficult to find. These data are not only lost from scientific discourse, but are also elusive to automated search, retrieval and processing. Here, we use the nanopublication model to make scientific assertions that were concluded from a workflow analysis of Huntington's Disease data machine-readable, interoperable, and citable. We followed the nanopublication guidelines to semantically model our assertions as well as their provenance metadata and authorship. We demonstrate interoperability by linking nanopublication provenance to the Research Object model. These results indicate that nanopublications can provide an incentive for researchers to expose data that is interoperable and machine-readable for future use and preservation for which they can get credits for their effort. Nanopublications can have a leading role into hypotheses generation offering opportunities to produce large-scale data integration.
Year
DOI
Venue
2013
10.1186/2041-1480-6-5
J. Biomedical Semantics
Keywords
DocType
Volume
bioinformatics,algorithms
Conference
6
Issue
ISSN
Citations 
1
2041-1480
4
PageRank 
References 
Authors
0.47
5
10
Name
Order
Citations
PageRank
Eleni Mina1453.58
Mark Thompson240.81
Rajaram Kaliyaperumal3266.95
Jun Zhao486987.96
Eelke van der Horst5727.34
Zuotian Tatum661.23
Kristina M Hettne714710.47
Erik A. Schultes840.47
Barend Mons943033.31
Marco Roos1040531.88