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Comparing approaches to predict transmembrane domains in protein sequences
Blekinge Institute of Technology, Sweden.
Travelstart Nordic, Sweden.ORCID iD: 0000-0002-8591-1035
Ericsson, Sweden.
2005 (English)In: ProceedingSAC '05 Proceedings of the 2005 ACM symposium on Applied computing, ACM Press, 2005, 185-189 p.Conference paper (Refereed)
Abstract [en]

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 se-quences with the possibility to choose between different ap-proaches 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.

Place, publisher, year, edition, pages
ACM Press, 2005. 185-189 p.
Keyword [en]
learning, classifiers, protein sequences
National Category
Computer Science
Research subject
Computer and Information Sciences Computer Science, Computer Science
URN: urn:nbn:se:lnu:diva-42364DOI: 10.1145/1066677.1066720ISBN: 1-58113-964-0OAI: diva2:805245
2005 ACM Symposium on Applied computing
Available from: 2015-04-15 Created: 2015-04-15 Last updated: 2015-09-17Bibliographically approved

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Hagelbäck, Johan
Computer Science

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