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Medientyp: E-Book Titel: Data analytics in bioinformatics : a machine learning perspective Beteiligte: Satpathy, Rabinarayan [Herausgeber:in]; Choudhury, Tanupriya [Herausgeber:in]; Satpathy, Suneeta [Herausgeber:in]; Mohanty, Sachi Nandan [Herausgeber:in]; Zhang, Xiaobo [Herausgeber:in] Erschienen: Hoboken, NJ: Scrivener Publishing, Wiley, 2021 Ausgabe: First edition Umfang: 1 Online-Ressource Sprache: Englisch DOI: 10.1002/9781119785620 ISBN: 9781119785620 Identifikator: Schlagwörter: Bioinformatik Entstehung: Anmerkungen: Description based on publisher supplied metadata and other sources Beschreibung: Cover -- Half-Title Page -- Series Page -- Title Page -- Copyright Page -- Contents -- Preface -- Acknowledgement -- Part 1: THE COMMENCEMENT OF MACHINE LEARNING SOLICITATION TO BIOINFORMATICS -- 1 Introduction to Supervised Learning -- 1.1 Introduction -- 1.2 Learning Process & -- its Methodologies -- 1.2.1 Supervised Learning -- 1.2.2 Unsupervised Learning -- 1.2.3 Reinforcement Learning -- 1.3 Classification and its Types -- 1.4 Regression -- 1.4.1 Logistic Regression -- 1.4.2 Difference between Linear & -- Logistic Regression -- 1.5 Random Forest -- 1.6 K-Nearest Neighbor -- 1.7 Decision Trees -- 1.8 Support Vector Machines -- 1.9 Neural Networks -- 1.10 Comparison of Numerical Interpretation -- 1.11 Conclusion & -- Future Scope -- References -- 2 Introduction to Unsupervised Learning in Bioinformatics -- 2.1 Introduction -- 2.2 Clustering in Unsupervised Learning -- 2.3 Clustering in Bioinformatics-Genetic Data -- 2.3.1 Microarray Analysis -- 2.3.2 Clustering Algorithms -- 2.3.3 Partition Algorithms -- 2.3.4 Hierarchical Clustering Algorithms -- 2.3.5 Density-Based Approach -- 2.3.6 Model-Based Approach -- 2.3.7 Grid-Based Clustering -- 2.3.8 Soft Clustering -- 2.4 Conclusion -- References -- 3 A Critical Review on the Application of Artificial Neural Network in Bioinformatics -- 3.1 Introduction -- 3.1.1 Different Areas of Application of Bioinformatics -- 3.1.2 Bioinformatics in Real World -- 3.1.3 Issues with Bioinformatics -- 3.2 Biological Datasets -- 3.3 Building Computational Model -- 3.3.1 Data Pre-Processing and its Necessity -- 3.3.2 Biological Data Classification -- 3.3.3 ML in Bioinformatics -- 3.3.4 Introduction to ANN -- 3.3.5 Application of ANN in Bioinformatics -- 3.3.6 Broadly Used Supervised Machine Learning Techniques -- 3.4 Literature Review.