Abstract
This paper presents an effective core-promoter prediction system on human DNA sequence. The system, named PromSearch, employs a hybrid approach which combines search-by-content method and search-by-signal method. Global statistics of promoter-specific contents are included to represent new significant information underlying the proximal and downstream region around transcription start site (TSS) of DNA sequence. Local signal features such as TATA box and CAAT box are encoded by the position weight matrix (PWM) method. In the experiment for the sequence set from the review by J.W.Fickett, PromSeach shows 47% positive predictive value which surpasses most of previously systems. On large genomic sequences, it shows reduced false positive rate while preserving true positive rate.
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© 2004 Springer-Verlag Berlin Heidelberg
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Kim, BH., Park, SB., Zhang, BT. (2004). PromSearch: A Hybrid Approach to Human Core-Promoter Prediction. In: Yang, Z.R., Yin, H., Everson, R.M. (eds) Intelligent Data Engineering and Automated Learning – IDEAL 2004. IDEAL 2004. Lecture Notes in Computer Science, vol 3177. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-28651-6_18
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DOI: https://doi.org/10.1007/978-3-540-28651-6_18
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-22881-3
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