Abstract
Testing for natural selection operating at molecular level has become one of the important issues in contemporary bioinformatics. In the paper the novel methodology called quasi dominance rough set approach (QDRSA) is proposed and applied for testing of balancing selection in four genes involved in human familial cancer. QDRSA can be considered as a hybrid of classical rough set approach (CRSA) and dominance rough set approach (DRSA). The advantages of QDRSA over CRSA and DRSA are illustrated for certain class of problems together with limitations of proposed methodology for other types of problems where CRSA or DRSA are better choice. The analysis of the reasons why QDRSA can produce decision algorithms yielding smaller error rates than DRSA is performed on the real world example, what shows that superiority of QDRSA in certain types of applications is of practical value.
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Cyran, K.A. (2009). Quasi Dominance Rough Set Approach in Testing for Traces of Natural Selection at Molecular Level. In: Cyran, K.A., Kozielski, S., Peters, J.F., Stańczyk, U., Wakulicz-Deja, A. (eds) Man-Machine Interactions. Advances in Intelligent and Soft Computing, vol 59. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-00563-3_16
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DOI: https://doi.org/10.1007/978-3-642-00563-3_16
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