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Functional Genomics

Overview of attention for book
Cover of 'Functional Genomics'

Table of Contents

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    Book Overview
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    Chapter 1 Prediction of Protein Tertiary Structures Using MUFOLD.
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    Chapter 2 Prediction of protein functions.
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    Chapter 3 Genome-wide screens for expressed hypothetical proteins.
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    Chapter 4 Self-Custom-Made SFP Arrays for Nonmodel Organisms.
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    Chapter 5 Construction and analysis of full-length and normalized cDNA libraries from citrus.
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    Chapter 6 Assembling linear DNA templates for in vitro transcription and translation.
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    Chapter 7 Automated Computational Analysis of Genome-Wide DNA Methylation Profiling Data from HELP-Tagging Assays.
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    Chapter 8 Detection of RNA Editing Events in Human Cells Using High-Throughput Sequencing
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    Chapter 9 Comparative study of differential gene expression in closely related bacterial species by comparative hybridization.
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    Chapter 10 Whole-Genome RT-qPCR MicroRNA Expression Profiling
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    Chapter 11 Using Quantitative Real-Time Reverse Transcriptase Polymerase Chain Reaction to Validate Gene Regulation by PTTG.
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    Chapter 12 FRET-Based Real-Time DNA Microarrays
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    Chapter 13 2-D Gel Electrophoresis: Constructing 2D-Gel Proteome Reference Maps.
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    Chapter 14 The use of antigen microarrays in antibody profiling.
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    Chapter 15 Limited proteolysis in proteomics using protease-immobilized microreactors.
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    Chapter 16 Mass spectrometry for protein quantification in biomarker discovery.
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    Chapter 17 High-throughput microtitre plate-based assay for DNA topoisomerases.
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    Chapter 18 Microscale Thermophoresis as a Sensitive Method to Quantify Protein: Nucleic Acid Interactions in Solution
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    Chapter 19 Bioluminescence resonance energy transfer: an emerging tool for the detection of protein-protein interaction in living cells.
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    Chapter 20 LuMPIS: Luciferase-Based MBP-Pull-Down Protein Interaction Screening System.
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    Chapter 21 Yeast Two-Hybrid Screens: Improvement of Array-Based Screening Results by N- and C-terminally Tagged Fusion Proteins.
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    Chapter 22 Inducible microRNA-Mediated Knockdown of the Endogenous Human Lamin A/C Gene.
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    Chapter 23 Multiple-Gene Silencing Using Antisense RNAs in Escherichia coli.
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    Chapter 24 Functional screen of zebrafish deubiquitylating enzymes by morpholino knockdown and in situ hybridization.
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    Chapter 25 Silencing of gene expression by gymnotic delivery of antisense oligonucleotides.
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    Chapter 26 Polycistronic Expression of Interfering RNAs from RNA Polymerase III Promoters.
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    Chapter 27 Metabolite Analysis of Cannabis sativa L. by NMR Spectroscopy.
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    Chapter 28 Metabolome Analysis of Gram-Positive Bacteria such as Staphylococcus aureus by GC-MS and LC-MS.
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    Chapter 29 Metabolic Fingerprinting Using Comprehensive Two-Dimensional Gas Chromatography - Time-of-Flight Mass Spectrometry.
Attention for Chapter 20: LuMPIS: Luciferase-Based MBP-Pull-Down Protein Interaction Screening System.
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Chapter title
LuMPIS: Luciferase-Based MBP-Pull-Down Protein Interaction Screening System.
Chapter number 20
Book title
Functional Genomics
Published in
Methods in molecular biology, November 2011
DOI 10.1007/978-1-61779-424-7_20
Pubmed ID
22130998
Book ISBNs
978-1-61779-423-0, 978-1-61779-424-7
Authors

Pinto MG, Baiker A, María G. Vizoso Pinto, Armin Baiker, Pinto, María G. Vizoso, Baiker, Armin

Editors

Michael Kaufmann, Claudia Klinger

Abstract

Analyzing the putative interaction partners of an individual protein is one approach to elucidate its function. In the LuMPIS protocol, bait and prey proteins are expressed with N-terminal maltose binding protein (MBP)- and eGFP-luciferase (eGFP-luc) tags, respectively. Positive protein-protein interactions (PPIs) can be detected after pull-down of the MBP-tagged prey protein using amylose beads followed by the bioluminescence detection of the bound eGFP-luc-tagged bait protein. The LuMPIS technology offers the following advantages: the PPIs are detected in the mammalian cell context, the use of two long protein tags (i.e., MBP and eGFP-luc) increases the expression levels of genes whose gene expression levels are known to be frequently impaired, the use of amylose beads for pull-down is much more economic as compared to sepharose beads in combination with monoclonal antibodies and finally, the use of an eGFP-luc-tag enables the qualitative control of transfection efficiencies by fluorescence microscopy prior to starting the assay.

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

Geographical breakdown

Country Count As %
Unknown 5 100%

Demographic breakdown

Readers by professional status Count As %
Professor 1 20%
Student > Ph. D. Student 1 20%
Student > Bachelor 1 20%
Researcher 1 20%
Unknown 1 20%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 2 40%
Agricultural and Biological Sciences 1 20%
Medicine and Dentistry 1 20%
Unknown 1 20%
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 18 March 2022.
All research outputs
#20,531,158
of 25,959,914 outputs
Outputs from Methods in molecular biology
#8,547
of 14,428 outputs
Outputs of similar age
#129,417
of 157,243 outputs
Outputs of similar age from Methods in molecular biology
#35
of 82 outputs
Altmetric has tracked 25,959,914 research outputs across all sources so far. This one is in the 18th percentile – i.e., 18% of other outputs scored the same or lower than it.
So far Altmetric has tracked 14,428 research outputs from this source. They receive a mean Attention Score of 3.3. This one is in the 36th percentile – i.e., 36% 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 157,243 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 16th percentile – i.e., 16% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 82 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 53% of its contemporaries.

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