Handbook of Statistical Bioinformatics

This handbook provides authoritative contributions on modern methods and tools in statistical bioinformatics, focusing on the interface between computational statistics and computational biology. It covers single-cell analysis, network analysis, and systems biology, with contributions by leading experts on probabilistic and statistical modeling and the analysis of massive data sets. It is a valuable resource for students, researchers, and practitioners in statistics, computer science, and biological and biomedical research.

Format: Hardback
Length: 410 pages
Publication date: 09 December 2022
Publisher: Springer-Verlag Berlin and Heidelberg GmbH & Co. KG

In its second edition, this comprehensive handbook gathers authoritative insights into modern methods and tools in statistical bioinformatics, with a particular emphasis on the interplay between computational statistics and cutting-edge advancements in computational biology. The book is divided into three parts, each dedicated to statistical approaches for single-cell analysis, network analysis, and systems biology. Renowned experts contribute their expertise to address key topics in probabilistic and statistical modeling, as well as the analysis of vast data sets generated by modern biotechnology. This handbook serves as an invaluable resource for students, researchers, and practitioners in statistics, computer science, biological and biomedical research, who are eager to stay abreast of the latest developments in computational statistics as applied to computational biology.

Introduction:
Statistical bioinformatics plays a pivotal role in analyzing biological data, enabling researchers to uncover patterns, relationships, and insights that would otherwise remain hidden. With the rapid advancements in biotechnology and computational technologies, the field has witnessed a surge in innovative methods and tools that facilitate the analysis of large and complex data sets. This handbook aims to provide a comprehensive and up-to-date overview of the latest developments in statistical bioinformatics, focusing on the interface between computational statistics and computational biology.

Single-Cell Analysis:
Single-cell analysis is a rapidly growing field that involves the study of individual cells within a biological sample. It provides a deeper understanding of cell heterogeneity, gene expression, and cellular processes. The handbook includes chapters on statistical methods for single-cell analysis, such as dimensionality reduction, clustering, and differential expression analysis. These methods help researchers identify unique cell populations, identify regulatory networks, and predict cellular responses to environmental stimuli.

Network Analysis:
Network analysis is a powerful tool for understanding the complex interactions between biological entities, such as genes, proteins, and cells. The handbook includes chapters on statistical methods for network analysis, such as graph theory, network inference, and community detection. These methods help researchers identify key nodes in the network, identify regulatory relationships, and predict disease outcomes.

Systems Biology:
Systems biology is an interdisciplinary field that aims to understand the complex interactions between biological systems at multiple scales. The handbook includes chapters on statistical methods for systems biology, such as model fitting, simulation, and Bayesian inference. These methods help researchers build predictive models of biological systems, identify biomarkers for disease, and optimize drug discovery processes.

Conclusion:
In conclusion, this handbook serves as a valuable resource for students, researchers, and practitioners in statistics, computer science, biological and biomedical research. It provides a comprehensive overview of the latest developments in statistical bioinformatics, with a focus on the interface between computational statistics and computational biology. By leveraging the power of statistical methods and computational tools, researchers can gain a deeper understanding of biological systems and make meaningful contributions to their fields.

Weight: 793g
Dimension: 235 x 155 (mm)
ISBN-13: 9783662659014
Edition number: 2nd ed. 2022