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Bayesian Markov models consistently outperform PWMs at predicting motifs in nucleotide sequences
Matthias Siebert, View ORCID ProfileJohannes Söding
doi: https://doi.org/10.1101/047647
Matthias Siebert
1Quantitative and Computational Biology, Max Planck Institute for Biophysical Chemistry, AmFassberg 11, 37077 Göttingen, Germany
2Gene Center, Ludwig-Maximilians-Universität München, Feodor-Lynen-Strasse 25, 81377,Munich, Germany
Johannes Söding
1Quantitative and Computational Biology, Max Planck Institute for Biophysical Chemistry, AmFassberg 11, 37077 Göttingen, Germany
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Posted April 08, 2016.
Bayesian Markov models consistently outperform PWMs at predicting motifs in nucleotide sequences
Matthias Siebert, Johannes Söding
bioRxiv 047647; doi: https://doi.org/10.1101/047647
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