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Protein Bioinformatics

Overview of attention for book
Cover of 'Protein Bioinformatics'

Table of Contents

  1. Altmetric Badge
    Book Overview
  2. Altmetric Badge
    Chapter 1 Protein Bioinformatics Databases and Resources
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    Chapter 2 UniProt Protein Knowledgebase
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    Chapter 3 Tutorial on Protein Ontology Resources
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    Chapter 4 CATH-Gene3D: Generation of the Resource and Its Use in Obtaining Structural and Functional Annotations for Protein Sequences
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    Chapter 5 Structure-Based Virtual Screening
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    Chapter 6 Bioinformatics Analysis of Protein Phosphorylation in Plant Systems Biology Using P3DB
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    Chapter 7 Navigating the Glycome Space and Connecting the Glycoproteome
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    Chapter 8 Impact of Nonsynonymous Single-Nucleotide Variations on Post-Translational Modification Sites in Human Proteins
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    Chapter 9 Analysis of Cysteine Redox Post-Translational Modifications in Cell Biology and Drug Pharmacology
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    Chapter 10 Analysis of Protein Phosphorylation and Its Functional Impact on Protein–Protein Interactions via Text Mining of the Scientific Literature
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    Chapter 11 Functional Interaction Network Construction and Analysis for Disease Discovery
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    Chapter 12 Prediction of Protein Interactions by Structural Matching: Prediction of PPI Networks and the Effects of Mutations on PPIs that Combines Sequence and Structural Information
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    Chapter 13 NDEx: A Community Resource for Sharing and Publishing of Biological Networks
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    Chapter 14 Bioinformatics Analysis of Functional Associations of PTMs
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    Chapter 15 Bioinformatics Analysis of PTM-Modified Protein Interaction Networks and Complexes
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    Chapter 16 iPTMnet: Integrative Bioinformatics for Studying PTM Networks
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    Chapter 17 Protein Identification from Tandem Mass Spectra by Database Searching
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    Chapter 18 Bioinformatics Analysis of Top-Down Mass Spectrometry Data with ProSight Lite
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    Chapter 19 Mapping Biological Networks from Quantitative Data-Independent Acquisition Mass Spectrometry: Data to Knowledge Pipelines
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    Chapter 20 Annotation of Alternatively Spliced Proteins and Transcripts with Protein-Folding Algorithms and Isoform-Level Functional Networks
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    Chapter 21 Computational and Statistical Methods for High-Throughput Mass Spectrometry-Based PTM Analysis
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    Chapter 22 Cross-Species PTM Mapping from Phosphoproteomic Data
Attention for Chapter 7: Navigating the Glycome Space and Connecting the Glycoproteome
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Chapter title
Navigating the Glycome Space and Connecting the Glycoproteome
Chapter number 7
Book title
Protein Bioinformatics
Published in
Methods in molecular biology, February 2017
DOI 10.1007/978-1-4939-6783-4_7
Pubmed ID
28150237
Book ISBNs
978-1-4939-6781-0, 978-1-4939-6783-4
Authors

Campbell, Matthew P., Peterson, Robyn A., Gasteiger, Elisabeth, Mariethoz, Julien, Lisacek, Frederique, Packer, Nicolle H., Matthew P. Campbell, Robyn A. Peterson, Elisabeth Gasteiger, Julien Mariethoz, Frederique Lisacek, Nicolle H. Packer

Editors

Cathy H. Wu, Cecilia N. Arighi, Karen E. Ross

Abstract

UniCarbKB ( http://unicarbkb.org ) is a comprehensive resource for mammalian glycoprotein and annotation data. In particular, the database provides information on the oligosaccharides characterized from a glycoprotein at either the global or site-specific level. This evidence is accumulated from a peer-reviewed and manually curated collection of information on oligosaccharides derived from membrane and secreted glycoproteins purified from biological fluids and/or tissues. This information is further supplemented with experimental method descriptions that summarize important sample preparation and analytical strategies. A new release of UniCarbKB is published every three months, each includes a collection of curated data and improvements to database functionality. In this Chapter, we outline the objectives of UniCarbKB, and describe a selection of step-by-step workflows for navigating the information available. We also provide a short description of web services available and future plans for improving data access. The information presented in this Chapter supplements content available in our knowledgebase including regular updates on interface improvements, new features, and revisions to the database content ( http://confluence.unicarbkb.org ).

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X Demographics

X Demographics

The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
 Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 8 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 8 100%

Demographic breakdown

Readers by professional status Count As %
Unspecified 1 13%
Other 1 13%
Student > Bachelor 1 13%
Professor 1 13%
Student > Ph. D. Student 1 13%
Other 1 13%
Unknown 2 25%
Readers by discipline Count As %
Agricultural and Biological Sciences 2 25%
Biochemistry, Genetics and Molecular Biology 1 13%
Unspecified 1 13%
Computer Science 1 13%
Medicine and Dentistry 1 13%
Other 0 0%
Unknown 2 25%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 06 February 2017.
All research outputs
#17,873,766
of 22,950,943 outputs
Outputs from Methods in molecular biology
#7,259
of 13,138 outputs
Outputs of similar age
#293,520
of 420,304 outputs
Outputs of similar age from Methods in molecular biology
#681
of 1,176 outputs
Altmetric has tracked 22,950,943 research outputs across all sources so far. This one is in the 19th percentile – i.e., 19% of other outputs scored the same or lower than it.
So far Altmetric has tracked 13,138 research outputs from this source. They receive a mean Attention Score of 3.4. This one is in the 39th percentile – i.e., 39% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 420,304 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 26th percentile – i.e., 26% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 1,176 others from the same source and published within six weeks on either side of this one. This one is in the 36th percentile – i.e., 36% of its contemporaries scored the same or lower than it.

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