Integration and Visualization of Gene Selection and Gene Regulatory Networks for Cancer Genome
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Integration and Visualization of Gene Selection and Gene Regulatory Networks for Cancer Genome

1st Edition - May 9, 2018

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  • Authors: Shruti Mishra, Debahuti Mishra, Sandeep Satpathy
  • Paperback ISBN: 9780128163566
  • eBook ISBN: 9780128163573

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Description

Integration and Visualization of Gene Selection and Gene Regulatory Networks for Cancer Genome helps readers identify and select the specific genes causing oncogenes. The book also addresses the validation of the selected genes using various classification techniques and performance metrics, making it a valuable source for cancer researchers, bioinformaticians, and researchers from diverse fields interested in applying systems biology approaches to their studies.

Key Features

  • Provides well described techniques for the purpose of gene selection/feature selection for the generation of gene subsets
  • Presents and analyzes three different types of gene selection algorithms: Support Vector Machine-Bayesian T-Test-Recursive Feature Elimination (SVM-BT-RFE), Canonical Correlation Analysis-Trace Ratio (CCA-TR), and Signal-To-Noise Ratio-Trace Ratio (SNRTR)
  • Consolidates fundamental knowledge on gene datasets and current techniques on gene regulatory networks into a single resource

Readership

Bioinformaticians, Cancer Researchers, researchers interested in applying Systems Biology approaches to their studies; Geneticists, Bioengineers, researchers interested in Machine learning, Data Mining, Bioinformatics

Table of Contents

  • 1. Literature Review
    2. SVM-BT-RFE: An Improved Gene Selection Framework Using Bayesian T-Test Embedded in Support Vector Machine (Recursive Feature Elimination) Algorithm
    3. Enhanced Gene Ranking Approaches Using Modified Trace Ratio Algorithm for Gene Expression Data
    4. SNR-TR Gene Ranking Method: A Signal-to-Noise Ratio Based Gene Selection Algorithm Using Trace Ratio for Gene Expression Data
    5. Visualization of Interactive Gene Regulatory Network Using Gene Selection Techniques from Expression Data
    6. Conclusion and Future Work

Product details

  • No. of pages: 200
  • Language: English
  • Copyright: © Academic Press 2018
  • Published: May 9, 2018
  • Imprint: Academic Press
  • Paperback ISBN: 9780128163566
  • eBook ISBN: 9780128163573

About the Authors

Shruti Mishra

Dr. Mishra is currently working as an Associate Professor in the Department of Computer Science & Engineering, Vignana Bharathi Institute of Technology, Hyderabad and as former Head of the Department for the same institution. She was earlier working as an Assistant Professor, Department of Computer Science & Engineering, Institute of Technical Education & Research, Siksha O Anusandhan (Deemed-to-be University), Bhubaneswar, Odisha, India. She has guided 5 M.Tech thesis and more than 30 B.Tech students. Dr. Mishra has around 22 publications in various peer-reviewed journals and conference, 3 book chapters and 1 book to her credit. Her area of research is basically in Data Mining, Bioinformatics and Machine Learning. She is currently into the field of Geoinformatics and Deep Learning.

Affiliations and Expertise

Associate Professor, Department of Computer Science & Engineering, Vignana Bharathi Institute of Technology (VBIT), Hyderabad, India

Debahuti Mishra

Affiliations and Expertise

Department of Computer Science and Engineering, Institute of Technical Education and Research, Siksha ‘O’ Anusandhan, Bhubaneswar, Odisha, India

Sandeep Satpathy

Affiliations and Expertise

Department of Computer Science and Engineering, Vignana Bharathi Institute of Technology (VBIT), Hyderabad, India

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