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Giulio Caravagna edited this page Mar 20, 2018 · 25 revisions

Current version: (2018) "Haggis and tatties"

Author: Giulio Caravagna [@gcaravagna], Institute of Cancer Research, UK.

REVOLVER is a tool for Transfer Learning (TL) in Cancer Evolution.

TL is a relatively new declination of Machine Learning in which we share information across learning tasks and domains to increase our performance. TL is an umbrella term for several paradigms; in REVOLVER what we do is actually Multi-task Learning.

REVOLVER correlates the task of selecting n trees from n patients for which sequencing data from one or more samples is available. The method, its mathematical ground and the pseudocode of the algorithm are described in the main paper.

References

  • Caravagna G, Giarratano Y, Ramazzotti D, Tomlinson I, Graham TA, Sanguinetti G, Sottoriva A. Detecting repeated cancer evolution in human tumours from multi-region sequencing data. Preprint

If you are interested in general introduction to TL, you might start from a classic:

  • Pan SJ & Yang Q (2010). A survey on transfer learning. IEEE Trans Know Data Eng, 22(10), 1345–1359.
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