↓ Skip to main content

Cancer Gene Profiling

Overview of attention for book
Attention for Chapter 1: Factors Affecting the Use of Human Tissues in Biomedical Research: Implications in the Design and Operation of a Biorepository.
Altmetric Badge

Mentioned by

twitter
1 tweeter

Citations

dimensions_citation
2 Dimensions

Readers on

mendeley
11 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Chapter title
Factors Affecting the Use of Human Tissues in Biomedical Research: Implications in the Design and Operation of a Biorepository.
Chapter number 1
Book title
Cancer Gene Profiling
Published in
Methods in molecular biology, January 2016
DOI 10.1007/978-1-4939-3204-7_1
Pubmed ID
Book ISBNs
978-1-4939-3203-0, 978-1-4939-3204-7
Authors

Atherton, Daniel S, Sexton, Katherine C, Otali, Dennis, Bell, Walter C, Grizzle, William E, Daniel S. Atherton, Katherine C. Sexton, Dennis Otali, Walter C. Bell, William E. Grizzle M.D., Ph.D., William E. Grizzle

Editors

Robert Grützmann, Christian Pilarsky

Abstract

The availability of high-quality human tissues is necessary to advance medical research. Although there are inherent and induced limitations on the use of human tissues in research, biorepositories play critical roles in minimizing the effects of such limitations. Specifically, the optimal utilization of tissues in research requires tissues to be diagnosed accurately, and the actual specimens provided to investigators must be carefully described (i.e., there must be quality control of each aliquot of the tissue provided for research, including a description of any damage to tissues). Tissues also should be collected, processed, stored, and distributed (i.e., handled) uniformly under a rigorous quality management system (QMS). Frequently, tissues are distributed to investigators by tissue banks which have collected, processed, and stored them by standard operating procedures (SOPs). Alternatively, tissues for research may be handled via SOPs that are modified to the specific requirements of investigators (i.e., using a prospective biorepository model). The primary goal of any type of biorepository should be to ensure its specimens are of high quality and are utilized appropriately in research; however, approaches may vary based on the tissues available and requested. For example, extraction of specific molecules (e.g., microRNA) to study molecular characteristics of a tissue may require less clinical annotation than tissues that are utilized to identify how the molecular expression might be used to clarify a clinical outcome of a disease or the response to a specific therapy. This review focuses on the limitations of the use of tissues in research and how the design and operations of a tissue biorepository can minimize some of these limitations.

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 11 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 11 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 3 27%
Professor 2 18%
Researcher 2 18%
Student > Ph. D. Student 1 9%
Professor > Associate Professor 1 9%
Other 0 0%
Unknown 2 18%
Readers by discipline Count As %
Medicine and Dentistry 5 45%
Decision Sciences 1 9%
Computer Science 1 9%
Biochemistry, Genetics and Molecular Biology 1 9%
Engineering 1 9%
Other 0 0%
Unknown 2 18%

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 December 2015.
All research outputs
#5,807,081
of 6,790,336 outputs
Outputs from Methods in molecular biology
#3,212
of 4,795 outputs
Outputs of similar age
#235,689
of 291,128 outputs
Outputs of similar age from Methods in molecular biology
#664
of 1,023 outputs
Altmetric has tracked 6,790,336 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 4,795 research outputs from this source. They receive a mean Attention Score of 1.6. This one is in the 1st percentile – i.e., 1% 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 291,128 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 1,023 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.