Interpretation of gene expression microarray experiments

ABSTRACT

Microarrays nowadays have an almost ubiquitous presence in modern biological research The extent and versatility of the techniques that are available for analysis and interpretation of microarray experiments can be somehow bewildering to the interested biologists. Functional genomics involves the highthroughput analysis of large datasets of information derived from various biological experiments. Microarray technology makes this possible by monitoring the emitting fluorescence reflecting the expression levels of thousands of genes simultaneously, which are bound to the oligonucleotide probes specific for each of the putative gene sequences comprising the total genome of the investigated organism, under a particular condition.. This chapter is a brief overview of the basic concepts involved in a microarray experiment; and it aspires to provide a concise overview of key issues regarding the various steps of implementation of this promising experimental methodology. In this sense, the chapter gives a feeling for what the data actually represent, and will provide information on the various computational methods that one can employ to derive meaningful results from such experiments.

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Index Terms

• Applied computing

  • Life and medical sciences

    • Computational biology

    • Genetics

    • Systems biology

• Computing methodologies

  • Machine learning

    • Learning paradigms

      • Supervised learning

        • Supervised learning by classification

    • Machine learning algorithms

      • Feature selection