Text mining and ontologies in biomedicine: Making sense of raw text
By Irena Spasic, Sophia Ananiadou, John McNaught, Anand Kumar. Briefings Bioinform., 2005
339 citations recorded by the source corpus.
Subfields: Artificial Intelligence, Molecular Biology
View Paper: https://www.semanticscholar.org/paper/201e667b068cd81cb8af10a925b40c8288d1e39e
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Artificial Intelligence
- Sophia Ananiadou
- Hong Yu
- K. Cohen
- Dina Demner-Fushman
- Junichi Tsujii
- Pierre Zweigenbaum
- Yulan He
- Deyu Zhou
In Molecular Biology
- Hong Yu
- Dina Demner-Fushman
- Junichi Tsujii
- Sophia Ananiadou
- K. Cohen
- Pierre Zweigenbaum
- Douglas B. Kell
- Yulan He
Citations in the corpus
- Structuring and extracting knowledge for the support of hypothesis generation in molecular biology (2009, neutral): “predefined sets of biological terms [7,8], or that use machine learning algorithms to recognize entities and”
- Frontiers of biomedical text mining: current progress (2007, methodology): “We also issued bibliographic queries for: ‘text mining’ in Bioinformatics (MEDLINE), ‘biology’ or ‘medicine’ in ACM journals and PubMed ‘related articles,’ starting from the review papers [5–7].”
- Extracting interactions between proteins from the literature (2008, positive): “…so far rely on the techniques from one or more areas [29] [30] [31] [32] including Information Retrieval (IR) [27] [33], Machine Learning (ML) [34] [35], Natural Language Processing (NLP) [36] [37] [38], Information Extraction (IE) [39] [40] [41] [42] and Text Mining [43] [44] [45] [46] [47] [48].”
- Text mining and its potential applications in systems biology. (2006, positive): “Ontologies are crucial for text mining because they provide semantic interpretation to text and also constrain the possible interpretations of biological entities (terms) (Figure 2): when we provide semantic interpretation to text, we link terms to concepts in ontologies [40,41], whereby textual evi”
- Biomedical language processing: what's beyond PubMed? (2006, background): “Bodenreider (2006) reviews the primary ontological resources in the biomedical domain, and Spasic et al. (2005) reviews the use of such resources in various BLP applications.”