Demo Data from EDBT 2026 / reviewers in the wild / expert
Iain McKendrick
dblp:77/10200
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2011
—ORCID · none
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 · 100% |
Topics — the 2 heaviest of 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Bioinformatics and computational biology › biomedical text mining
biomedical event extraction |
0.1 | 1 | 2011 | Automatic extraction of angiogenesis bioprocess from text · Bioinform. 2011 |
Bioinformatics and computational biology
biomedical text mining |
0.1 | 1 | 2011 | Automatic extraction of angiogenesis bioprocess from text · Bioinform. 2011 |
Methods — techniques the papers use, named apart from their topics
supervised machine learning · 0.1lexicon-based extraction · 0.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2011 | Automatic extraction of angiogenesis bioprocess from textabstractMOTIVATION: Understanding key biological processes (bioprocesses) and their relationships with constituent biological entities and pharmaceutical agents is crucial for drug design and discovery. One way to harvest such information is searching the literature. However, bioprocesses are difficult to capture because they may occur in text in a variety of textual expressions. Moreover, a bioprocess is often composed of a series of bioevents, where a bioevent denotes changes to one or a group of cells involved in the bioprocess. Such bioevents are often used to refer to bioprocesses in text, which current techniques, relying solely on specialized lexicons, struggle to find. RESULTS: This article presents a range of methods for finding bioprocess terms and events. To facilitate the study, we built a gold standard corpus in which terms and events related to angiogenesis, a key biological process of the growth of new blood vessels, were annotated. Statistics of the annotated corpus revealed that over 36% of the text expressions that referred to angiogenesis appeared as events. The proposed methods respectively employed domain-specific vocabularies, a manually annotated corpus and unstructured domain-specific documents. Evaluation results showed that, while a supervised machine-learning model yielded the best precision, recall and F1 scores, the other methods achieved reasonable performance and less cost to develop. AVAILABILITY: The angiogenesis vocabularies, gold standard corpus, annotation guidelines and software described in this article are available at http://text0.mib.man.ac.uk/~mbassxw2/angiogenesis/ CONTACT: [email protected]. Xinglong Wang, Iain McKendrick, Ian P. Barrett, Ian Dix, Tim French 0003, Jun'ichi Tsujii, Sophia Ananiadou |
Bioinform. | 2 |