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BMC Cancer
Published in: BMC Cancer 1/2015

Open Access 01-12-2015 | DEBATE

Computational cancer biology: education is a natural key to many locks

Authors: Frank Emmert-Streib, Shu-Dong Zhang, Peter Hamilton

Published in: BMC Cancer | Issue 1/2015

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Abstract

Background

Oncology is a field that profits tremendously from the genomic data generated by high-throughput technologies, including next-generation sequencing. However, in order to exploit, integrate, visualize and interpret such high-dimensional data efficiently, non-trivial computational and statistical analysis methods are required that need to be developed in a problem-directed manner.

Discussion

For this reason, computational cancer biology aims to fill this gap. Unfortunately, computational cancer biology is not yet fully recognized as a coequal field in oncology, leading to a delay in its maturation and, as an immediate consequence, an under-exploration of high-throughput data for translational research.

Summary

Here we argue that this imbalance, favoring ’wet lab-based activities’, will be naturally rectified over time, if the next generation of scientists receives an academic education that provides a fair and competent introduction to computational biology and its manifold capabilities. Furthermore, we discuss a number of local educational provisions that can be implemented on university level to help in facilitating the process of harmonization.
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Metadata
Title
Computational cancer biology: education is a natural key to many locks
Authors
Frank Emmert-Streib
Shu-Dong Zhang
Peter Hamilton
Publication date
01-12-2015
Publisher
BioMed Central
Published in
BMC Cancer / Issue 1/2015
Electronic ISSN: 1471-2407
DOI
https://doi.org/10.1186/s12885-014-1002-2

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