Mining the Biomedical Literature (Computational Molecular Biology)

By Hagit Shatkay

The creation of high-throughput equipment has reworked biology right into a data-rich technological know-how. wisdom approximately organic entities and techniques has generally been obtained by means of millions of scientists via a long time of experimentation and research. the present abundance of biomedical information is followed through the production and fast dissemination of recent info. a lot of this knowledge and data, despite the fact that, is represented merely in textual content form--in the biomedical literature, lab notebooks, websites, and different resources. Researchers' have to locate appropriate info within the substantial quantities of textual content has created a surge of curiosity in computerized text-analysis.

In this e-book, Hagit Shatkay and Mark Craven supply a concise and available advent to key principles in biomedical textual content mining. The chapters disguise such issues because the correct resources of biomedical textual content; text-analysis equipment in ordinary language processing; the projects of knowledge extraction, info retrieval, and textual content categorization; and strategies for empirically assessing text-mining structures. eventually, the authors describe numerous functions that realize entities in textual content and hyperlink them to different entities and information assets, aid the curation of based databases, and utilize textual content to allow extra prediction and discovery.

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