Analyzing Network Data in Biology and Medicine

Analyzing Network Data in Biology and Medicine

Medical Books
ISBN: 1108432239Format: PDFEdition: -Date: June 13, 2019Pages: 643 pagesLanguage: English

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Book Description

The increased and widespread availability of large network data resources in recent years has resulted in a growing need for effective methods for their analysis. The challenge is to detect patterns that provide a better understanding of the data. However, this is not a straightforward task because of the size of the data sets and the computer power required for the analysis. The solution is to devise methods for approximately answering the questions posed, and these methods will vary depending on the data sets under scrutiny. This cutting-edge text introduces biological concepts and biotechnologies producing the data, graph and network theory, cluster analysis and machine learning, before discussing the thought processes and creativity involved in the analysis of large-scale biological and medical data sets, using a wide range of real-life examples. Bringing together leading experts, this text provides an ideal introduction to and insight into the interdisciplinary field of network data analysis in biomedicine.


1. From Genetic Data to Medicine: From DNA Samples to Disease Risk Prediction in Personalized Genetic Tests
2. Epigenetic Data and Disease
3. Introduction to Graph and Network Theory
4. Protein–Protein Interaction Data, their Quality, and Major Public Databases
5. Graphlets in Network Science and Computational Biology
6. Unsupervised Learning: Cluster Analysis
7. Machine Learning for Data Integration in Cancer Precision Medicine: Matrix Factorization Approaches
8. Machine Learning for Biomarker Discovery: Significant Pattern Mining
9. Network Alignment
10. NetworkMedicine
11. Elucidating Genotype-to-Phenotype Relationships via Analyses of Human Tissue Interactomes
12. Network Neuroscience
13. Cytoscape: A Tool for Analyzing and Visualizing Network Data
14. Analysis of the Signatures of Cancer Stem Cells in Malignant Tumors Using Protein Interactomes and the STRING Database

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Analyzing Network Data in Biology and Medicine
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