Artifacts from Combining Hidden Markov Models
Hidden Markov models (HMMs) are used extensively in bioinformatics to model and analyse all kinds of features. At times, simultaneous modelling of two or more features is desired, either to achieve a more refined analysis or simply to study the interactions between these features. We have some early indications that a standard approach to combined modelling introduces undesired artifacts. This project aims to further investigate the severity of such artifacts.
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