GEO DataSets

(Submitter supplied) Degradome sequencing is commonly used to generate high-throughput information on mRNA cleavages by small RNAs. Here we developed an extension module based on a deep learning convolutional neural network (CNN) in a machine learning environment to discriminate false from true cleavage sites applied on datasets from potato (Solanum tuberosum, St) and the oomycete pathogen Phytophthora infestans (Pi). The core of the CNN module is a stochastic gradient descent optimizer with cyclical learning rate (CLR) which together with Bayesian optimization scored a validation accuracy of 100%. more...

Organism:

Solanum tuberosum; Phytophthora infestans

Type:

Expression profiling by high throughput sequencing; Non-coding RNA profiling by high throughput sequencing

4 related Platforms

35 Samples

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