Advances in bioengineering. (2020)

• Record Type: Book
• Further Information: Note: Renu Vyas, editors.
• Other Names: Vyas, Renu
• Contents: Intro -- Foreword -- Preface -- About the Book -- Contents -- About the Editor -- Part I: Data Engineering -- 1: Modelling of Protein Complexes Involved in Signalling Pathway for Non-small Cell Lung Cancer -- 1.1 Introduction to Pathway Modelling -- 1.2 Methods in Pathway Modelling -- 1.2.1 Mathematical Modelling Approach -- 1.2.1.1 Boolean Networking -- 1.2.1.2 Ordinary Differential Equation -- 1.2.1.3 Stoichiometric Approach -- 1.2.2 Network-Based Modelling Approach -- 1.2.2.1 Bayesian Method -- 1.2.2.2 Gaussian Networking -- 1.2.2.3 Maximum Likelihood Approach 1.2.2.4 Hidden Markov Model -- 1.2.2.5 Latent Variable Model -- 1.2.3 Molecular Modelling Approach in Lung Cancer -- 1.3 Signalling Pathways in NSCLC -- 1.3.1 MAPK Pathway -- 1.3.2 NF-ƙB Pathway -- 1.3.3 RAS Pathway -- 1.4 Molecular Dynamics Approach in NSCLC Pathway -- 1.5 Conclusion -- References -- 2: Role of BioJava in the Department of Bioinformatics Tools -- 2.1 What Is Bioinformatics? -- 2.2 Application of Java in Bioinformatics -- 2.3 Introduction to BioJava -- 2.4 The BioJava Modules -- 2.4.1 Core of BioJava -- 2.4.2 Alignment Module -- 2.4.3 Structure Module 2.4.4 ModFinder Module -- 2.4.5 Protein Disorder Module -- 2.4.6 Web Service Access Module -- 2.5 The BioJava Packages -- 2.5.1 Sequence Matching -- 2.5.2 Symbolic Representation for Sequence -- 2.5.3 Biological Sequence Data -- 2.5.4 Process and Produce Flat File of Sequences -- 2.5.5 GUI Representation of the Sequences -- 2.5.6 Sequence Database -- 2.5.7 Input Output Utility -- 2.5.8 Network Programming Utility -- 2.5.9 To Manage and Generate XML Document -- 2.5.10 To Generate HTML Reports from Blast Output -- 2.6 BioJava: A Tutorial with the NetBeans IDE 2.6.1 Download and Install jdk 1.8+ Versions -- 2.6.2 Download BioJava packages -- 2.6.3 Add .jar File in NetBeans Project -- 2.7 Design and Implementation -- 2.8 Exception Handling in BioJava -- 2.9 How to Contribute in BioJava Open-Source Project? -- 2.10 Conclusions -- References -- 3: Overview of Machine Learning Methods in ADHD Prediction -- 3.1 Attention Deficit Hyperactivity Disorder (ADHD) -- 3.1.1 Symptoms and Causes of ADHD -- 3.1.2 Diagnosis and Prediction of ADHD -- 3.2 Overview of Various Machine Learning Methods in Predictive Analysis 3.2.1 ADHD Prediction Using Machine Learning Models -- 3.3 Genetic Programming -- 3.4 Conclusion -- References -- 4: Applications of Deep Learning in Drug Discovery -- 4.1 Introduction -- 4.2 Machine Learning Primer -- 4.3 ANNs and Deep Learning -- 4.4 Deep Neural Network Architectures -- 4.4.1 Convolutional Neural Networks (CNNs) -- 4.4.2 Recurrent Neural Networks (RNNs) -- 4.4.3 Autoencoders (AEs) and Variational Autoencoders (VAEs) -- 4.4.4 Generative Adversarial Networks (GANs) -- 4.5 Deep Learning Applications in Drug Discovery
• Publisher Details: Singapore : Springer
• Publication Date: 2020
• Extent: 1 online resource (229 p.)
• Subjects: 660.6; Bioengineering; Bioengineering; Electronic books; Electronic books
• Languages: English
• ISBNs: 9789811520631; 9811520631
• Related ISBNs: 9789811520624; 9811520623
• Access Rights: Legal Deposit; Only available on premises controlled by the deposit library and to one user at any one time; The Legal Deposit Libraries (Non-Print Works) Regulations (UK).
• Access Usage: Restricted: Printing from this resource is governed by The Legal Deposit Libraries (Non-Print Works) Regulations (UK) and UK copyright law currently in force.