Text mining and its potential applications in systems biology

With biomedical literature increasing at a rate of several thousand papers per week, it is impossible to keep abreast of all developments; therefore, automated means to manage the information overload are required. Text mining techniques, which involve the processes of information retrieval, informa...

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Bibliographic Details
Published in:Trends in biotechnology (Regular ed.) 2006-12, Vol.24 (12), p.571-579
Main Authors: Ananiadou, Sophia, Kell, Douglas B., Tsujii, Jun-ichi
Format: Article
Language:English
Subjects:
Artificial Intelligence
Biological and medical sciences
Biology
Biotechnology
Data mining
Disease
Fundamental and applied biological sciences. Psychology
General aspects
Genomics
Hypotheses
Information retrieval
Information Storage and Retrieval - methods
Mathematics in biology. Statistical analysis. Models. Metrology. Data processing in biology (general aspects)
Methods
Models, Biological
Natural Language Processing
Ordinary differential equations
Research Design
Search engines
Syntax
Systems Biology - methods
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Summary:With biomedical literature increasing at a rate of several thousand papers per week, it is impossible to keep abreast of all developments; therefore, automated means to manage the information overload are required. Text mining techniques, which involve the processes of information retrieval, information extraction and data mining, provide a means of solving this. By adding meaning to text, these techniques produce a more structured analysis of textual knowledge than simple word searches, and can provide powerful tools for the production and analysis of systems biology models.
ISSN:0167-7799
1879-3096
DOI:10.1016/j.tibtech.2006.10.002