Background: Likelihood-based phylogenetic inference is generally considered to be the most reliable classification method for unknown sequences. However, traditional likelihood-ba...
Frederick A. Matsen III, Robin B. Kodner, E. Virgi...
We describe a method for the fully automatic learning of hierarchical finite state translation models. The input to the method is transcribed speech utterances and their correspon...
In contrast to proteins, many classes of functionally related RNA molecules show a rather weak sequence conservation but instead a fairly well conserved secondary structure. Hence ...
Background: Design of protein structure comparison algorithm is an important research issue, having far reaching implications. In this article, we describe a protein structure com...
This article proposes an algorithm to automatically learn useful transformations of data to improve accuracy in supervised classification tasks. These transformations take the for...