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HLA Typing

Overview of attention for book
Cover of 'HLA Typing'

Table of Contents

  1. Altmetric Badge
    Book Overview
  2. Altmetric Badge
    Chapter 1 The Past, Present, and Future of HLA Typing in Transplantation
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    Chapter 2 Role of Human Leukocyte Antigens (HLA) in Autoimmune Diseases
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    Chapter 3 The IPD Databases: Cataloguing and Understanding Allele Variants
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    Chapter 4 Allele Frequency Net Database
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    Chapter 5 High-Resolution HLA-Typing by Next-Generation Sequencing of Randomly Fragmented Target DNA
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    Chapter 6 High-Throughput Contiguous Full-Length Next-Generation Sequencing of HLA Class I and II Genes from 96 Donors in a Single MiSeq Run
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    Chapter 7 Application of High-Throughput Next-Generation Sequencing for HLA Typing on Buccal Extracted DNA
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    Chapter 8 Super High Resolution for Single Molecule-Sequence-Based Typing of Classical HLA Loci Using Ion Torrent PGM
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    Chapter 9 High-Resolution Full-Length HLA Typing Method Using Third Generation (Pac-Bio SMRT) Sequencing Technology
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    Chapter 10 Full-Length HLA Class I Genotyping with the MinION Nanopore Sequencer
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    Chapter 11 Imputation-Based HLA Typing with SNPs in GWAS Studies
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    Chapter 12 In Silico Typing of Classical and Non-classical HLA Alleles from Standard RNA-Seq Reads
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    Chapter 13 PHLAT: Inference of High-Resolution HLA Types from RNA and Whole Exome Sequencing
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    Chapter 14 Using Exome and Amplicon-Based Sequencing Data for High-Resolution HLA Typing with ATHLATES
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    Chapter 15 HLA Typing from Short-Read Sequencing Data with OptiType
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    Chapter 16 Comprehensive HLA Typing from a Current Allele Database Using Next-Generation Sequencing Data
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    Chapter 17 Accurate Assembly and Typing of HLA using a Graph-Guided Assembler Kourami
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    Chapter 18 AmpliSAS and AmpliHLA: Web Server Tools for MHC Typing of Non-Model Species and Human Using NGS Data
  20. Altmetric Badge
    Chapter 19 HLA Haplotype Frequency Estimation from Real-Life Data with the Hapl-o-Mat Software
Attention for Chapter 1: The Past, Present, and Future of HLA Typing in Transplantation
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Chapter title
The Past, Present, and Future of HLA Typing in Transplantation
Chapter number 1
Book title
HLA Typing
Published in
Methods in molecular biology, January 2018
DOI 10.1007/978-1-4939-8546-3_1
Pubmed ID
29858798
Book ISBNs
978-1-4939-8545-6, 978-1-4939-8546-3
Authors

Claire H. Edgerly, Eric T. Weimer, Edgerly, Claire H., Weimer, Eric T.

Abstract

The HLA region is the most polymorphic genes in the human genome and is associated with an increasing number of disease states. Historically, HLA typing methodology has been governed by phenotypic determination. This practice has evolved into the use of molecular methods such as real-time PCR, sequence-specific oligonucleotides, and sequencing-based methods. Numerous studies have identified HLA matching as a key determinate to improve patient outcomes from transplantation. Solid-organ transplants focus on HLA-DRB1 in renal organ allocation while hematopoietic cell transplants focus on HLA-A, -B, -C, -DRB1 matching. The role of HLA typing in the future will be driven by HLA expression, understanding of HLA haplotypes, and rapid HLA typing.

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X Demographics

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

Geographical breakdown

Country Count As %
Unknown 70 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 11 16%
Student > Bachelor 8 11%
Researcher 7 10%
Other 6 9%
Student > Doctoral Student 5 7%
Other 8 11%
Unknown 25 36%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 14 20%
Medicine and Dentistry 11 16%
Immunology and Microbiology 8 11%
Agricultural and Biological Sciences 5 7%
Computer Science 2 3%
Other 4 6%
Unknown 26 37%
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 25 July 2018.
All research outputs
#17,976,833
of 23,085,832 outputs
Outputs from Methods in molecular biology
#7,313
of 13,205 outputs
Outputs of similar age
#310,660
of 442,605 outputs
Outputs of similar age from Methods in molecular biology
#869
of 1,499 outputs
Altmetric has tracked 23,085,832 research outputs across all sources so far. This one is in the 19th percentile – i.e., 19% of other outputs scored the same or lower than it.
So far Altmetric has tracked 13,205 research outputs from this source. They receive a mean Attention Score of 3.4. This one is in the 39th percentile – i.e., 39% 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 442,605 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 25th percentile – i.e., 25% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 1,499 others from the same source and published within six weeks on either side of this one. This one is in the 36th percentile – i.e., 36% of its contemporaries scored the same or lower than it.

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