A dynamic Bayesian network approach to protein secondary structure prediction-2

S lin-log plots of the distributions, where the lines show fitting exponential tails for the three types of secondary structure segments. (b) The comparison between the distribution of helices observed in the dataset and those predicted by DBNand DBN. (c) The comparison of distributions between observation and prediction of sheets. (d) The comparison of distributions between observation and prediction of coils.<p><b>Copyright information:</b></p><p>Taken from "A dynamic Bayesian network approach to protein secondary structure prediction"</p><p>http://www.biomedcentral.com/1471-2105/9/49</p><p>BMC Bioinformatics 2008;9():49-49.</p><p>Published online 25 Jan 2008</p><p>PMCID:PMC2266706.</p><p>