Hidden Markov models (HMMs) are often used for biological sequence annotation. Each sequence feature is represented by a collection of states with the same label. In annotating a ...
Background: Traditional algorithms for hidden Markov model decoding seek to maximize either the probability of a state path or the number of positions of a sequence assigned to th...
Background: Existing hidden Markov model decoding algorithms do not focus on approximately identifying the sequence feature boundaries. Results: We give a set of algorithms to com...
Assigning functions to novel proteins is one of the most important problems in the post-genomic era. Several approaches have been applied to this problem, including analyzing gene...
Minghua Deng, Kui Zhang, Shipra Mehta, Ting Chen, ...
Proteins are large organic compounds made of amino acids arranged in a linear chain (primary structure). Most proteins fold into unique threedimensional (3D) structures called inte...
Marco Vassura, Luciano Margara, Filippo Medri, Pie...