Prediction of protein tertiary structure class from synchrotron radiation circular dichroism spectra

A new approach to predict the tertiary structure class of proteins from synchrotron radiation circular dichroism (SRCD) spectra is presented. A protein's SRCD spectrum is first approximated using a Radial Basis Function Network (RBFN) and the resulting set is used to train different varieties of Support Vector Machine (SVM). The performance of three well known multi-class SVM schemes are evaluated and a method presented that takes into account the properties of spectra for each of the structure classes.</p

Prediction of protein tertiary structure class from synchrotron radiation circular dichroism spectra

A new approach to predict the tertiary structure class of proteins from synchrotron radiation circular dichroism (SRCD) spectra is presented. A protein's SRCD spectrum is first approximated using a Radial Basis Function Network (RBFN) and the resulting set is used to train different varieties of Support Vector Machine (SVM). The performance of three well known multi-class SVM schemes are evaluated and a method presented that takes into account the properties of spectra for each of the structure classes