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Bioinformatics Advancements for Detecting Epidemic Disease Using Machine Learning Approaches

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Electronic Systems and Intelligent Computing

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 686))

Abstract

In the twentieth century, many researchers have started working on bioinformatics for disease biomarker detection using genetic information, i.e., DNA microarray dataset and RNA sequencing dataset with machine learning approaches. The journey of this concept starts with the classification technique on DNA microarray dataset by comparing it with reference genome or by deNovo (without reference genome) technique, and lots of different tools were published in different publications. Later, with the availability and advancement of computational power many researchers started working on large RNA sequencing dataset and some tools are published again with significant features. Nowadays, also this area is like a newborn baby and several challenges are still not solved, but it does not have a proper guideline for new researchers to face those challenges. After analyzing so many tools on DNA as well as RNA, we are able to summarize these works with a common workflow, and in this paper, we have proposed a generalized workflow for detecting epidemic diseases like HIV-AIDS, Cancer using machine learning approaches.

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Authors and Affiliations

  1. Department of Computer Science and Engineering, National Institute of Technology Arunachal Pradesh, Papum Pare, India

    Bikash Baruah & Manash Pratim Dutta

Authors
  1. Bikash Baruah
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  2. Manash Pratim Dutta
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Correspondence to Bikash Baruah .

Editor information

Editors and Affiliations

  1. School of Computer Engineering, Kalinga Institute of Industrial Technology (KIIT) Deemed to be University, Bhubaneswar, Odisha, India

    Pradeep Kumar Mallick

  2. Department of Electronics and Communication Engineering, National Institute of Technology Arunachal Pradesh, Yupia, Arunachal Pradesh, India

    Preetisudha Meher

  3. Department of Electronics and Communication Engineering, National Institute of Technology Arunachal Pradesh, Yupia, Arunachal Pradesh, India

    Alak Majumder

  4. Department of Electronics and Communication Engineering, National Institute of Technology Rourkela, Rourkela, Odisha, India

    Santos Kumar Das

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Baruah, B., Dutta, M.P. (2020). Bioinformatics Advancements for Detecting Epidemic Disease Using Machine Learning Approaches. In: Mallick, P.K., Meher, P., Majumder, A., Das, S.K. (eds) Electronic Systems and Intelligent Computing. Lecture Notes in Electrical Engineering, vol 686. Springer, Singapore. https://doi.org/10.1007/978-981-15-7031-5_100

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  • DOI: https://doi.org/10.1007/978-981-15-7031-5_100

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-15-7030-8

  • Online ISBN: 978-981-15-7031-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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