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The Wilms' Tumor (WT1) Gene

Overview of attention for book
Cover of 'The Wilms' Tumor (WT1) Gene'

Table of Contents

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    Book Overview
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    Chapter 1 WT1 Mutation in Childhood Cancer.
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    Chapter 2 Clinical Aspects of WT1 and the Kidney.
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    Chapter 3 The Role of WT1 in Embryonic Development and Normal Organ Homeostasis.
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    Chapter 4 Tools and Techniques for Wt1-Based Lineage Tracing.
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    Chapter 5 Biological Systems and Methods for Studying WT1 in the Epicardium.
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    Chapter 6 Isolation and Colony Formation of Murine Bone and Bone Marrow Cells.
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    Chapter 7 Isolation and Fluorescence-Activated Cell Sorting of Murine WT1-Expressing Adipocyte Precursor Cells.
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    Chapter 8 The Wilms' Tumor (WT1) Gene
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    Chapter 9 Multiphoton Microscopy for Visualizing Lipids in Tissue.
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    Chapter 10 Function and Regulation of the Wilms' Tumor Suppressor 1 (WT1) Gene in Fish.
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    Chapter 11 Immunofluorescence Staining of Wt1 on Sections of Zebrafish Embryos and Larvae.
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    Chapter 12 Fluorescence-Activated Cell Sorting (FACS) Protocol for Podocyte Isolation in Adult Zebrafish.
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    Chapter 13 In Vitro Transcription to Study WT1 Function.
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    Chapter 14 Measuring Equilibrium Binding Constants for the WT1-DNA Interaction Using a Filter Binding Assay.
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    Chapter 15 The Wilms' Tumor (WT1) Gene
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    Chapter 16 The Wilms' Tumor (WT1) Gene
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    Chapter 17 Methods to Identify and Validate WT1-RNA Interaction.
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    Chapter 18 The Wilms' Tumor (WT1) Gene
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    Chapter 19 The Wilms' Tumor (WT1) Gene
Attention for Chapter 18: The Wilms' Tumor (WT1) Gene
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Chapter title
The Wilms' Tumor (WT1) Gene
Chapter number 18
Book title
The Wilms' Tumor (WT1) Gene
Published in
Methods in molecular biology, January 2016
DOI 10.1007/978-1-4939-4023-3_18
Pubmed ID
Book ISBNs
978-1-4939-4021-9, 978-1-4939-4023-3
Authors

Aitken, Stuart, Bharathavikru, Ruthrothaselvi, Stuart Aitken, Ruthrothaselvi Bharathavikru

Editors

Nicholas Hastie

Abstract

Differential gene expression analysis has been conventionally performed by microarray techniques; however with the recent advent of next-generation sequencing (NGS) approaches, it has become easier to analyze the coding as well as the noncoding components. Additionally, NGS data analysis also provides information regarding the expression changes of specific isoforms. There are several bioinformatics tools available to analyze NGS data but with different parameters. This chapter provides a comparative insight into these tools by utilizing NGS datasets available from Wt1 knockout and embryonic stem cell line model.

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Mendeley readers

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The data shown below were compiled from readership statistics for 2 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 2 100%

Demographic breakdown

Readers by professional status Count As %
Unspecified 1 50%
Researcher 1 50%
Readers by discipline Count As %
Unspecified 1 50%
Unknown 1 50%
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 16 July 2016.
All research outputs
#20,335,770
of 22,880,691 outputs
Outputs from Methods in molecular biology
#9,918
of 13,132 outputs
Outputs of similar age
#330,756
of 393,712 outputs
Outputs of similar age from Methods in molecular biology
#1,054
of 1,471 outputs
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So far Altmetric has tracked 13,132 research outputs from this source. They receive a mean Attention Score of 3.4. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
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We're also able to compare this research output to 1,471 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.