Abstract
Microarrays have become a standard tool for studying gene functions. For example, we can investigate if a subset of genes shows a coherent expression pattern under different conditions. The plaid model, a model-based biclustering method, can be used to incorporate the addiction structure used for the microarray experiment. In this paper we describe an enhancement for the plaid model algorithm based on the theory of the false discovery rate.
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This research has been supported by grants of the University of Palermo.
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Augugliaro, L., Mineo, A.M. (2011). Plaid Model for Microarray Data: an Enhancement of the Pruning Step. In: Fichet, B., Piccolo, D., Verde, R., Vichi, M. (eds) Classification and Multivariate Analysis for Complex Data Structures. Studies in Classification, Data Analysis, and Knowledge Organization. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-13312-1_47
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DOI: https://doi.org/10.1007/978-3-642-13312-1_47
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