Yeast Systems Biology : Methods and Protocols (Methods in Molecular Biology)

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Yeast Systems Biology : Methods and Protocols (Methods in Molecular Biology)

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  • 製本 Paperback:紙装版/ペーパーバック版/ページ数 535 p.
  • 言語 ENG
  • 商品コード 9781493961351
  • DDC分類 579.562

Full Description

Systems Biology aims at deciphering the genotype-phenotype relationships at the levels of genes, transcripts (RNAs), peptides, proteins, metabolites, and environmental factors participating in complex cellular networks in order to reveal the mechanisms and principles governing the behavior of complex biological systems.  Yeast Systems Biology: Methods and Protocols presents an up-to-date view of the optimal characteristics of the yeast Saccharomyces cerevisiae as a model eukaryote, perspective on the latest experimental and computational techniques  for systems biology studies, most of which were first designed for and validated in yeast, and selected examples of yeast systems biology studies and their applications in biotechnology and medicine.  These experiments under controlled conditions can uncover the complexity and interplay of biological networks with their dynamics, basic principles of internal organization, and balanced orchestrated functions between organelles in direct interaction with the environment as well as the characterization of short and long-term effects of perturbations and dysregulation of networks that may illuminate the origin of complex human diseases.  Written for the highly successful Methods in Molecular Biology™ series, this volume contains the kind of detailed description and implementation advice that is crucial for getting optimal results.

 

Practical and cutting-edge, Yeast Systems Biology: Methods and Protocols serves researchers interested in comprehensive systems biology strategies in well-defined model systems with specific objectives as well as a better knowledge of the latest post-genomic strategies at all 'omic levels and computational approaches towards analysis, integration, and modeling of biological systems, from single-celled organisms to higher eukaryotes.

Contents

Yeast Systems Biology: The Challenge of Eukaryotic Complexity.- Saccharomyces cerevisiae: Gene Annotation and Genome Variability, State-of-the-Art Through Comparative Genomics.- Genome-Wide Measurement of Histone H3 Replacement Dynamics in Yeast.- Genome-Wide Approaches to Studying Yeast Chromatin Modifications.- Absolute and Relative Quantification of mRNA Expression (Transcript Analysis).- Enrichment of Unstable Non-Coding RNAs and Their Genome-Wide Identification.- Genome-Wide Transcriptome Analysis in Yeast Using High-Density Tiling Arrays.- RNA Sequencing.- Polyadenylation State Microarray (PASTA) Analysis.- Enabling Technologies for Yeast Proteome Analysis.- Protein Turnover Methods in Single-Celled Organisms: Dynamic SILAC.- Protein-Protein Interactions and Networks: Forward and Reverse Edgetics.- Use of Proteome Arrays to Globally Identify Substrates for E3 Ubiquitin Ligases.- Fit for Purpose Quenching and Extraction Protocols for Metabolic Profiling of Yeast Using Chromatography-Mass Spectrometry Platforms.- The Automated Cell: Compound and Environment Screening System (ACCESS) for Chemogenomic Screening.- Competition Experiments Coupled with High-Throughput Analyses for Functional Genomics Studies in Yeast.- Fluorescence Fluctuation Spectroscopy and Imaging Methods for Examination of Dynamic Protein Interactions in Yeast.- Nutritional Control of Cell Growth Via TOR Signaling in Budding Yeast.- Computational Yeast Systems Biology: A Case Study for the MAP Kinase Cascade.- Standards, Tools, and Databases for the Analysis of Yeast 'Omics Data.- A Computational Method to Search for DNA Structural Motifs in Functional Genomic Elements.- High Throughput Analyses and Curation of Protein Interactions in Yeast.- Noise in Biological Systems: Pros, Cons, and Mechanisms of Control.- Genome-Scale Integrative Data Analysis and Modeling of Dynamic Processes in Yeast.- Genome-Scale Metabolic Models of Saccharomyces cerevisiae.- Representation, Simulation, and Hypothesis Generation in Graph and Logical Models of Biological Networks.- Use of Genome-Scale Metabolic Models in Evolutionary Systems Biology.- Saccharomyces cerevisiae Contributions Towards Understanding Mammalian Gene Function and Therapy.

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