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Deep Neural Network for Supervised Inference of Gene Regulatory Network

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Modelling and Implementation of Complex Systems (MISC 2018)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 64))

Abstract

Inferring gene regulatory network from gene expression data is a challenging task in system biology. Elucidating the structure of these networks is a machine-learning problem. Several approaches have been proposed to address this challenge using unsupervised semi-supervised and supervised methods. Semi-supervised and supervised methods use primordially SVM. Most supervised approaches infer local model where each local model is associated with one TF. In this work, we propose a global model to infer gene regulatory networks from experimental data using deep neural network architecture. We evaluate our method on DREAM4 multifactorial datasets. The obtained results show that prediction accuracy using deep neural network outperform SVM in all tested data.

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Author information

Authors and Affiliations

  1. Computer Science Dept, Constantine 2 University, Ali Mendjeli, Algeria

    Meroua Daoudi

  2. MISC Laboratory, Constantine 2 University, Ali Mendjeli, Algeria

    Souham Meshoul

Authors
  1. Meroua Daoudi
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  2. Souham Meshoul
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Corresponding author

Correspondence to Meroua Daoudi .

Editor information

Editors and Affiliations

  1. Faculty of New Information and Communication Technologies, University of Constantine 2, Constantine, Algeria

    Salim Chikhi

  2. Faculty of Technology, GeCoDe Laboratory, University of Saida, Saida, Algeria

    Abdelmalek Amine

  3. Faculty of New Information and Communication Technologies, University of Constantine 2, Constantine, Algeria

    Allaoua Chaoui

  4. Faculty of New Information and Communication Technologies, University of Constantine 2, Constantine, Algeria

    Djamel Eddine Saidouni

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Daoudi, M., Meshoul, S. (2019). Deep Neural Network for Supervised Inference of Gene Regulatory Network. In: Chikhi, S., Amine, A., Chaoui, A., Saidouni, D.E. (eds) Modelling and Implementation of Complex Systems. MISC 2018. Lecture Notes in Networks and Systems, vol 64. Springer, Cham. https://doi.org/10.1007/978-3-030-05481-6_11

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