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Patient-Derived Xenografts

Overview of attention for book
Cover of 'Patient-Derived Xenografts'

Table of Contents

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    Book Overview
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    Chapter 1 Patient-Derived Xenografts: Historical Evolution, Immunocompromised Host Models, and Translational Significance
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    Chapter 2 Patient-Derived Xenograft Models in Cancer Research: Methodology, Applications, and Future Prospects
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    Chapter 3 Patient-Derived Xenografts: A Valuable Preclinical Model for Drug Development and Biomarker Discovery
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    Chapter 4 Patient-Derived Xenograft Models for Leukemias
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    Chapter 5 Patient-Derived Orthotopic Xenograft Models for High-Grade Pediatric Brain Cancers
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    Chapter 6 Generation of Orthotopic and Subcutaneous Patient-Derived Xenograft Models from Diverse Clinical Tissue Samples of Pediatric Extracranial Solid Tumors
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    Chapter 7 Development of Orthotopic Patient-Derived Xenograft Models of Pediatric Intracranial Tumors
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    Chapter 8 A Humanized Patient-Derived Xenograft Model for Pancreatic Cancer
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    Chapter 9 Development and Expansion of Patient-Derived Xenografts for Endometrial Cancer
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    Chapter 10 A Multiplexed Approach to Assess Small Cell Lung Cancer Subtype Heterogeneity in Primary and Patient-Derived Tumor Samples
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    Chapter 11 Generation of Metastatic Cholangiocarcinoma Patient-Derived Xenograft Models
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    Chapter 12 Patient-Derived Xenograft Models for Translational Prostate Cancer Research and Drug Development
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    Chapter 13 Patient-Derived Xenograft Models for Ovarian Cancer
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    Chapter 14 Orthotopic MC-38 Allograft as a Robust Preclinical Model of Colorectal Carcinoma
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    Chapter 15 Assessing Protein Expression in Patient-Derived Xenografts Using Western Blotting
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    Chapter 16 Analysis of Protein Interactions in Patient-Derived Xenografts Using Immunoprecipitation
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    Chapter 17 A Semiautomated Proteomics and Phosphoproteomics Protocol for the Identification of Novel Therapeutic Targets and Predictive Biomarkers in In Vivo Xenograft Models of Pediatric Cancers
Overall attention for this book and its chapters
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (90th percentile)
  • High Attention Score compared to outputs of the same age and source (99th percentile)

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Title
Patient-Derived Xenografts
Published by
Methods in molecular biology, January 2024
DOI 10.1007/978-1-0716-3858-3
ISBNs
978-1-07-163857-6, 978-1-07-163858-3
Editors

Saad, Mohamed I.

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Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 17. 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 May 2024.
All research outputs
#2,207,297
of 25,884,216 outputs
Outputs from Methods in molecular biology
#313
of 14,393 outputs
Outputs of similar age
#33,718
of 360,756 outputs
Outputs of similar age from Methods in molecular biology
#3
of 330 outputs
Altmetric has tracked 25,884,216 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 91st percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 14,393 research outputs from this source. They receive a mean Attention Score of 3.5. This one has done particularly well, scoring higher than 97% 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 360,756 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 90% of its contemporaries.
We're also able to compare this research output to 330 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 99% of its contemporaries.