There are today several systems for predicting transmembrane domains in membrane protein sequences. As they are based on different classifiers as well as different pre-and post-processing techniques, it is very difficult to evaluate the performance of the particular classifier used. We have developed a system called MemMiC for predicting transmembrane domains in protein sequences with the possibility to choose between different approaches to pre-and post-processing as well as different classifiers. Therefore it is possible to compare the performance of each classifier in a certain environment as well as the different approaches to pre-and post-processing. We have demonstrated the usefulness of MemMiC in a set of experiments, which shows, e.g., that the performance of a classifier is very dependent on which pre-and post-processing techniques are used.
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