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Elodie Drula

dblp:118/0827 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2012
0000-0002-9168-5214ORCID · reported

Domains — the database's venue-derived domains; a paper can count in several

Applied, interdisciplinary, general and emerging computing · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Interdisciplinary, comprehensive, and emerging computing
1 paper
Bioinformatics and computational biology · 56% Computational social science and digital humanities · 44%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology
biocuration
0.112012
MyMiner: a web application for computer-assisted biocuration and text annotation · Bioinform. 2012
Computational social science and digital humanities › text analysis
text annotation
0.112012
MyMiner: a web application for computer-assisted biocuration and text annotation · Bioinform. 2012
Bioinformatics and computational biology
biomedical text mining
0.012012
MyMiner: a web application for computer-assisted biocuration and text annotation · Bioinform. 2012

Methods — techniques the papers use, named apart from their topics

text mining · 0.1
YearPublicationVenuePosition
2012 MyMiner: a web application for computer-assisted biocuration and text annotation
abstract
MOTIVATION: The exponential growth of scientific literature has resulted in a massive amount of unstructured natural language data that cannot be directly handled by means of bioinformatics tools. Such tools generally require structured data, often generated through a cumbersome process of manual literature curation. Herein, we present MyMiner, a free and user-friendly text annotation tool aimed to assist in carrying out the main biocuration tasks and to provide labelled data for the development of text mining systems. MyMiner allows easy classification and labelling of textual data according to user-specified classes as well as predefined biological entities. The usefulness and efficiency of this application have been tested for a range of real-life annotation scenarios of various research topics. AVAILABILITY: http://myminer.armi.monash.edu.au.
David Salgado, Martin Krallinger, Marc Depaule, Elodie Drula, Ashish V. Tendulkar, Florian Leitner, Alfonso Valencia, Christophe Marcelle
Bioinform.4