An unsupervised classification scheme for improving predictions of prokaryotic TIS |
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Authors: | Maike Tech and Peter Meinicke |
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Institution: | (1) Abteilung Bioinformatik, Institut f?r Mikrobiologie und Genetik, Georg-August-Universit?t G?ttingen, Goldschmidtstr. 1, 37077 G?ttingen, Germany |
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Abstract: | Background Although it is not difficult for state-of-the-art gene finders to identify coding regions in prokaryotic genomes, exact prediction
of the corresponding translation initiation sites (TIS) is still a challenging problem. Recently a number of post-processing
tools have been proposed for improving the annotation of prokaryotic TIS. However, inherent difficulties of these approaches
arise from the considerable variation of TIS characteristics across different species. Therefore prior assumptions about the
properties of prokaryotic gene starts may cause suboptimal predictions for newly sequenced genomes with TIS signals differing
from those of well-investigated genomes. |
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Keywords: | |
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