Recent advances in DNA sequencing techniques have led to an increase in the identification of single nucleotide polymorphisms (SNPs) in BRCA1 and BRCA2 genes, but no further information regarding the deleterious probability of many of them is available (Variants of Unknown Significance/VUS). As a result, in the current study, different sequence- and structure-based computation...

This chapter presents a novel framework for tuning the parameters of Evolutionary Algorithms. A hybrid technique combining Meta-EAs and statistical Racing approaches is developed, which is not only capable of effectively exploring the search space of numerical parameters but also suitable for tuning symbolic parameters where it is generally difficult to define any sensible distance metric.

In this position paper we deal with the conception of heterogeneity as both the force and the result of evolutionary change. We ask, how this heterogeneity can be measured empirically and how we can get a measure which allows to get a broad comparable empirical account especially on several levels of aggregation. Based on this discussion we suggest that for several questions the measures of tot...

Group Search Optimizer(GSO) is one of the best algorithms, and is very new in the field of Evolutionary Computing. It is very robust and efficient algorithm, which is inspired by animal searching behaviour. The paper describes an application of GSO to clustering of networks. We have tested GSO against five standard benchmark datasets and the algorithm is proven to be very competitive in terms o...