Coverart for item
The Resource Proteome bioinformatics, edited by Shivakumar Keerthikumar and Suresh Mathivanan

Proteome bioinformatics, edited by Shivakumar Keerthikumar and Suresh Mathivanan

Label
Proteome bioinformatics
Title
Proteome bioinformatics
Statement of responsibility
edited by Shivakumar Keerthikumar and Suresh Mathivanan
Contributor
Subject
Language
eng
Summary
This thorough book covers the most recent proteomics techniques, databases, bioinformatics tools, and computational approaches that are used for the identification and functional annotation of proteins and their structure. The most recent proteomic resources widely used in the biomedical scientific community for storage and dissemination of data are discussed. In addition, specific MS/MS spectrum similarity scoring functions and their application in the field of proteomics, statistical evaluation of labeled comparative proteomics using permutation testing, and methods of phylogenetic analysis using MS data are also described in detail. Written for the highly successful Methods in Molecular Biology series, chapters contain the kind of detail and key implementation advice to ensure successful results. Authoritative and cutting-edge, Proteome Bioinformatics serves as a useful resource for researchers who are beginners as well as advanced investigators in the field of proteomics
Member of
Dewey number
572/.60285
Illustrations
illustrations
Index
index present
Literary form
non fiction
Nature of contents
  • dictionaries
  • bibliography
http://library.link/vocab/relatedWorkOrContributorName
  • Keerthikumar, Shivakumar,
  • Mathivanan, Suresh,
Series statement
  • Springer protocols
  • Methods in molecular biology,
Series volume
1549
http://library.link/vocab/subjectName
Proteomics
Label
Proteome bioinformatics, edited by Shivakumar Keerthikumar and Suresh Mathivanan
Instantiates
Publication
Copyright
Bibliography note
Includes bibliographical references and index
Color
mixed
Contents
  • TMT one-stop shop : from reliable sample preparation to computational analysis platform
  • Mehdi Mirzaei, Dana Pascovici, Jemma X. Wu, Joel Chick, Yunqi Wu, Brett Cooke, Paul Haynes, and Mark P. Molloy
  • Unassigned MS/MS spectra : who am I?
  • Mohashin Pathan, Monisha Samuel, Shivakumar Keerthikumar, and Suresh Mathivanan
  • Methods to calculate spectrum similarity
  • Şule Yilmaz, Elien Vandermarliere, and Lennart Martens
  • Proteotypic peptides and their applications
  • Shivakumar Keerthikumar and Suresh Mathivanan
  • Statistical evaluation of labeled comparative profiling proteomics experiments using permutation test
  • Hien D. Nguyen, Geoffrey J. McLachlan, and Michelle M. Hill
  • Introduction to proteome bioinformatics
  • De novo peptide sequencing : deep mining of high-resolution mass spectrometry data
  • Mohammad Tawhidul Islam, Abidali Mohamedali, Criselda Santan Fernandes, Mark S. Baker, and Shoba Ranganathan
  • Phylogenetic analysis using protein mass spectrometry
  • Shiyong Ma, Kevin M. Downard, and Jason W.H. Wong
  • Bioinformatics methods to deduce biological interpretation from proteomics data
  • Krishna Patel, Manika Singh, and Harsha Gowda
  • Systematic bioinformatics approach to identify high quality mass spectrometry data and functionally annotate proteins and proteomes
  • Mohammad Tawhidul Islam, Abidali Mohamedali, Seong Beom Ahn, Ishmam Nawar, Mark S. Baker, and Shoba Ranganathan
  • Network tools for the analysis of proteomic data
  • David Chisanga, Shivakumar Keerthikumar, Suresh Mathivanan, and Naveen Chilamkurti
  • Shivakumar Keerthikumar
  • Determining the significance of protein network features and attributes using permutation testing
  • Joseph Cursons and Melissa J. Davis
  • Bioinformatics tools and resources for analyzing protein structures
  • Jason J. Paxman and Begoña Heras
  • In silico approach to identify potential inhibitors for Axl-Gas6 signaling
  • Swathik Clarancia Peter, Jayakanthan Mannu, and Premendu P. Mathur
  • Proteomic data storage and sharing
  • Shivakumar Keerthikumar and Suresh Mathivanan
  • Choosing an optimal database for protein identification from tandem mass spectrometry data
  • Dhirendra Kumar, Amit Kumar Yadav, and Debasis Dash
  • Label-based and label-free strategies for protein quantitation
  • Sushma Anand, Monisha Samuel, Ching-Seng Ang, Shivakumar Keerthikumar, and Suresh Mathivanan
Control code
ocn966453268
Dimensions
unknown
Extent
1 online resource (xi, 233 pages)
Form of item
online
Isbn
9781493967407
Lccn
2016959985
Note
SpringerLink
Other control number
10.1007/978-1-4939-6740-7
Other physical details
illustrations (some color)
Sound
unknown sound
Specific material designation
remote
System control number
(OCoLC)966453268
Label
Proteome bioinformatics, edited by Shivakumar Keerthikumar and Suresh Mathivanan
Publication
Copyright
Bibliography note
Includes bibliographical references and index
Color
mixed
Contents
  • TMT one-stop shop : from reliable sample preparation to computational analysis platform
  • Mehdi Mirzaei, Dana Pascovici, Jemma X. Wu, Joel Chick, Yunqi Wu, Brett Cooke, Paul Haynes, and Mark P. Molloy
  • Unassigned MS/MS spectra : who am I?
  • Mohashin Pathan, Monisha Samuel, Shivakumar Keerthikumar, and Suresh Mathivanan
  • Methods to calculate spectrum similarity
  • Şule Yilmaz, Elien Vandermarliere, and Lennart Martens
  • Proteotypic peptides and their applications
  • Shivakumar Keerthikumar and Suresh Mathivanan
  • Statistical evaluation of labeled comparative profiling proteomics experiments using permutation test
  • Hien D. Nguyen, Geoffrey J. McLachlan, and Michelle M. Hill
  • Introduction to proteome bioinformatics
  • De novo peptide sequencing : deep mining of high-resolution mass spectrometry data
  • Mohammad Tawhidul Islam, Abidali Mohamedali, Criselda Santan Fernandes, Mark S. Baker, and Shoba Ranganathan
  • Phylogenetic analysis using protein mass spectrometry
  • Shiyong Ma, Kevin M. Downard, and Jason W.H. Wong
  • Bioinformatics methods to deduce biological interpretation from proteomics data
  • Krishna Patel, Manika Singh, and Harsha Gowda
  • Systematic bioinformatics approach to identify high quality mass spectrometry data and functionally annotate proteins and proteomes
  • Mohammad Tawhidul Islam, Abidali Mohamedali, Seong Beom Ahn, Ishmam Nawar, Mark S. Baker, and Shoba Ranganathan
  • Network tools for the analysis of proteomic data
  • David Chisanga, Shivakumar Keerthikumar, Suresh Mathivanan, and Naveen Chilamkurti
  • Shivakumar Keerthikumar
  • Determining the significance of protein network features and attributes using permutation testing
  • Joseph Cursons and Melissa J. Davis
  • Bioinformatics tools and resources for analyzing protein structures
  • Jason J. Paxman and Begoña Heras
  • In silico approach to identify potential inhibitors for Axl-Gas6 signaling
  • Swathik Clarancia Peter, Jayakanthan Mannu, and Premendu P. Mathur
  • Proteomic data storage and sharing
  • Shivakumar Keerthikumar and Suresh Mathivanan
  • Choosing an optimal database for protein identification from tandem mass spectrometry data
  • Dhirendra Kumar, Amit Kumar Yadav, and Debasis Dash
  • Label-based and label-free strategies for protein quantitation
  • Sushma Anand, Monisha Samuel, Ching-Seng Ang, Shivakumar Keerthikumar, and Suresh Mathivanan
Control code
ocn966453268
Dimensions
unknown
Extent
1 online resource (xi, 233 pages)
Form of item
online
Isbn
9781493967407
Lccn
2016959985
Note
SpringerLink
Other control number
10.1007/978-1-4939-6740-7
Other physical details
illustrations (some color)
Sound
unknown sound
Specific material designation
remote
System control number
(OCoLC)966453268

Library Locations

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      Albany, Auckland, 0632, NZ
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