Roxana Danger
Roxana Danger
Verified email at imperial.ac.uk
TitleCited byYear
Implementing interoperable provenance in biomedical research
V Curcin, S Miles, R Danger, Y Chen, R Bache, A Taweel
Future Generation Computer Systems 34, 1-16, 2014
322014
ProvAbs: model, policy, and tooling for abstracting PROV graphs
P Missier, J Bryans, C Gamble, V Curcin, R Danger
International Provenance and Annotation Workshop, 3-15, 2014
312014
Objectminer: A New Approach for Mining Complex Objects.
R Danger, J Ruíz-Shulcloper, RB Llavori
ICEIS (2), 42-47, 2004
242004
Towards a Protein–Protein Interaction information extraction system: Recognizing named entities
R Danger, F Pla, A Molina, P Rosso
Knowledge-Based Systems 57, 104-118, 2014
192014
A comparison of machine learning techniques for detection of drug target articles
R Danger, I Segura-Bedmar, P Martínez, P Rosso
Journal of biomedical informatics 43 (6), 902-913, 2010
172010
Generating complex ontology instances from documents
R Danger, R Berlanga
Journal of Algorithms 64 (1), 16-30, 2009
172009
Templates as a method for implementing data provenance in decision support systems
V Curcin, E Fairweather, R Danger, D Corrigan
Journal of biomedical informatics 65, 1-21, 2017
162017
Access control and view generation for provenance graphs
R Danger, V Curcin, P Missier, J Bryans
Future Generation Computer Systems 49, 8-27, 2015
162015
Provenance graph abstraction by node grouping
P Missier, J Bryans, C Gamble, V Curcin, R Danger
School of Computing Science Technical Report Series, 2013
152013
Evidence-based rules from family practice to inform family practice; the learning healthcare system case study on urinary tract infections
JK Soler, D Corrigan, P Kazienko, T Kajdanowicz, R Danger, ...
BMC family practice 16 (1), 63, 2015
122015
OntoPathView: a simple view definition language for the collaborative development of ontologies
E Jiménez, R Berlanga, I Sanz, MJ Aramburu, R Danger
Artificial Intelligence Research and Development 131, 429, 2005
112005
Automatic drug-drug interaction detection: A machine learning approach with maximal frequent sequence extraction
S García Blasco, SM Mola Velasco, RM Danger Mercaderes, P Rosso
CEUR Workshop Proceedings 761, 51-58, 2011
102011
ProvAbs: Model
P Missier, J Bryans, C Gamble, V Curcin, R Danger
Policy, and Tooling for Abstracting PROV Graphs, Revised Selected Papers of …, 2014
92014
The management and integration of biomedical knowledge: application in the Health-e-Child Project (Position Paper)
E Jiménez-Ruiz, R Berlanga, I Sanz, R McClatchey, R Dánger, D Manset, ...
OTM Confederated International Conferences" On the Move to Meaningful …, 2006
92006
Provenance model for randomized controlled trials
V Curcin, R Danger, W Kuchinke, S Miles, A Taweel, C Ohmann
Data Provenance and Data Management in eScience, 3-33, 2013
82013
Drug-drug interaction detection: a new approach based on maximal frequent sequences
S García-Blasco, R Danger Mercaderes, P Rosso
Sociedad Española para el Procesamiento del Lenguaje Natural, 2010
82010
A Semantic Web approach for ontological instances analysis
R Danger, R Berlanga
Software and data technologies, 269-282, 2007
72007
CRISOL: An approach for automatically populating Semantic Web from unstructured text collections
R Danger, R Berlanga, J Rui’z-Shulcloper
International Conference on Database and Expert Systems Applications, 243-252, 2004
62004
Text Mining using the hierarchical syntactical structure of documents
R Danger, J Ruíz-Shulcloper, R Berlanga
Conference on Technology Transfer, 556-565, 2003
62003
PPIEs: Protein-protein interaction information extraction system
R Danger, P Rosso, F Pla, A Molina
Procesamiento del lenguaje natural 40, 2008
52008
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Articles 1–20