Network Biology: Methods and Applications

ISBN-13: 9781493958559 / Angielski / Miękka / 2016 / 437 str.

Gerard Cagney; Andrew Emili

Opis

Network Biology presents experimental and computational approaches currently prevalent in network biology by practiced experts in the field. The text offers an ensemble of procedures for graduate students and seasoned professionals looking to polish their skill sets.

Spis treści

1. Analysis of Protein–Protein Interactions Using High-throughput Yeast Two-Hybrid Screens

            Seesandra V. Rajagopala and Peter Uetz

 

2. Identification of Mammalian Protein Complexes by Lentiviral-Based Affinity Purification and Mass Spectrometry

            Zuyao Ni, Jonathan B. Olsen, Andrew Emili, and Jack F. Greenblatt

 

3. Protein Networks Involved in Vesicle Fusion, Transport, and Storage Revealed by Array-Based Proteomics

            Mikael Bauer, Magdalena Maj, Ludwig Wagner, Dolores J. Cahill, Sara Linse, and David J. O’Connell

 

4. Identification and Relative Quantification of Native and Proteolytically Generated Protein C-termini from Complex Proteomes: C-terminome Analysis

            Oliver Schilling, Pitter F. Huesgen, Olivier Barré, and Christopher M. Overall

 

5. Construction of Protein Interaction Networks Based on the Label Free Quantitative Proteomics

            Mihaela E. Sardiu and Michael P. Washburn

 

6. Studying Binding Specificities of Peptide Recognition Modules by High-Throughput Phage Display Selections

            Haiming Huang and Sachdev S. Sidhu

 

7. Array-Based Synthetic Genetic Screens to Map Bacterial Pathways and Functional Networks in Escherichia coli

            Mohan Babu, Alla Gagarinova, and Andrew Emili

 

8. Advanced Methods for High-Throughput Microscopy Screening of Genetically Modified Yeast Libraries

            Yifat Cohen and Maya Schuldiner

 

9. Pooled Lentiviral shRNA Screening for Functional Genomics in Mammalian Cells

            Kim Blakely, Troy Ketela, and Jason Moffat

 

10. Plant DNA Sequencing for Phylogenetic Analyses: From Plants to Sequences

            Susana S. Neves and Laura L. Forrest

 

11. Using Coevolution to Predict Protein-Protein Interactions

            Gregory W. Clark, Vaqaar-un-Nisa Dar, Alexandr Bezginov, Jinhao M. Yang, Robert L. Charlebois, and Elisabeth R.M. Tillier

 

12. Visualizing Gene-Set Enrichment Results Using the Cytoscape Plugin Enrichment Map

            Daniele Merico, Ruth Isserlin, and Gary D. Bader

 

13. Quality Control Methodology for High-Throughput Protein-Protein Interaction Screening

            Alexei Vazquez, Jean-François Rual, and Kavitha Venkatesan

 

14. Filtering and Interpreting Large-Scale Experimental Protein-Protein Interaction Data

            Gabriel Musso, Andrew Emili, and Zhaolei Zhang

 

15. Classification of Cancer Patients Using Pathway Analysis and Network Clustering

            David C.Y. Fung, Amy Lo, Lucy Jankova, Stephan J. Clarke, Mark Molloy, Graham R. Robertson, and Marc R. Wilkins

 

16. Statistical Analysis of Dynamic Transcriptional Regulatory Network Structure

            Jennifer J. Smith, Ramsey A. Saleem, and John D. Aitchison

 

17. Imputing and Predicting Quantitative Genetic Interactions in Epistatic MAPs

            Colm Ryan, Gerard Cagney, Nevan Krogan, Pádraig Cunningham, and Derek Greene

 

18. Displaying Chemical Information on a Biological Network Using Cytoscape

            Iain M. Wallace, Gary D. Bader, Guri Giaever, and Corey Nislow

 

19. Modeling of Proteins and Their Assemblies with the Integrative Modeling Platform

            Benjamin Webb, Keren Lasker, Dina Schneidman-Duhovny, Elina Tjioe, Jeremy Phillips, Seung Joong Kim, Javier Velázquez-Muriel, Daniel Russel, and Andrej Sali

 

20. Predicting Node Characteristics from Molecular Networks

            Sara Mostafavi, Anna Goldenberg, and Quaid Morris

 

21. Mathematical Modeling of Biomolecular Network Dynamics

            Alexander V. Ratushny, Stephen A. Ramsey, and John D. Aitchison

Blurb

While extremely large datasets describing gene sequences, mRNA transcripts, protein abundance, and metabolite concentrations are increasingly commonplace, these represent only starting ‘parts lists’ that are usually insufficient to unlock mechanistic insights on their own right.  Fortunately, as Network Biology: Methods and Applications examines, concepts emerging from the study of biological entities such as networks (e.g. functional interactions linking genes, proteins, metabolites, etc.) suggest that order rather than chaos prevails, with such principles as modular and hierarchical organization, reactive information-driven causal-response behaviours, systems robustness, co-evolution, and self-organization guiding the way.  This volume presents detailed, practical descriptions of the experimental and computational approaches currently prevalent in network biology as written by practiced experts in the field.  Written in the highly successful Methods in Molecular Biology™ series format, relevant chapters contain introductions to their respective topics, lists of the necessary materials, step-by-step, readily reproducible protocols, and tips on troubleshooting and avoiding known pitfalls.

 

Comprehensive and accessible, Network Biology: Methods and Applications provides an ensemble of procedures that will be of great value to a broad assortment of readers, ranging from graduate students to seasoned professionals looking to polish their skill sets.