Text mining in bioinformatics: past, present and future

The peer-reviewed articles and textual data are main source of data in biology. Text mining is solution to extract information from textual data sources that are usually in bulky quantities, messy and disorganized. Dealing with this situation needs to deploy innovative methods and techniques. In thi...

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Bibliographic Details
Main Authors: Faiiazee, Hadee, Syed Mohamed, Syed Abdul Rahman Al-Haddad, Abdullah, Rusli, Samsudin, Khairulmizam
Format: Conference or Workshop Item
Language:English
Published: IEEE 2012
Online Access:http://psasir.upm.edu.my/id/eprint/68794/1/Text%20mining%20in%20bioinformatics%20past%2C%20present%20and%20future.pdf
Description
Summary:The peer-reviewed articles and textual data are main source of data in biology. Text mining is solution to extract information from textual data sources that are usually in bulky quantities, messy and disorganized. Dealing with this situation needs to deploy innovative methods and techniques. In this paper, we identify the current heavily used methods for biomedical text mining, their capabilities and developments, some proposed solution and how to evaluate performance. Biomedical specific challenges in text mining context have been studied with respect to proposed answers and then main future trends based on current needs and requirements have been discussed.