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mGene is a computational tool for the genome-wide prediction of protein coding genes from eukaryotic DNA sequences. It is based on recent advances in machine learning and uses discriminative training techniques, such as support vector machines (SVMs) and hidden semi-Markov support vector machines ( HSMSVMs). : A Web Service for Accurate Computational Gene Finding. mGene. web is a web service for the genome- wide prediction of protein coding genes . Original Code for , mGene. mulit and The source code of the versions , and that have been used for .

Signal prediction. Anno2SignalLabel uses an AGS to collect labeled genomic positions for the selected genomic signal. Possible signals include transcription. Here we report on the performance of for different species and different data set sizes. We evaluate the prediction performance on the signal and. We present a highly accurate gene-prediction system for eukaryotic genomes, called mGene. It combines in an unprecedented manner the flexibility of generalized hidden Markov models (gHMMs) with the predictive power of modern machine learning methods, such as Support Vector Machines (SVMs). Its excellent.

Genome Res. Nov;19(11) doi: /gr Epub Jun mGene: accurate SVM-based gene finding with an application to nematode genomes. Schweikert G(1), Zien A, Zeller G, Behr J, Dieterich C, Ong CS, Philips P, De Bona F, Hartmann L, Bohlen A, Krüger N, Sonnenburg S, Rätsch G. 3 Jun We describe , a web service for the genome-wide prediction of protein coding genes from eukaryotic DNA sequences. It offers pre-trained models for the recognition of gene structures including untranslated regions in an increasing number of organisms. With , users have the. 7 Dec The system is based on the recently developed accurate gene finding system mGene [1], which employs state-of-the-art prediction techniques and which has been shown to perform very well compared to established gene finding systems [ 2]. In contrast to many HMM-based gene finders, mGene has the.


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