Background: Single Nucleotide Polymorphisms (SNPs) are the most abundant form of genomic variation and can cause phenotypic differences between individuals, including diseases. Ba...
Vinayak Kulkarni, Mounir Errami, Robert Barber, Ha...
Background: Classification and variable selection play an important role in knowledge discovery in highdimensional data. Although Support Vector Machine (SVM) algorithms are among...
Natalia Becker, Grischa Toedt, Peter Lichter, Axel...
Background: Sequence-derived structural and physicochemical descriptors have frequently been used in machine learning prediction of protein functional families, thus there is a ne...
Serene A. K. Ong, Hong Huang Lin, Yu Zong Chen, Ze...
In this paper we embed evolutionary computation into statistical learning theory. First, we outline the connection between large margin optimization and statistical learning and s...