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The Surfaceome

Overview of attention for book
Cover of 'The Surfaceome'

Table of Contents

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    Book Overview
  2. Altmetric Badge
    Chapter 1 Surfaceome Analysis Protocol for the Identification of Novel Bordetella pertussis Antigens
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    Chapter 2 “Shaving” Live Bacterial Cells with Proteases for Proteomic Analysis of Surface Proteins
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    Chapter 3 Methods for Mapping the Extracellular and Membrane Proteome in the Avian Embryo, and Identification of Putative Vascular Targets or Endothelial Genes
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    Chapter 4 Mass Spectrometry-Based Identification of Extracellular Domains of Cell Surface N-Glycoproteins: Defining the Accessible Surfaceome for Immunophenotyping Stem Cells and Their Derivatives
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    Chapter 5 Application of Higher Density Iron Oxide Nanoparticle Pellicles to Enrich the Plasma Membrane and Its Proteome from Cells in Suspension
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    Chapter 6 Proteomic Profiling of Secreted Proteins, Exosomes, and Microvesicles in Cell Culture Conditioned Media
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    Chapter 7 Cloning, Expression, and Purification of the Glycosylated Transmembrane Protein, Cation-Dependent Mannose 6-Phosphate Receptor, from Sf9 Cells Using the Baculovirus System
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    Chapter 8 Bispecific Antibody Armed T Cells to Target Cancer Cells
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    Chapter 9 Immunophenotyping of Live Human Pluripotent Stem Cells by Flow Cytometry
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    Chapter 10 Detecting Cell Surface Expression of the G Protein-Coupled Receptor CXCR4
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    Chapter 11 NaV Channels: Assaying Biosynthesis, Trafficking, Function
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    Chapter 12 High-Content Electrophysiological Analysis of Human Pluripotent Stem Cell-Derived Cardiomyocytes (hPSC-CMs)
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    Chapter 13 Methods for Evaluation of Vascular Endothelial Cell Function with Transient Receptor Potential (TRP) Channel Drugs
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    Chapter 14 Methods to Study the Signal Transduction of the Surface Receptor Tyrosine Kinase TrkB in Neurons
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    Chapter 15 Polarized Human Retinal Pigment Epithelium Exhibits Distinct Surface Proteome on Apical and Basal Plasma Membranes
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    Chapter 16 Extracellular Matrix Molecule-Based Capture of Mesenchymal Stromal Cells Under Flow
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    Chapter 17 Generation of Induced Pluripotent Stem Cells from Patients with COL3A1 Mutations and Differentiation to Smooth Muscle Cells for ECM-Surfaceome Analyses
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    Chapter 18 Fabrication and Mechanical Properties Measurements of 3D Microtissues for the Study of Cell–Matrix Interactions
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    Chapter 19 Discovery of Surface Target Proteins Linking Drugs, Molecular Markers, Gene Regulation, Protein Networks, and Disease by Using a Web-Based Platform Targets-search
Attention for Chapter 19: Discovery of Surface Target Proteins Linking Drugs, Molecular Markers, Gene Regulation, Protein Networks, and Disease by Using a Web-Based Platform Targets-search
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Chapter title
Discovery of Surface Target Proteins Linking Drugs, Molecular Markers, Gene Regulation, Protein Networks, and Disease by Using a Web-Based Platform Targets-search
Chapter number 19
Book title
The Surfaceome
Published in
Methods in molecular biology, January 2018
DOI 10.1007/978-1-4939-7553-2_19
Pubmed ID
Book ISBNs
978-1-4939-7551-8, 978-1-4939-7553-2
Authors

Bin Yan, Panwen Wang, Junwen Wang, Kenneth R. Boheler, Yan, Bin, Wang, Panwen, Wang, Junwen, Boheler, Kenneth R.

Abstract

Integration and analysis of high content omics data have been critical to the investigation of molecule interactions (e.g., DNA-protein, protein-protein, chemical-protein) in biological systems. Human proteomic strategies that provide enriched information on cell surface proteins can be utilized for repurposing of drug targets and discovery of disease biomarkers. Although several published resources have proved useful to the analysis of these interactions, our newly developed web-based platform Targets-search has the capability of integrating multiple types of omics data to unravel their association with diverse molecule interactions and disease. Here, we describe how to use Targets-search, for the integrated and systemic exploitation of surface proteins to identify potential drug targets, which can further be used to analyze gene regulation, protein networks, and possible biomarkers for diseases and cancers. To illustrate this process, we have taken data from Ewing's sarcoma to identify surface proteins differentially expressed in Ewing's sarcoma cells. These surface proteins were then analyzed to determine which ones were known drug targets. The information suggested putative targets for drug repurposing and subsequent analyses illustrated their regulation by the transcription factor EWSR1.

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 7 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 7 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 2 29%
Professor 1 14%
Unspecified 1 14%
Professor > Associate Professor 1 14%
Student > Ph. D. Student 1 14%
Other 0 0%
Unknown 1 14%
Readers by discipline Count As %
Medicine and Dentistry 3 43%
Unspecified 1 14%
Chemistry 1 14%
Environmental Science 1 14%
Unknown 1 14%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 15 August 2018.
All research outputs
#14,961,684
of 23,012,811 outputs
Outputs from Methods in molecular biology
#4,729
of 13,156 outputs
Outputs of similar age
#255,728
of 442,345 outputs
Outputs of similar age from Methods in molecular biology
#508
of 1,498 outputs
Altmetric has tracked 23,012,811 research outputs across all sources so far. This one is in the 32nd percentile – i.e., 32% of other outputs scored the same or lower than it.
So far Altmetric has tracked 13,156 research outputs from this source. They receive a mean Attention Score of 3.4. This one has gotten more attention than average, scoring higher than 59% of its peers.
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 442,345 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 39th percentile – i.e., 39% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 1,498 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 60% of its contemporaries.