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TitleMachine Learning for Personalized Medicine
LanguageEnglish
File Size8.7 MB
Total Pages89
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Page 1

Machine Learning for Personalized Medicine

Karsten Borgwardt

ETH Zürich Fraunhofer-Institut Kaiserslautern, September 30, 2016

Department Biosystems

Page 2

The Need for Machine Learning in Computational Biology

BGI Hong Kong, Tai Po Industrial Estate, Hong Kong

High-throughput technologies:

Genome and RNA sequencing

Compound screening

Genotyping chips

Bioimaging

Molecular databases are growing much faster than our knowledge of biological processes.

Department Biosystems Karsten Borgwardt ITWM Kaiserslautern September 30, 2016 2 / 76

Page 44

The Evolution of Bioinformatics

Future of Bioinformatics: Personalized Medicine

Department Biosystems Karsten Borgwardt ITWM Kaiserslautern September 30, 2016 43 / 76

Page 45

Personalized Medicine: Biomarker Discovery

Personalized Medicine

Tailoring medical treatment to the molecular properties of a patient

Biomarker Discovery

Detecting molecular components that are indicative of disease outbreak, progression or
therapy outcome

Biomarker

The term ‘biomarker’, short for ‘biological marker’, refers to a broad subcategory of medical
signs — that is, objective indications of medical state observed from outside the patient —
which can be measured accurately and reproducibly (Strimbu and Tavel, 2010).

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Page 88

Main References III

F. Llinares-López, et al., Bioinformatics 31, 240 (2015).

N. Shervashidze, K. M. Borgwardt, NIPS , Y. Bengio, D. Schuurmans, J. Lafferty,
C. K. I. Williams, A. Culotta, eds. (MIT Press, Cambridge, MA, 2009), pp.
1660–1668.

M. Sugiyama, K. M. Borgwardt, Advances in Neural Information Processing Systems
26: 27th Annual Conference on Neural Information Processing Systems 2013. (2013),
pp. 467–475.

M. Sugiyama, C. Azencott, D. Grimm, Y. Kawahara, K. M. Borgwardt, Proceedings
of the 2014 SIAM International Conference on Data Mining, Philadelphia,
Pennsylvania, USA, April 24-26, 2014 (2014), pp. 199–207.

M. Sugiyama, F. Llinares-López, N. Kasenburg, K. M. Borgwardt, SIAM Data Mining
(2015).

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Page 89

Main References IV

R. E. Tarone, Biometrics 46, 515 (1990).

A. Terada, M. Okada-Hatakeyama, K. Tsuda, J. Sese, Proceedings of the National
Academy of Sciences 110, 12996 (2013).

A. Terada, K. Tsuda, J. Sese, IEEE International Conference on Bioinformatics and
Biomedicine (2013), pp. 153–158.

P. H. Westfall, S. S. Young, Statistics in Medicine 13, 1084 (1993).

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