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Interpretable convolutional neural networks for effective translation initiation site prediction
2017
2017 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)
Thanks to rapidly evolving sequencing techniques, the amount of genomic data at our disposal is growing increasingly large. Determining the gene structure is a fundamental requirement to effectively interpret gene function and regulation. An important part in that determination process is the identification of translation initiation sites. In this paper, we propose a novel approach for automatic prediction of translation initiation sites, leveraging convolutional neural networks that allow for
doi:10.1109/bibm.2017.8217833
dblp:conf/bibm/ZuallaertKSN17
fatcat:qgdnnj5skrcuno2c7sewwilhba