Title |
Brain cancer prognosis: independent validation of a clinical bioinformatics approach
|
---|---|
Published in |
Journal of Clinical Bioinformatics, February 2012
|
DOI | 10.1186/2043-9113-2-2 |
Pubmed ID | |
Authors |
Raffaele Fronza, Michele Tramonti, William R Atchley, Christine Nardini |
Abstract |
Translational and evidence based medicine can take advantage of biotechnology advances that offer a fast growing variety of high-throughput data for screening molecular activities of genomic, transcriptional, post-transcriptional and translational observations. The clinical information hidden in these data can be clarified with clinical bioinformatics approaches. We have recently proposed a method to analyze different layers of high-throughput (omic) data to preserve the emergent properties that appear in the cellular system when all molecular levels are interacting. We show here that this method applied to brain cancer data can uncover properties (i.e. molecules related to protective versus risky features in different types of brain cancers) that have been independently validated as survival markers, with potential important application in clinical practice. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
United Kingdom | 1 | 33% |
Germany | 1 | 33% |
France | 1 | 33% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Science communicators (journalists, bloggers, editors) | 1 | 33% |
Scientists | 1 | 33% |
Members of the public | 1 | 33% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 1 | 6% |
Italy | 1 | 6% |
Unknown | 16 | 89% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 6 | 33% |
Researcher | 6 | 33% |
Other | 2 | 11% |
Student > Bachelor | 2 | 11% |
Professor | 1 | 6% |
Other | 1 | 6% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 8 | 44% |
Medicine and Dentistry | 3 | 17% |
Biochemistry, Genetics and Molecular Biology | 2 | 11% |
Computer Science | 2 | 11% |
Business, Management and Accounting | 1 | 6% |
Other | 2 | 11% |