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Gene selection and disease prediction from gene expression data using a two-stage hetero-associative memory

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Abstract

In general, gene expression microarrays consist of a vast number of genes and very few samples, which represents a critical challenge for disease prediction and diagnosis. This paper develops a two-stage algorithm that integrates feature selection and prediction by extending a type of hetero-associative neural networks. In the first level, the algorithm generates the associative memory, whereas the second level picks the most relevant genes. With the purpose of illustrating the applicability and efficiency of the method proposed here, we use four different gene expression microarray databases and compare their classification performance against that of other renowned classifiers built on the whole (original) feature (gene) space. The experimental results show that the two-stage hetero-associative memory is quite competitive with standard classification models regarding the overall accuracy, sensitivity and specificity. In addition, it also produces a significant decrease in computational efforts and an increase in the biological interpretability of microarrays because worthless (irrelevant and/or redundant) genes are discarded.

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Acknowledgements

This study was partially supported by the Valencian Council of Education, Research, Culture and Sport [PROMETEOII/2014/062], the Mexican PRODEP [DSA/103.5/15/7004], and the Spanish Ministry of Economy, Industry and Competitiveness under Grant [TIN2013-46522-P].

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Authors and Affiliations

  1. National Institute of Genomic Medicine, 14610, Ciudad de México, Mexico

    Laura Cleofas-Sánchez

  2. Department of Computer Languages and Systems, Institute of New Imaging Technologies, Universitat Jaume I, 12071, Castelló de la Plana, Spain

    J. Salvador Sánchez

  3. Multidisciplinary University Division, Universidad Autónoma de Ciudad Juárez, 32310, Ciudad Juárez, Chihuahua, Mexico

    Vicente García

Authors
  1. Laura Cleofas-Sánchez
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  2. J. Salvador Sánchez
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  3. Vicente García
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Correspondence to J. Salvador Sánchez.

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Cleofas-Sánchez, L., Sánchez, J.S. & García, V. Gene selection and disease prediction from gene expression data using a two-stage hetero-associative memory. Prog Artif Intell 8, 63–71 (2019). https://doi.org/10.1007/s13748-018-0148-6

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