Artificial Neural Networks

ISBN-13: 9781071608289 / Angielski / Miękka / 2021 / 359 str.

Hugh Cartwright

Spis treści

1. Identifying Genotype-Phenotype Correlations via Integrative Mutation Analysis

Edward Airey, Stephanie Portelli, Joicymara S. Xavier, YooChan Myung, Michael Silk, Malancha Karmakar, João P. L. Velloso, Carlos H. M. Rodrigues, Hardik H. Parate, Hardik H. Parate, Anjali Garg, Raghad Al-Jarf, Lucy Barr, Juliana A. Geraldo, Pâmela M. Rezende, Douglas E.V. Pires, and  David B. Ascher 

 

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

Christian Bock, Michael Moor, Catherine R. Jutzeler, and Karsten Borgwardt

 

3. Siamese Neural Networks: An Overview

Davide Chicco

 

4. Computational Methods for Elucidating Gene Expression Regulation in Bacteria

Kratika Naskulwar, Ruben Chevez-Guardado, and  Lourdes Peña-Castillo

 

5. Neuro-evolutive Algorithms Applied for Modeling Some Biochemical Separation Processes

Silvia Curteanu, Elena-Niculina Dragoi, Alexandra Cristina Blaga, Anca Irina Galaction, and Dan Cascaval

 

6. Computational Approaches for de novo Drug Design: Past, Present, and Future

Xuhan Liu, Adriaan P. IJzerman, and Gerard J. P. van Westen

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

Irene Lena Hudson

 

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

T. Murlidharan Nair

  9. A Novel Computational Approach for Biomarker Detection for Gene Expression based Computer Aided Diagnostic Systems for Breast Cancer

Ali Al-Yousef and Sandhya Samarasinghe

 

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

Xiao Tan, Andrew T Su, Hamideh Hajiabadi, Minh Tran, and Quan Nguyen

 

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

Hao Wang, Jiaxin Yang, and Jianrong Wang

 

12. Predicting Host Phenotype based on Gut Microbiome using a Convolutional Neural Network Approach

Derek Reiman, Ali M. Farhat, and Yang Dai

 

13. Predicting Hot-Spots using a Deep Neural Network Approach

António J. Preto, Pedro Matos-Filipe, José G. Almeida, Joana Mourão, and Irina S. Moreira

 

14. Using Neural Networks for Relation Extraction from Biomedical Literature

Diana Sousa, Andre Lamurias, and Francisco M. Couto

 

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

Eshel Faraggi, Robert L. Jernigan, and Andrzej Kloczkowski

 

 

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

Charles Fracchia

 

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

Mario Malcangi 

Blurb

This volume presents examples of how Artificial Neural Networks (ANNs) are applied in biological sciences and related areas. Chapters cover a wide variety of topics, including the analysis of intracellular sorting information, prediction of the behavior of bacterial communities, biometric authentication, studies of Tuberculosis, gene signatures in breast cancer classification, the use of mass spectrometry in metabolite identification, visual navigation, and computer diagnosis. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, application details for both the expert and non-expert reader, and tips on troubleshooting and avoiding known pitfalls.

 Authoritative and practical, Artificial Neural Networks: Third Edition should be of value to all scientists interested in the hands-on application of ANNs in the biosciences.