Artificial Neural Networks

Chapter 1 Identifying Genotype-Phenotype Correlations via Integrative Mutation Analysis.

Chapter 2 Machine Learning for Biomedical Time Series Classification: From Shapelets to Deep Learning

Chapter 3 Siamese Neural Networks: An Overview

Chapter 4 Computational Methods for Elucidating Gene Expression Regulation in Bacteria

Chapter 5 Neuroevolutive Algorithms Applied for Modeling Some Biochemical Separation Processes

Chapter 6 Computational Approaches for De Novo Drug Design: Past, Present, and Future

Chapter 7 Data Integration Using Advances in Machine Learning in Drug Discovery and Molecular Biology

Chapter 8 Building and Interpreting Artificial Neural Network Models for Biological Systems

Chapter 9 A Novel Computational Approach for Biomarker Detection for Gene Expression-Based Computer-Aided Diagnostic Systems for Breast Cancer

Chapter 10 Applying Machine Learning for Integration of Multi-Modal Genomics Data and Imaging Data to Quantify Heterogeneity in Tumour Tissues

Chapter 11 Leverage Large-Scale Biological Networks to Decipher the Genetic Basis of Human Diseases Using Machine Learning

Chapter 12 Predicting Host Phenotype Based on Gut Microbiome Using a Convolutional Neural Network Approach.

Chapter 13 Predicting Hot Spots Using a Deep Neural Network Approach

Chapter 14 Using Neural Networks for Relation Extraction from Biomedical Literature

Chapter 15 A Hybrid Levenberg-Marquardt Algorithm on a Recursive Neural Network for Scoring Protein Models

Chapter 16 Secure and Scalable Collection of Biomedical Data for Machine Learning Applications

Chapter 17 AI-Based Methods and Technologies to Develop Wearable Devices for Prosthetics and Predictions of Degenerative Diseases