Abstract
When screening abnormal genes [7] (such as cancer genes), it is very difficult to only rely on the experience of bioinformatics scientists, so we usually use deep learning methods for calculation and processing. But for bioinformatics scientists with relatively weak programming experience, it is unrealistic for them to independently develop abnormal gene recognition models. A Selene-based abnormal gene detection system developed in this paper completely solves this problem. It can detect abnormal genes without writing a lot of code. This article uses DeepSea and DeepSea-AlexNet convolutional neural network models to realize the function of gene detection. DeepSea-AlexNet is a model constructed by combining the characteristics of the DeepSea network and the AlexNet network. It is very useful for improving the accuracy of identifying abnormal genes.
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Zhang, Q., Jiang, Y. (2021). An Abnormal Gene Detection Method Based on Selene. In: Huang, DS., Jo, KH., Li, J., Gribova, V., Premaratne, P. (eds) Intelligent Computing Theories and Application. ICIC 2021. Lecture Notes in Computer Science(), vol 12838. Springer, Cham. https://doi.org/10.1007/978-3-030-84532-2_36
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