Artificial Neural Networks / edited by Hugh Cartwright.

Format:

Book

Contributor:

Cartwright, Hugh., Editor.

SpringerLink (Online service)

Series:

Springer Protocols (Springer-12345)

Methods in molecular biology 1940-6029 ; 2190

Methods in Molecular Biology, 1940-6029 ; 2190

Language:

English

Subjects (All):

Neurosciences.

Neuroscience.

Local Subjects:

Neuroscience.

Physical Description:

1 online resource (XII, 359 pages) : 134 illustrations, 114 illustrations in color.

Edition:

3rd ed. 2021.

Contained In:

Springer Nature eBook

Place of Publication:

New York, NY : Springer US : Imprint: Humana, 2021.

System Details:

text file PDF

Summary:

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.

Contents:

Identifying Genotype-Phenotype Correlations via Integrative Mutation Analysis

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

Siamese Neural Networks: An Overview

Computational Methods for Elucidating Gene Expression Regulation in Bacteria

Neuro-evolutive Algorithms Applied for Modeling Some Biochemical Separation Processes

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

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

Building and Interpreting Artificial Neural Network Models for Biological Systems

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

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

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

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

Predicting Hot-Spots using a Deep Neural Network Approach

Using Neural Networks for Relation Extraction from Biomedical Literature

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

Secure and Scalable Collection of Biomedical Data for Machine Learning Applications

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

Other Format:

Printed edition:

ISBN:

978-1-0716-0826-5

9781071608265

Access Restriction:

Restricted for use by site license.