We provide a number of predefined workflows that combine different modules of our system to perform tasks like

• Single signal training, prediction and evaluation: Given a geneome annotation in gff-format and the corresponding genomic DNA sequence in fasta-format this workflow trains, predicts and evaluates one out of six different types of gene signals (acceptor and donor splice sites, transcription start sites, cleavage sites, translation initiation site and stop codon positions).

  http://galaxy.raetschlab.org/workflow/imp?id=1fad1eaf5f4f1766 (SingleSignalWorkflow, version 1.0)

• Training of all gene signal predictors: This workflow has the same inputs as the single signal workflow, but trains all six gene signals at the same time to be used subsequently for either signal predictions on any given DNA sequence or gene structure training and prediction

  http://galaxy.raetschlab.org/workflow/imp?id=964b37715ec9bd22 (SignalWorkflow, version 1.0)

• Single content training, prediction and evaluation: This workflow corresponds to the single signal workflow but trains, predicts and evaluates sensors for gene segments that accurately identify six different gene segment types (contents) namely coding exons (one general and one frame specific), introns, 5'-UTR-exons 3'UTR-exons and intergenic regions.

  http://galaxy.raetschlab.org/workflow/imp?id=2fdbd5c5858e78fb (SingleContentWorkflow, version 1.0)

• Training of all gene content predictors: With the same input as above this workflow trains predictors for all different gene segment types

  http://galaxy.raetschlab.org/workflow/imp?id=ba03619785539f8c (ContentWorkflow, version 1.0)

• Training of gene structure predictors: Based on a gff file with an initial annotation and a fasta file with the corresponding genomic DNA sequence. This workflow includes all workflows above and uses their output to train a gene structure predictor

  http://galaxy.raetschlab.org/workflow/imp?id=36ddb788a0f14eb3 (mGeneTrainWorkflow, version 1.0)

• Gene structure predictions: Using either user trained signal and gene structure predictiors or pretrained predictors from a number of model organsims this workflow predicts gene structures on a given DNA sequence. If there is a annotation in gff-format available for the given DNA sequence the prediction can be evaluated using the geneEval module.

  http://galaxy.raetschlab.org/workflow/imp?id=dff4190d282fb07a (mGenePredictWorkflow, version 1.0)

Please note: To use workflows you have to be logged in to Galaxy. If you do not have an login, you can register in a one-step procedure (use Register in the User menu).