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Lung Cancer and Personalized Medicine: Novel Therapies and Clinical Management

Overview of attention for book
Attention for Chapter 7: Next-Generation Sequencing and Applications to the Diagnosis and Treatment of Lung Cancer.
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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 (91st percentile)
  • High Attention Score compared to outputs of the same age and source (92nd percentile)

Mentioned by

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2 news outlets
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3 X users

Citations

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13 Dimensions

Readers on

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57 Mendeley
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Chapter title
Next-Generation Sequencing and Applications to the Diagnosis and Treatment of Lung Cancer.
Chapter number 7
Book title
Lung Cancer and Personalized Medicine: Novel Therapies and Clinical Management
Published in
Advances in experimental medicine and biology, December 2015
DOI 10.1007/978-3-319-24932-2_7
Pubmed ID
Book ISBNs
978-3-31-924931-5, 978-3-31-924932-2
Authors

Kruglyak, Kristina M, Lin, Erick, Ong, Frank S, Kristina M. Kruglyak Ph.D., Erick Lin M.D., Ph.D., Frank S. Ong M.D., Kristina M. Kruglyak, Erick Lin, Frank S. Ong, Kruglyak, Kristina M., Ong, Frank S.

Editors

Aamir Ahmad, Shirish M. Gadgeel

Abstract

Cancer is a genetic disease characterized by uncontrolled growth of abnormal cells. Over time, somatic mutations accumulate in the cells of an individual due to replication errors, chromosome segregation errors, or DNA damage. When not caught by traditional mechanisms, these somatic mutations can lead to cellular proliferation, the hallmark of cancer. Lung cancer is the leading cause of cancer-related mortality in the United States, accounting for approximately 160,000 deaths annually. Five year survival rates for lung cancer remain low (<50 %) for all stages, with even worse prognosis (<15 %) in late stage cases. Technological advances, including advances in next-generation sequencing (NGS), offer the vision of personalized medicine or precision oncology, wherein an individual's treatment can be based on his or her individual molecular profile, rather than on historical population-based medicine. Towards this end, NGS has already been used to identify new biomarker candidates for the early diagnosis of lung cancer and is increasingly used to guide personalized treatment decisions. In this review we will provide a high-level overview of NGS technology and summarize its application to the diagnosis and treatment of lung cancer. We will also describe how NGS can drive advances that bring us closer to precision oncology and discuss some of the technical challenges that will need to be overcome in order to realize this ultimate goal.

X Demographics

X Demographics

The data shown below were collected from the profiles of 3 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 57 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 57 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 8 14%
Student > Bachelor 7 12%
Researcher 6 11%
Student > Postgraduate 5 9%
Student > Ph. D. Student 4 7%
Other 8 14%
Unknown 19 33%
Readers by discipline Count As %
Medicine and Dentistry 11 19%
Biochemistry, Genetics and Molecular Biology 8 14%
Computer Science 3 5%
Agricultural and Biological Sciences 3 5%
Social Sciences 3 5%
Other 7 12%
Unknown 22 39%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 18. 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 04 February 2023.
All research outputs
#1,930,204
of 24,203,404 outputs
Outputs from Advances in experimental medicine and biology
#268
of 5,177 outputs
Outputs of similar age
#33,564
of 399,074 outputs
Outputs of similar age from Advances in experimental medicine and biology
#33
of 431 outputs
Altmetric has tracked 24,203,404 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 92nd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 5,177 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.6. This one has done particularly well, scoring higher than 94% 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 399,074 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 91% of its contemporaries.
We're also able to compare this research output to 431 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 92% of its contemporaries.