AdaptRM has a multi-tasking framework for the synergetic learning of epitranscriptomes. It was enabled by an adaptive pooling layer and several standard convolution blocks. Trained for an integrated multi-task formulated by three case studies, the model can operate on low-resolution and high-resolution datasets without further preprocessing the input primary sequence, and conduct tissue-specific and type-specific prediction according to users’ needs.

Users need to specify a task of interest first, and input or upload the query sequences in the Fasta format. Results will be presented or downloaded after a while.

The result table shows the prediction result. Results can be downloaded from this page.

We displayed a framework figure and a brief introduction of the model. Users can download this model directly from this site.