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Perspective of Feature Selection Techniques in Bioinformatics

The availability of massive amounts of experimental data based on genome-wide association and mass spectroscopy studies have given motivation in recent years to a large effort in developing mathematical, statistical and computational techniques to infer biological models from data. In many bioinformatics problems the number of features is significantly larger than the number of samples (high feature to sample ratio data sets) and feature selection techniques have become an apparent need in many bioinformatics applications. In addition to the large pool of techniques that have already been developed in the data mining fields, specific applications in bioinformatics have led to a wealth of newly proposed techniques.

Provided by: King Saud University Topic: Data Management Date Added: Jun 2011 Format: PDF

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