Artificial Neural Networks for Protein Secondary Structure Prediction

The biological function of a protein is strongly influenced by its three
dimensional structure. Predicting this structure, however, is not an easy
task: as a protein is synthesised, it will twist into different shapes and
structures, according to the electrostatic interactions of its constituents.

The initial protein sequence will twist into a secondary structure, and from
there into the tertiary structure and its final configuration. Predicting
the secondary structure of proteins from raw sequence information is therefore
an important step towards predicting their final conformation.

In this seminar, I will be reviewing the application of artificial neural
networks to this problem over the last decade and a half.