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A hidden Markov model of signal peptides has been developed. It contains submodels for the N-terminal part, the hydrophobic region, and the region around the cleavage site. For known signal peptides, the model can be used to assign objective boundaries between these three regions. Applied to our data, the length distributions for the three regions are(More)
We provide a unified overview of methods that currently are widely used to assess the accuracy of prediction algorithms, from raw percentages, quadratic error measures and other distances, and correlation coefficients, and to information theoretic measures such as relative entropy and mutual information. We briefly discuss the advantages and disadvantages(More)
We have developed a new method for the identification of signal peptides and their cleavage sites based on neural networks trained on separate sets of prokaryotic and eukaryotic sequences. The method performs significantly better than previous prediction schemes, and can easily be applied to genome-wide data sets. Discrimination between cleaved signal(More)
Translation in eukaryotes does not always start at the first AUG in an mRNA, implying that context information also plays a role. This makes prediction of translation initiation sites a non-trivial task, especially when analysing EST and genome data where the entire mature mRNA sequence is not known. In this paper, we employ artificial neural networks to(More)
Hidden Markov models were introduced in the beginning of the 1970's as a tool in speech recognition. During the last decade they have been found useful in addressing problems in computational biology such as characterising sequence families, gene finding, structure prediction and phylogenetic analysis. In this paper we propose several measures between(More)
In a double-blind cross-over trial, 20 chronic schizophrenic patients were treated with sulpiride and haloperidol in two 12-week periods. The final median dose of sulpiride was 2000 mg/day (range 800-3200) and of haloperidol 12 mg/day (range 6-24). Sulpiride had an antipsychotic effect and therapeutic profile not significantly different from that of(More)
Sixteen out of 25 hebephrenic and paranoid schizophrenic patients completed a double-blind cross-over study with sulpiride and haloperidol. The patient sample was relatively chronic: Median age was 35 years (range 26-53 years), median duration of illness 10 years (4-35 years), and median duration of neuroleptic treatment 5 years (1-28 years). Each patient(More)
BACKGROUND Rapid risk stratification is a core task in emergency medicine. Identifying patients at high and low risk shortly after admission could help clinical decision-making regarding treatment, level of observation, allocation of resources and post discharge follow-up. The purpose of the present study was to determine short-, mid- and long-term(More)
Machine learning is widely used to analyze biological sequence data. Non-sequential models such as SVMs or feed-forward neural networks are often used although they have no natural way of handling sequences of varying length. Recurrent neural networks such as the long short term memory (LSTM) model on the other hand are designed to handle sequences. In this(More)