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Systems Biology Approach to Analyze Microarray Datasets for Identification of Disease-Causing Genes: Case Study of Oral Squamous Cell Carcinoma

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Reverse Engineering of Regulatory Networks

Part of the book series: Methods in Molecular Biology ((MIMB,volume 2719))

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Abstract

The discovery of potential disease-causing genes can aid medical progress. The post-genomic era has made this a more difficult task. Modern high-throughput methods have not solved the problem of identifying disease genes. Conventional methods cannot be used to investigate many rare or lethal diseases. Monitoring gene expression values in different samples using microarray technology is one of the best and most accurate ways to identify disease-causing genes. One of the most recent advances in experimental molecular biology is microarrays, which allow researchers to simultaneously monitor the expression levels of thousands of genes. Statistical analysis of microarray data might aid gene discovery by revealing pathways related to the target gene and facilitating identification of candidate genes. Systems biology, an interdisciplinary approach, has emerged as a crucial analytic tool with the potential to reveal previously unidentified causes and consequences of human illness. Genetic, environmental, immunological, or neurological factors have been implicated in the developing complex disorders like cancer. Because of this, it is important to approach the study of such disease from a novel perspective. The system biology approach allows us to rapidly identify disease-causing genes and assess their viability as therapeutic targets. This chapter demonstrates systems biology approaches to identify candidate genes using public database. Oral squamous cell carcinoma (OSCC) is used as a model disease to show how systems biology can be used successfully to identify and prioritize disease genes.

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Author information

Authors and Affiliations

  1. Raipur Institute of Technology, Raipur, Chhattisgarh, India

    Jyotsna Choubey & Tanushree Chatterjee

  2. Department of Systems Biology & Bioinformatics, University of Rostock, Rostock, Germany

    Olaf Wolkenhauer

Authors
  1. Jyotsna Choubey
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  2. Olaf Wolkenhauer
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  3. Tanushree Chatterjee
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Editor information

Editors and Affiliations

  1. Department of Electronics and Communication Engineering, Jalpaiguri Govt. Engineering College, Jalpaiguri, West Bengal, India

    Sudip Mandal

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© 2024 The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature

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Choubey, J., Wolkenhauer, O., Chatterjee, T. (2024). Systems Biology Approach to Analyze Microarray Datasets for Identification of Disease-Causing Genes: Case Study of Oral Squamous Cell Carcinoma. In: Mandal, S. (eds) Reverse Engineering of Regulatory Networks. Methods in Molecular Biology, vol 2719. Humana, New York, NY. https://doi.org/10.1007/978-1-0716-3461-5_2

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  • DOI: https://doi.org/10.1007/978-1-0716-3461-5_2

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  • Publisher Name: Humana, New York, NY

  • Print ISBN: 978-1-0716-3460-8

  • Online ISBN: 978-1-0716-3461-5

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