## Description

This track shows gene predictions using the N-SCAN gene structure prediction software provided by the Computational Genomics Lab at Washington University in St. Louis, MO, USA.

## Methods

N-SCAN combines biological-signal modeling in the target genome sequence along with information from a multiple-genome alignment to generate de novo gene predictions. It extends the TWINSCAN target-informant genome pair to allow for an arbitrary number of informant sequences as well as richer models of sequence evolution. N-SCAN models the phylogenetic relationships between the aligned genome sequences, context-dependent substitution rates, insertions, and deletions.

Human N-SCAN uses mouse (mm7) as the informant and iterative pseudogene masking.

## Credits

Thanks to Michael Brent's Computational Genomics Group at Washington University St. Louis for providing this data.

Special thanks for this implementation of N-SCAN to Aaron Tenney in the Brent lab, and Robert Zimmermann, currently at Max F. Perutz Laboratories in Vienna, Austria.

## References

Gross SS, Brent MR. Using multiple alignments to improve gene prediction. In Proc. 9th Int'l Conf. on Research in Computational Molecular Biology (RECOMB '05):374-388 and J Comput Biol. 2006 Mar;13(2):379-93.

Korf I, Flicek P, Duan D, Brent MR. Integrating genomic homology into gene structure prediction. Bioinformatics. 2001 Jun 1;17(90001)S140-8.

van Baren MJ, Brent MR. Iterative gene prediction and pseudogene removal improves genome annotation. Genome Res. 2006 May;16(5):678-85.