Hidden Markov Models are a widely used generative model for analysing sequence data. A variant, Profile Hidden Markov Models are a special case used in Bioinformatics to represent,...
Stefan Mutter, Bernhard Pfahringer, Geoffrey Holme...
We present a new semi-supervised training procedure for conditional random fields (CRFs) that can be used to train sequence segmentors and labelers from a combination of labeled a...
Feng Jiao, Shaojun Wang, Chi-Hoon Lee, Russell Gre...
Computational protein design can be formulated as an optimization problem, where the objective is to identify the sequence of amino acids that minimizes the energy of a given prot...
Noah Ollikainen, Ellen Sentovich, Carlos Coelho, A...
Background: Amino acid sequence probability distributions, or profiles, have been used successfully to predict secondary structure and local structure in proteins. Profile models ...
We consider video sequences that have been encrypted uncompressed. Since encryption masks the source, traditional data compression algorithms are rendered ineffective. However, it...
Daniel Schonberg, Chuohao Yeo, Stark C. Draper, Ka...