Putative synaptic genes defined from a Drosophila whole body developmental transcriptome by a machine learning approach

BACKGROUND: Assembly and function of neuronal synapses require the coordinated expression of a yet undetermined set of genes. Although roughly a thousand genes are expected to be important for this function in Drosophila melanogaster, just a few hundreds of them are known so far. RESULTS: In this work we trained three learning algorithms to predict a “synaptic function” for genes of Drosophila using data from a whole-body developmental transcriptome published by others. Using statistical and biological criteria to analyze and combine the predictions, we obtained a gene catalogue that is highly enriched in genes of relevance for Drosophila synapse assembly and function but still not recognized as such. CONCLUSIONS: The utility of our approach is that it reduces the number of genes to be tested through hypothesis-driven experimentation. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12864-015-1888-3) contains supplementary material, which is available to authorized users.