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

BMC Cancer

Frank Emmert-Streib¹  Shu-Dong Zhang²  Peter Hamilton² 

[1] Computational Biology and Machine Learning Laboratory, Center for Cancer Research and Cell Biology, School of Medicine, Dentistry and Biomedical Sciences, Faculty of Medicine, Health and Life Sciences, Queen’s University Belfast, Belfast, Lisburn Road, Belfast, UK

[2] Center for Cancer Research and Cell Biology, School of Medicine, Dentistry and Biomedical Sciences, Faculty of Medicine, Health and Life Sciences, Queen’s University Belfast, Lisburn Road, Belfast, UK

关键词: Systems medicine;    Statistical genomics;    Computational genomics;    Computational oncology;    Genomics data;    Computational biology;    Cancer;   

Others  :  1106757
DOI  :  10.1186/s12885-014-1002-2

 received in 2014-07-05, accepted in 2014-12-22,  发布年份 2015

【 摘 要 】

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.

【 授权许可】

   
2015 Emmert-Streib et al.; licensee BioMed Central.

【 图 表 】

Figure 1.

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