| Title |
Mining Cancer Transcriptomes: Bioinformatic Tools and the Remaining Challenges
|
|---|---|
| Published in |
Molecular Diagnosis & Therapy, February 2017
|
| DOI | 10.1007/s40291-017-0264-1 |
| Pubmed ID | |
| Authors |
Thomas Milan, Brian T. Wilhelm |
| Abstract |
The development of next-generation sequencing technologies has had a profound impact on the field of cancer genomics. With the enormous quantities of data being generated from tumor samples, researchers have had to rapidly adapt tools or develop new ones to analyse the raw data to maximize its value. While much of this effort has been focused on improving specific algorithms to get faster and more precise results, the accessibility of the final data for the research community remains a significant problem. Large amounts of data exist but are not easily available to researchers who lack the resources and experience to download and reanalyze them. In this article, we focus on RNA-seq analysis in the context of cancer genomics and discuss the bioinformatic tools available to explore these data. We also highlight the importance of developing new and more intuitive tools to provide easier access to public data and discuss the related issues of data sharing and patient privacy. |
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.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 19 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 19 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Bachelor | 4 | 21% |
| Student > Master | 3 | 16% |
| Researcher | 2 | 11% |
| Student > Doctoral Student | 1 | 5% |
| Student > Ph. D. Student | 1 | 5% |
| Other | 1 | 5% |
| Unknown | 7 | 37% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 4 | 21% |
| Computer Science | 2 | 11% |
| Medicine and Dentistry | 2 | 11% |
| Social Sciences | 1 | 5% |
| Biochemistry, Genetics and Molecular Biology | 1 | 5% |
| Other | 2 | 11% |
| Unknown | 7 | 37% |
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 September 2018.
All research outputs
#15,815,903
of 23,577,654 outputs
Outputs from Molecular Diagnosis & Therapy
#230
of 392 outputs
Outputs of similar age
#198,225
of 312,460 outputs
Outputs of similar age from Molecular Diagnosis & Therapy
#9
of 15 outputs
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