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Olfactory Receptors

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Cover of 'Olfactory Receptors'

Table of Contents

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    Book Overview
  2. Altmetric Badge
    Chapter 1 Databases in SenseLab for the Genomics, Proteomics, and Function of Olfactory Receptors
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    Chapter 2 HORDE: Comprehensive Resource for Olfactory Receptor Genomics.
  4. Altmetric Badge
    Chapter 3 Identification of Olfactory Receptor Genes from Mammalian Genome Sequences
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    Chapter 4 Molecular Modelling of Odorant/Olfactory Receptor Complexes
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    Chapter 5 The Electrical Properties of Olfactory Receptors in the Development of Biological Smell Sensors
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    Chapter 6 A Hit Map-Based Statistical Method to Predict Best Ligands for Orphan Olfactory Receptors: Natural Key Odorants Versus “Lock Picks”
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    Chapter 7 A Robust, Rapid, and Simple Method of Producing Olfactory Receptors Using Commercial E . coli Cell-Free Systems
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    Chapter 8 Human Olfactory Receptors: Recombinant Expression in the Baculovirus/Sf9 Insect Cell System, Functional Characterization, and Odorant Identification
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    Chapter 9 Single Cell RT-PCR Identification of Odorant Receptors Expressed by Olfactory Neurons
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    Chapter 10 Next-generation sequencing of the human olfactory receptors.
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    Chapter 11 Deciphering Activation of Olfactory Receptors Using Heterologous Expression in Saccharomyces cerevisiae and Bioluminescence Resonance Energy Transfer
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    Chapter 12 Olfactory receptors in human airway epithelia.
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    Chapter 13 Functional characterization of insect olfactory receptor neurons through in vivo approaches.
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    Chapter 14 Functional Assay of Mammalian and Insect Olfactory Receptors Using Xenopus Oocytes
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    Chapter 15 Pharmacology of Mammalian olfactory receptors.
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    Chapter 16 Visualizing olfactory receptor expression and localization in Drosophila.
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    Chapter 17 Deorphanization of Human Olfactory Receptors by Luciferase and Ca-Imaging Methods
  19. Altmetric Badge
    Chapter 18 Evolution of Olfactory Receptors
Attention for Chapter 6: A Hit Map-Based Statistical Method to Predict Best Ligands for Orphan Olfactory Receptors: Natural Key Odorants Versus “Lock Picks”
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Chapter title
A Hit Map-Based Statistical Method to Predict Best Ligands for Orphan Olfactory Receptors: Natural Key Odorants Versus “Lock Picks”
Chapter number 6
Book title
Olfactory Receptors
Published in
Methods in molecular biology, January 2013
DOI 10.1007/978-1-62703-377-0_6
Pubmed ID
Book ISBNs
978-1-62703-376-3, 978-1-62703-377-0
Authors

Dietmar Krautwurst, Matthias Kotthoff, Krautwurst, Dietmar, Kotthoff, Matthias

Abstract

Smell is a multidimensional chemical sense. It creates a perception of our odorous environment by integrating the information of a plethora of volatile chemicals with other sensory inputs, emotions and memories. We are almost always exposed to odorant mixtures, not just single chemicals. Olfactory processing of complex odorant mixtures, such as coffee or wine, first is decoded at the site of perception by the hundreds of different olfactory receptor types, each residing in the cilia of their olfactory sensory neurons in the nose. Often, only a few odorants from many are essential to determine complex olfactory perception. But merely using the chemical structure of odorants is insufficient to identify and predict characteristic odor qualities and low odor thresholds. An understanding of odorant coding critically depends on knowledge about the interaction of key odorants of biologically relevant odor bouquets with their best cognate receptors. Here, we describe a hit map-based method of correlating the information content of all bioassay-tested odorants with their cognate odorant-receptor frequency in four phylogenetic subsets of human olfactory/chemosensory receptors.

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

Geographical breakdown

Country Count As %
Israel 1 6%
France 1 6%
Unknown 16 89%

Demographic breakdown

Readers by professional status Count As %
Researcher 4 22%
Other 2 11%
Student > Master 2 11%
Professor 1 6%
Lecturer > Senior Lecturer 1 6%
Other 2 11%
Unknown 6 33%
Readers by discipline Count As %
Agricultural and Biological Sciences 4 22%
Environmental Science 1 6%
Business, Management and Accounting 1 6%
Biochemistry, Genetics and Molecular Biology 1 6%
Computer Science 1 6%
Other 4 22%
Unknown 6 33%
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 24 April 2013.
All research outputs
#18,337,420
of 22,708,120 outputs
Outputs from Methods in molecular biology
#7,850
of 13,078 outputs
Outputs of similar age
#218,008
of 280,717 outputs
Outputs of similar age from Methods in molecular biology
#220
of 340 outputs
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So far Altmetric has tracked 13,078 research outputs from this source. They receive a mean Attention Score of 3.3. This one is in the 24th percentile – i.e., 24% of its peers scored the same or lower than it.
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We're also able to compare this research output to 340 others from the same source and published within six weeks on either side of this one. This one is in the 12th percentile – i.e., 12% of its contemporaries scored the same or lower than it.