Title |
Personalized Oncology Suite: integrating next-generation sequencing data and whole-slide bioimages
|
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Published in |
BMC Bioinformatics, September 2014
|
DOI | 10.1186/1471-2105-15-306 |
Pubmed ID | |
Authors |
Andreas Dander, Matthias Baldauf, Michael Sperk, Stephan Pabinger, Benjamin Hiltpolt, Zlatko Trajanoski |
Abstract |
Cancer immunotherapy has recently entered a remarkable renaissance phase with the approval of several agents for treatment. Cancer treatment platforms have demonstrated profound tumor regressions including complete cure in patients with metastatic cancer. Moreover, technological advances in next-generation sequencing (NGS) as well as the development of devices for scanning whole-slide bioimages from tissue sections and image analysis software for quantitation of tumor-infiltrating lymphocytes (TILs) allow, for the first time, the development of personalized cancer immunotherapies that target patient specific mutations. However, there is currently no bioinformatics solution that supports the integration of these heterogeneous datasets. |
X Demographics
Geographical breakdown
Country | Count | As % |
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United States | 5 | 63% |
United Kingdom | 1 | 13% |
India | 1 | 13% |
Unknown | 1 | 13% |
Demographic breakdown
Type | Count | As % |
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Members of the public | 5 | 63% |
Scientists | 3 | 38% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
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India | 1 | 2% |
Sweden | 1 | 2% |
Unknown | 56 | 97% |
Demographic breakdown
Readers by professional status | Count | As % |
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Researcher | 16 | 28% |
Student > Ph. D. Student | 7 | 12% |
Student > Master | 7 | 12% |
Student > Bachelor | 4 | 7% |
Professor | 3 | 5% |
Other | 14 | 24% |
Unknown | 7 | 12% |
Readers by discipline | Count | As % |
---|---|---|
Computer Science | 11 | 19% |
Medicine and Dentistry | 11 | 19% |
Agricultural and Biological Sciences | 9 | 16% |
Biochemistry, Genetics and Molecular Biology | 5 | 9% |
Engineering | 3 | 5% |
Other | 9 | 16% |
Unknown | 10 | 17% |