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Fig. 4 | BMC Bioinformatics

Fig. 4

From: Fangorn Forest (F2): a machine learning approach to classify genes and genera in the family Geminiviridae

Fig. 4

Flowchart of the Fangorn Forest method. First, the complete genome is given as input to the family classification model (a). If it is classified as a geminivirus the sequence is given as input for the genus classification model (b) and to the VM algorithm (c). This algorithm selects putative genes (ORFs) (d). These candidates are then given as input to the ORF classification model (e). Finally, the output of the genus model (f) and the output of the ORF model (g) are combined so that the virus genomic organization can be visualized (h). Additional analysis may be optionally performed (i). Based on the class determined by the genus model, a BLAST search with specific sequences may be performed. Furthermore, species demarcation analyses (SDT) and phylogenetic analyses may be carried out. If in the step A, the sequence is classified as non-geminivirus or if the replication origin is missing, the genomic sequence is given as input for the VM (j) algorithm. The result of the prediction (l) is presented in a table (m)

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