Background: Prediction of protein structural classes (a, b, a + b and a/b) from amino acid sequences is of great importance, as it is beneficial to study protein function, regulat...
Abstract. We describe and empirically evaluate machine learning methods for the prediction of zinc binding sites from protein sequences. We start by observing that a data set consi...
Sauro Menchetti, Andrea Passerini, Paolo Frasconi,...
We present a structured output prediction approach for classifying potential anti-cancer drugs. Our QSAR model takes as input a description of a molecule and predicts the activity...
In many applications, replacing a complex word form by its stem can reduce sparsity, revealing connections in the data that would not otherwise be apparent. In this paper, we focu...
Shane Bergsma, Aditya Bhargava, Hua He, Grzegorz K...
Web extraction systems attempt to use the immense amount of unlabeled text in the Web in order to create large lists of entities and relations. Unlike traditional IE methods, the ...