174,99 €
inkl. MwSt.
Versandkostenfrei*
Versandfertig in über 4 Wochen
payback
87 °P sammeln
  • Gebundenes Buch

This book describes approaches for recognizing and classifying proteins into families of evolutionary related proteins. Reviewing all the major resources for classifying protein families, the book combines descriptions of general philosophies of protein family classification systems with detailed descriptions and examples of selected families found in different biological systems. Scientists in diverse areas of biology and protein science will learn how to use the various resources and databases and gain valuable insight into how proteins evolve and how new functional repertoires…mehr

Produktbeschreibung
This book describes approaches for recognizing and classifying proteins into families of evolutionary related proteins. Reviewing all the major resources for classifying protein families, the book combines descriptions of general philosophies of protein family classification systems with detailed descriptions and examples of selected families found in different biological systems. Scientists in diverse areas of biology and protein science will learn how to use the various resources and databases and gain valuable insight into how proteins evolve and how new functional repertoires emerge.
New insights into the evolution and nature of proteins

Exploring several distinct approaches, this book describes the methods for comparing protein sequences and protein structures in order to identify homologous relationships and classify proteins and protein domains into evolutionary families. Readers will discover the common features as well as the key philosophical differences underlying the major protein classification systems, including Pfam, Panther, SCOP, and CATH. Moreover, they'll discover how these systems can be used to understand the evolution of protein families as well as understand and predict the degree to which structural and functional information are shared between relatives in a protein family.

Edited and authored by leading international experts, Protein Families offers new insights into protein families that are important to medical research as well as protein families that help us understand biological systems and key biological processes such as cell signaling and the immune response. The book is divided into three sections:
Section I: Concepts Underlying Protein Family Classification reviews the major strategies for identifying homologous proteins and classifying them into families.
Section II: In-Depth Reviews of Protein Families focuses on some fascinating super protein families for which we have substantial amounts of sequence, structural and functional data, making it possible to trace the emergence of functionally diverse relatives.
Section III: Review of Protein Families in Important Biological Systems examines protein families associated with a particular biological theme, such as the cytoskeleton.

All chapters are extensively illustrated, including depictions of evolutionary relationships. References at the end of each chapter guide readers to original research papers and reviews in the field.

Covering protein family classification systems alongside detailed descriptions of select protein families, this book offers biochemists, molecular biologists, protein scientists, structural biologists, and bioinformaticians new insight into the evolution and nature of proteins.
Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
Autorenporträt
CHRISTINE ORENGO, PhD, is Professor of Bioinformatics at University College London. Dr. Orengo's research focuses on protein structure comparison, classification, and analysis. Her group develops the CATH domain family classification and algorithms for predicting protein functions and functional networks. ALEX BATEMAN, PhD, is Senior Investigator at Wellcome Trust Sanger Institute, where he leads the Pfam database project. Dr. Bateman also participates in the European InterPro project, which seeks to merge the annotations from Pfam, PRINTS, Prosite, and other domain databases.