In this master’s thesis, hidden Markov models (HMM) are evaluated as a tool for forecasting movements in a currency cross. With an ever increasing electronic market, making way for more automated trading, or so called algorithmic trading, there is constantly a need
Being able to predict the sequence-structure relationship in proteins will extend the scope of many bioinformatics tools relying on structure information. Here we use Hidden Markov models (HMM) to recognize and pinpoint the location in target sequences of local structural motifs (local
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