CRAIG is a new program for ab initio gene prediction based on a conditional random field model with semi-Markov structure that is trained with an online large-margin algorithm related to multiclass SVMs. Our experiments on benchmark vertebrate datasets and on regions from the ENCODE project show significant improvements in prediction accuracy over published gene predictors that use intrinsic features only, particularly at the gene level and on genes with long introns.
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Global Discriminative Training for Higher-Accuracy Computational Gene Prediction
Bernal A, Crammer K, Hatzigeorgiou A, Pereira F.
PLoS Comput Biol 3(3):e54. 2007