Cancer Communications
indexed by SCI
BMC

doi: 10.1186/s40880-015-0008-8
Cancer research in the era of next-generation sequencing and big data calls for intelligent modeling
Jari Yli-Hietanen, Antti Ylipaa and Olli Yli-Harja
Department of Signal Processing, Tampere University of Technology, Tampere 33101, Finland
[Abstract] We examine the role of big data and machine learning in cancer research. We describe an example in cancer research where gene-level data from The Cancer Genome Atlas (TCGA) consortium is interpreted using a pathway-level model. As the complexity of computational models increases, their sample requirements grow exponentially. This growth stems from the fact that the number of combinations of variables grows exponentially as the number of variables increases. Thus, a large sample size is needed. The number of variables in a computational model can be reduced by incorporating biological knowledge. One particularly successful way of doing this is by using available gene regulatory, signaling, metabolic, or context-specific pathway information. We conclude that the incorporation of existing biological knowledge is essential for the progress in using big data for cancer research.
Chinese Journal of Cancer 2015, Volume: 34, Issue 10
[ PDF Full-text ]
[ Html full-text / Citation export] (BioMed Central)

[Google Scholar]


Cite this article

Jari Yli-Hietanen, Antti Ylipaa and Olli Yli-Harja. Cancer research in the era of next-generation sequencing and big data calls for intelligent modeling. Chin J Cancer. 2015, 34:12. doi:10.1186/s40880-015-0008-8


Export citations

EndNote


SHARE THIS ARTICLE


Your Comments

  

 


Comments:


CJC Wechat 微信公众号

CJC触屏版


 

Editorial Manager


CC adopts Editorial Manager to manage its submissions from Dec.18, 2014
 

 

Reference style for  

 EndNote,
 Reference Manager



Editorial Manager


 

Year:

 

Month:

Advanced search

Subscription


CJC is now published by BioMed Central

© Chinese Journal of Cancer

Sun Yat-sen University Cancer Center

651 Dongfeng Road East, Guangzhou 510060, P. R. China