MaxEntScan::score5ss scores 9 mers using different 5'ss models

To score 3' splice sites go to MaxEntScan::score3ss

To build your own MaxEntScan models as described in the paper (below) refer to MaxEntScan::build
MaxEntScan is based on the approach for modeling the sequences of short sequence motifs such as those involved in RNA splicing which simultaneously accounts for non-adjacent as well as adjacent dependencies between positions. This method is based on the 'Maximum Entropy Principle' and generalizes most previous probabilistic models of sequence motifs such as weight matrix models and inhomogeneous Markov models.

References: Yeo G and Burge C.B., Maximum Entropy Modeling of Short Sequence Motifs with Applications to RNA Splicing Signals, RECOMB 2003 (Journal Comp. Bio in press)

Our models have been used in a successful collaboration which involves predicting splicing mutations: Eng L, Coutinho G, Nahas S, Yeo G, Tanouye R, Babaei M, Dork T, Burge C, Gatti RA. Nonclassical splicing mutations in the coding and noncoding regions of the ATM Gene: maximum entropy estimates of splice junction strengths. Hum Mutat. 2004 Jan; 23(1):67-76

For questions and comments please email Gene at geneyeo@mit.edu.