Representative transcript sets for evaluating a translational initiation sites predictor |
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| Authors: | Jia Zeng Reda Alhajj Douglas J Demetrick |
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| Affiliation: | (1) Department of Computer Science, University of Calgary, Calgary, AB, T2N 1N4, Canada;(2) Department of Computer Science, Global University, Beirut, Lebanon;(3) Department of Pathology & Laboratory Medicine, Oncology, Biochemistry & Molecular Biology, University of Calgary, Calgary, AB, T2N 1N4, Canada |
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| Abstract: | Background Translational initiation site (TIS) prediction is a very important and actively studied topic in bioinformatics. In order to complete a comparative analysis, it is desirable to have several benchmark data sets which can be used to test the effectiveness of different algorithms. An ideal benchmark data set should be reliable, representative and readily available. Preferably, proteins encoded by members of the data set should also be representative of the protein population actually expressed in cellular specimens. |
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