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International Conference on Big Data, Cloud and Applications

BDCA 2018: Big Data, Cloud and Applications pp 210–221Cite as

Advanced Machine Learning Models for Large Scale Gene Expression Analysis in Cancer Classification: Deep Learning Versus Classical Models

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Part of the book series: Communications in Computer and Information Science ((CCIS,volume 872))

Abstract

Analysis of large gene expression datasets for cancer classification is a crucial task in bioinformatics and a very challenging one as well. In this paper, we explore the potential of using advanced models in machine learning namely those based on deep learning to handle such task. For this purpose we propose a deep feed forward neural network architecture. In addition, we also investigate other classical yet very popular machine learning classifiers namely, support vector machine, naive bayes, k-nearest neighbours and shallow neural networks. The main objective is to appreciate the extent to which they are able to deal with the increasing size of these datasets. We conducted our experimental study using a high-performance computing platform with 32 compute nodes, each consisting of two Intel (R) Xeon (R) CPU E5-2650 2.00 GHz processors. Each processor is made up of 8 cores. Five data sets available at the omnibus library have been used to test the five models . Experimental results show the effectiveness of deep learning and its ability to deal with large scale data.

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Acknowledgement

We express our sincere gratitude to every one that help us to accomplish this work. This was granted access to the HPC ressources of UCI-UFMC ‘(Unité de Calcul Intensif)’ of the University FRERES MENTOURI CONSTANTINE1. This work has been supported by the national research project CNEPRU under-grant N:B*07120140037.

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Authors and Affiliations

  1. Computer Science Department, Faculty of NTIC, University Constantine 2 - Abdelhamid Mehri Biotechnology Research Center (CRBt) & CERIST, Constantine, Algeria

    Imene Zenbout & Souham Meshoul

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  1. Imene Zenbout
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  2. Souham Meshoul
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Correspondence to Imene Zenbout .

Editor information

Editors and Affiliations

  1. Abdelmalek Essaâdi University, Tétouan, Morocco

    Youness Tabii

  2. Abdelmalek Essaâdi University, Tétouan, Morocco

    Mohamed Lazaar

  3. Abdelmalek Essaâdi University, Tétouan, Morocco

    Mohammed Al Achhab

  4. Université Ibn-Tofail, Tétouan, Morocco

    Nourddine Enneya

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Zenbout, I., Meshoul, S. (2018). Advanced Machine Learning Models for Large Scale Gene Expression Analysis in Cancer Classification: Deep Learning Versus Classical Models. In: Tabii, Y., Lazaar, M., Al Achhab, M., Enneya, N. (eds) Big Data, Cloud and Applications. BDCA 2018. Communications in Computer and Information Science, vol 872. Springer, Cham. https://doi.org/10.1007/978-3-319-96292-4_17

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  • DOI: https://doi.org/10.1007/978-3-319-96292-4_17

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  • Publisher Name: Springer, Cham

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  • Online ISBN: 978-3-319-96292-4

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