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Advancements of Mass Spectrometry in Biomedical Research

Overview of attention for book
Cover of 'Advancements of Mass Spectrometry in Biomedical Research'

Table of Contents

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    Book Overview
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    Chapter 1 Mass spectrometry for proteomics-based investigation.
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    Chapter 2 MALDI Profiling and Applications in Medicine
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    Chapter 3 Simplifying the proteome: analytical strategies for improving peak capacity.
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    Chapter 4 Quantitative shotgun proteomics with data-independent acquisition and traveling wave ion mobility spectrometry: a versatile tool in the life sciences.
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    Chapter 5 Stable Isotope Labeling by Amino Acids in Cell Culture (SILAC) for Quantitative Proteomics.
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    Chapter 6 Utility of computational structural biology in mass spectrometry.
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    Chapter 7 Affinity-Mass Spectrometry Approaches for Elucidating Structures and Interactions of Protein–Ligand Complexes
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    Chapter 8 Neurological Analyses: Focus on Gangliosides and Mass Spectrometry
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    Chapter 9 Mass Spectrometric Analysis of Post-translational Modifications (PTMs) and Protein-Protein Interactions (PPIs).
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    Chapter 10 Applications for Mass Spectrometry in the Study of Ion Channel Structure and Function
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    Chapter 11 A Mass Spectrometry View of Stable and Transient Protein Interactions
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    Chapter 12 Mass Spectrometry-Based Tissue Imaging of Small Molecules
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    Chapter 13 Redox proteomics: from bench to bedside.
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    Chapter 14 Analysis of Fluorinated Proteins by Mass Spectrometry
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    Chapter 15 Mass spectrometry for proteomics-based investigation using the zebrafish vertebrate model system.
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    Chapter 16 Mass Spectrometry-Based Biomarkers in Drug Development
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    Chapter 17 Detection of Biomedically Relevant Stilbenes from Wines by Mass Spectrometry
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    Chapter 18 Mass Spectrometric DNA Adduct Quantification by Multiple Reaction Monitoring and Its Future Use for the Molecular Epidemiology of Cancer
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    Chapter 19 Using Breast Milk to Assess Breast Cancer Risk: The Role of Mass Spectrometry-Based Proteomics
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    Chapter 20 Cancer secretomes and their place in supplementing other hallmarks of cancer.
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    Chapter 21 Thiostrepton, a natural compound that triggers heat shock response and apoptosis in human cancer cells: a proteomics investigation.
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    Chapter 22 Using Proteomics to Unravel the Mysterious Steps of the HBV-Life-Cycle.
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    Chapter 23 Oxidative Stress and Antibiotic Resistance in Bacterial Pathogens: State of the Art, Methodologies, and Future Trends
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    Chapter 24 Proteomic approaches to dissect neuronal signaling pathways.
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    Chapter 25 Investigating a Novel Protein Using Mass Spectrometry: The Example of Tumor Differentiation Factor (TDF).
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    Chapter 26 Mass spectrometry for the study of autism and neurodevelopmental disorders.
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    Chapter 27 Biomarkers in major depressive disorder: the role of mass spectrometry.
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    Chapter 28 Application of Mass Spectrometry to Characterize Localization and Efficacy of Nanoceria In Vivo
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    Chapter 29 Bottlenecks in proteomics.
Attention for Chapter 26: Mass spectrometry for the study of autism and neurodevelopmental disorders.
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Chapter title
Mass spectrometry for the study of autism and neurodevelopmental disorders.
Chapter number 26
Book title
Advancements of Mass Spectrometry in Biomedical Research
Published in
Advances in experimental medicine and biology, January 2014
DOI 10.1007/978-3-319-06068-2_26
Pubmed ID
Book ISBNs
978-3-31-906067-5, 978-3-31-906068-2
Authors

Armand G Ngounou Wetie, Robert M Dekroon, Mihaela Mocanu, Jeanne P Ryan, Costel C Darie, Alisa G Woods, Armand G. Ngounou Wetie, Robert M. Dekroon, Jeanne P. Ryan, Costel C. Darie, Alisa G. Woods, Wetie, Armand G. Ngounou, Dekroon, Robert M., Mocanu, Mihaela, Ryan, Jeanne P., Darie, Costel C., Woods, Alisa G.

Abstract

Mass spectrometry (MS) has been increasingly used to study central nervous system disorders, including autism spectrum disorders (ASDs). The first studies of ASD using MS focused on the identification of external toxins, but current research is more directed at understanding endogenous protein changes that occur in ASD (ASD proteomics). This chapter focuses on how MS has been used to study ASDs, with particular focus on proteomic analysis. Other neurodevelopmental disorders have been investigated using this technique, including genetic syndromes associated with autism such as fragile X syndrome and Smith-Lemli-Opitz syndrome.

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X Demographics

The data shown below were collected from the profile of 1 X user 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 17 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 17 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 3 18%
Professor > Associate Professor 2 12%
Student > Bachelor 1 6%
Professor 1 6%
Student > Ph. D. Student 1 6%
Other 3 18%
Unknown 6 35%
Readers by discipline Count As %
Medicine and Dentistry 3 18%
Pharmacology, Toxicology and Pharmaceutical Science 2 12%
Social Sciences 2 12%
Agricultural and Biological Sciences 1 6%
Biochemistry, Genetics and Molecular Biology 1 6%
Other 1 6%
Unknown 7 41%
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 02 October 2014.
All research outputs
#16,237,186
of 25,654,806 outputs
Outputs from Advances in experimental medicine and biology
#2,301
of 5,269 outputs
Outputs of similar age
#188,366
of 320,719 outputs
Outputs of similar age from Advances in experimental medicine and biology
#71
of 140 outputs
Altmetric has tracked 25,654,806 research outputs across all sources so far. This one is in the 34th percentile – i.e., 34% of other outputs scored the same or lower than it.
So far Altmetric has tracked 5,269 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 7.0. This one has gotten more attention than average, scoring higher than 53% 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 320,719 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 140 others from the same source and published within six weeks on either side of this one. This one is in the 48th percentile – i.e., 48% of its contemporaries scored the same or lower than it.