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Title:
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TEXT-MINING RESEARCH IN GENOMICS |
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Author(s):
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Carmen Galvez , Félix Moya-anegón |
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ISBN:
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978-972-8924-56-0 |
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Editors:
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Nuno Guimarães and Pedro Isaías |
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Year:
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2008 |
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Edition:
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Single |
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Keywords:
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Text-mining; Genomics; Bioinformatics; Knowledge Discovery in Text (KDT) |
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Type:
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Full Paper |
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First Page:
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277 |
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Last Page:
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283 |
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Language:
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English |
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Cover:
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Full Contents:
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click to dowload 
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Paper Abstract:
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Biomedical text-mining have great promise to improve the usefulness of genomic researchers. The goal of text-mining is
analyzed large collections of unstructured documents for the purposes of extracting interesting and non-trivial patterns of
knowledge. The analysis of biomedical texts and available databases, such as Medline and PubMed, can help to interpret
a phenomenon, to detect gene relations, or to establish comparisons among similar genes in different specific databases.
All these processes are crucial for making sense of the immense quantity of genomic information. In genomics, textmining
research refers basically to the creation of literature networks of related biological entities. Text data represent the
genomics knowledge base and can be mined for relationships, literature networks, and new discoveries by literature
relational chaining. However, text-mining is an emerging field without a clear definition in the genomics. This work
presents some applications of text-mining to genome-based research, such as the genomic term identification in curation
processes, the formulation of hypotheses about disease, the visualization of biological relationships, or the life-science
domain mapping. |
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