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Methods in Molecular Biology #781: Network Biology: Methods and Applications

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Methods in Molecular Biology #781: Network Biology: Methods and Applications Cover

 

Synopses & Reviews

Publisher Comments:

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.

Synopsis:

Network Biology presents experimental and computational approaches currently prevalent in network biology by practiced experts in the field.

Synopsis:

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.

Table of Contents

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

Product Details

ISBN:
9781617792755
Author:
Cagney, Gerard (edt)
Publisher:
Humana Press
Author:
Emili, Andrew
Author:
Cagney, Gerard
Location:
Totowa, NJ
Subject:
Computational approaches
Subject:
Data analysis
Subject:
Experimental approaches
Subject:
Gene isoforms
Subject:
Gene sequences
Subject:
Interaction Networks
Subject:
Metabolite concentrations
Subject:
Next-generation sequencing
Subject:
Protein complexes
Subject:
Quantitative ‘omic’ datasets
Subject:
mRNA transcripts
Subject:
Bioinformatics
Subject:
Systems Biology
Subject:
Computer Appl. in Life Sciences <p>Combines accurate high-throughput methods and innovative integrative analytical tools to approach network biology as comprehensively as possible</p><p>Features step-by-step guidance on a wide variety of methods and appli
Subject:
Computers Reference-Bioinformatics
Subject:
Physiology
Subject:
Computer Appl. in Life Sciences
Subject:
Life sciences
Subject:
B
Subject:
Biomedical and Life Sciences
Subject:
Biological models
Subject:
Biology_xData processing
Copyright:
Edition Description:
2011
Series:
Methods in Molecular Biology
Series Volume:
781
Publication Date:
20110907
Binding:
HARDCOVER
Language:
English
Pages:
452
Dimensions:
254 x 178 mm 1013 gr

Related Subjects

Computers and Internet » Computers Reference » Bioinformatics
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Health and Self-Help » Health and Medicine » Anatomy and Physiology
Science and Mathematics » Biology » Cytology and Cell Biology
Science and Mathematics » Biology » General
Science and Mathematics » Biology » Molecular

Methods in Molecular Biology #781: Network Biology: Methods and Applications New Hardcover
0 stars - 0 reviews
$139.00 In Stock
Product details 452 pages Humana Press - English 9781617792755 Reviews:
"Synopsis" by , Network Biology presents experimental and computational approaches currently prevalent in network biology by practiced experts in the field.
"Synopsis" by , 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.
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