Detection of polyadenylation signals in human DNA sequences

We present polyadq, a program for detection of human polyadenylation signals. To avoid training on possibly flawed data, the development of polyadq began with a de novo characterization of human mRNA 3' processing signals. This information was used in training two quadratic discriminant functions that polyadq uses to evaluate potential polyA signals. In our tests, polyadq predicts polyA signals with a correlation coefficient of 0.413 on whole genes and 0.512 in the last two exons of genes, substantially outperforming other published programs on the same data set. polyadq is also the only program that is able to consistently detect the ATTAAA variant of the polyA signal.     

An RNA folding method capable of identifying pseudoknots and base triples

MOTIVATION: Recently, we described a Maximum Weighted Matching (MWM) method for RNA structure prediction. The MWM method is capable of detecting pseudoknots and other tertiary base-pairing interactions in a computationally efficient manner (Cary and Stormo, Proceedings of the Third International Conference on Intelligent Systems for Molecular Biology, pp. 75-80, 1995). Here we report on the results of our efforts to improve the MWM method's predictive accuracy, and show how the method can be extended to detect base interactions formerly inaccessible to automated RNA modeling techniques. RESULTS: Improved performance in MWM structure prediction was achieved in two ways. First, new ways of calculating base pair likelihoods have been developed. These allow experimental data and combined statistical and thermodynamic information to be used by the program. Second, accuracy was improved by developing techniques for filtering out spurious base pairs predicted by the MWM program. We also demonstrate here a means by which the MWM folding method may be used to detect the presence of base triples in RNAs. AVAILABILITY: http://www.cshl.org/mzhanglab/tabaska/j axpage. html CONTACT: tabaska@cshl.org      

Identifying the 3'-terminal exon in human DNA.

MOTIVATION: We present JTEF, a new program for finding 3' terminal exons in human DNA sequences. This program is based on quadratic discriminant analysis, a standard non-linear statistical pattern recognition method. The quadratic discriminant functions used for building the algorithm were trained on a set of 3' terminal exons of type 3tuexon (those containing the true STOP codon). RESULTS: We showed that the average predictive accuracy of JTEF is higher than the presently available best programs (GenScan and Genemark.hmm) based on a test set of 65 human DNA sequences with 121 genes. In particular JTEF performs well on larger genomic contigs containing multiple genes and significant amounts of intergenic DNA. It will become a valuable tool for genome annotation and gene functional studies. AVAILABILITY: JTEF is available free for academic users on request from ftp://cshl.org/pub/science/mzhanglab/JTEF and will be made available through the World Wide Web (http://argon.cshl.org/).