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T-Cell Differentiation

Overview of attention for book
Cover of 'T-Cell Differentiation'

Table of Contents

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    Book Overview
  2. Altmetric Badge
    Chapter 1 The Vast Universe of T Cell Diversity: Subsets of Memory Cells and Their Differentiation
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    Chapter 2 Basic Aspects of T Helper Cell Differentiation
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    Chapter 3 FACS Analysis of Memory T Lymphocytes
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    Chapter 4 Intravital Microscopy Analysis of Hepatic T Cell Dynamics
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    Chapter 5 Analysis of T Cell Activation by Confocal Microscopy
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    Chapter 6 Phenotypic and Functional Analysis of Antigen-Specific T Cell Exhaustion
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    Chapter 7 pMHC Multiplexing Strategy to Detect High Numbers of T Cell Responses in Parallel
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    Chapter 8 Differentiation of Diverse Progenies of Memory T Cells from Naïve CD8+ T Cell Precursors
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    Chapter 9 Gammaretroviral Production and T Cell Transduction to Genetically Retarget Primary T Cells Against Cancer
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    Chapter 10 Measuring Telomerase Activity in Senescent Human T Cells Upon Genetic Modification
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    Chapter 11 Strategies for T Helper Cell Subset Differentiation from Naïve Precursors
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    Chapter 12 Phenotypic and Functional Analysis of the Suppressive Function of Human Regulatory T Cells
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    Chapter 13 Approaches to Detect microRNA Expression in T Cell Subsets and T Cell Differentiation
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    Chapter 14 T-Cell Differentiation
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    Chapter 15 T-Cell Differentiation
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    Chapter 16 Single-Cell RNA Sequencing of Human T Cells
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    Chapter 17 Extensive Phenotypic Analysis, Transcription Factor Profiling, and Effector Cytokine Production of Human MAIT Cells by Flow Cytometry
  19. Altmetric Badge
    Chapter 18 Developmental and Functional Assays to Study Murine and Human γδ T Cells
Attention for Chapter 14: T-Cell Differentiation
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  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (83rd percentile)
  • High Attention Score compared to outputs of the same age and source (91st percentile)

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Chapter title
T-Cell Differentiation
Chapter number 14
Book title
T-Cell Differentiation
Published in
Methods in molecular biology, January 2017
DOI 10.1007/978-1-4939-6548-9_14
Pubmed ID
Book ISBNs
978-1-4939-6546-5, 978-1-4939-6548-9
Authors

Ranzani, Valeria, Arrigoni, Alberto, Rossetti, Grazisa, Panzeri, Ilaria, Abrignani, Sergio, Bonnal, Raoul J P, Pagani, Massimiliano, Valeria Ranzani, Alberto Arrigoni, Grazisa Rossetti, Ilaria Panzeri, Sergio Abrignani, Raoul J. P. Bonnal, Massimiliano Pagani

Editors

Enrico Lugli

Abstract

Next-generation sequencing approaches, in particular RNA-seq, provide a genome-wide expression profiling allowing the identification of novel and rare transcripts such as long noncoding RNAs (lncRNA). Many RNA-seq studies have now been performed aimed at the characterization of lncRNAs and their possible involvement in cell development and differentiation in different organisms, cell types, and tissues. The adaptive immune system is an extraordinary context for the study of the role of lncRNAs in differentiation. Indeed lncRNAs seem to be key drivers in governing flexibility and plasticity of both CD8(+) and CD4(+) T cell, together with lineage-specific transcription factors and cytokines, acting as fine-tuners of fate choices in T cell differentiation.We describe here a pipeline for the identification of lncRNAs starting from RNA-Seq raw data.

X Demographics

X Demographics

The data shown below were collected from the profiles of 5 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 24 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 24 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 7 29%
Student > Master 4 17%
Student > Bachelor 3 13%
Student > Ph. D. Student 3 13%
Unspecified 2 8%
Other 3 13%
Unknown 2 8%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 10 42%
Agricultural and Biological Sciences 4 17%
Unspecified 2 8%
Neuroscience 2 8%
Medicine and Dentistry 2 8%
Other 1 4%
Unknown 3 13%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 10. 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 11 January 2018.
All research outputs
#3,273,432
of 22,896,955 outputs
Outputs from Methods in molecular biology
#797
of 13,135 outputs
Outputs of similar age
#69,078
of 420,429 outputs
Outputs of similar age from Methods in molecular biology
#96
of 1,074 outputs
Altmetric has tracked 22,896,955 research outputs across all sources so far. Compared to these this one has done well and is in the 85th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 13,135 research outputs from this source. They receive a mean Attention Score of 3.4. This one has done particularly well, scoring higher than 93% 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 420,429 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 83% of its contemporaries.
We're also able to compare this research output to 1,074 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 91% of its contemporaries.