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Description
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Mutation information is missing. The system will default to predicting based on absence of mutation. Please confirm to proceed or return to modify.
Model Introduction
RNA Splicer is an AI-driven tool jointly developed by Cyagen Biosciences and the AI Innovation Center of Tsinghua University Pearl River Delta Research Institute, designed to predict the impact of sequence variants on RNA splicing.
The AI model of RNA Splicer innovatively combines the deep learning DanQ model and the Transformer model, while also integrating the E-value algorithm from bioinformatics.
By training on normal splicing data, this tool can predict potential mRNA splicing alterations following base sequence variants, providing robust technical support for research into the effects of gene variants on RNA splicing.
Second base in codon
First base in codon
Last base in codon
Please enter the mutation site in the following input box for prediction.
Codon Chart
Model Introduction
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