Currently the best algorithms for transcription factor binding site prediction are severely limited in accuracy. There is good reason to believe that predictions from these different classes of algorithms could be used in conjunction to improve the quality of predictions. In this paper, we apply single layer networks and support vector machines on predictions from key algorithms. Furthermore, w...

We introduce the OneClassMaxMinOver (OMMO) algorithm for the problem of one-class support vector classification. The algorithm is extremely simple and therefore a convenient choice for practitioners. We prove that in the hard-margin case the algorithm converges with O(1/ √ t) to the maximum margin solution of the support vector approach for one-class classification introduced by Schölkopf et al...