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Computational Modelling and Pattern Recognition in Bioinformatics

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Time-Space, Spiking Neural Networks and Brain-Inspired Artificial Intelligence

Part of the book series: Springer Series on Bio- and Neurosystems ((SSBN,volume 7))

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Abstract

This chapter explores the ability of SNN to capture changes in Bioinformatics data for predicting events or classifying biological states from DNA, gene and protein data. It starts with a bioinformatics primer.

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Acknowledgements

The introductory biological material in Sects. 15.1 and 15.2 are mainly covered in [1, 2] and Sect. 15.4—in [34]. I acknowledge the contribution of my co-authors of the referenced in this chapter publications Elisa Capecci, Jack Dray, Lucien Koefoed, Mattias Futschik, Mike Watts, Vinita Jansari, Dimitar Dimitrov, Josafath Espinosa.

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  1. Knowledge Engineering and Discovery Research Institute (KEDRI), Auckland University of Technology, Auckland, New Zealand

    Nikola K. Kasabov

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Correspondence to Nikola K. Kasabov .

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Kasabov, N.K. (2019). Computational Modelling and Pattern Recognition in Bioinformatics. In: Time-Space, Spiking Neural Networks and Brain-Inspired Artificial Intelligence . Springer Series on Bio- and Neurosystems, vol 7. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-57715-8_15

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