https://pages.htgaa.org/2026a/tuzun-guvener/homework/week-07-hw-genetic-circuits-part-ii/index.htmlAssignment Part 1: Intracellular Artificial Neural Networks (IANNs) 1. What advantages do IANNs have over traditional genetic circuits, whose input/output behaviors are Boolean functions? A Boolean function is based on a binary system where it can only assign two values, such as "true" or "false", or as in numeric values: "0" or "1". This is akin to digital systems. Complexities in the biological systems cannot be adequately represented by binary input/output. Because signals in biological systems, such as concentrations of regulatory proteins, vary in gradation. So, a Boolean genetic circuit would have limitations in interpreting the complexities of a biological system. IANNs are based on analog systems where weights are implemented. Examples of weights include variable concentrations of regulatory proteins, promoter strengths, and RBS efficiencies. These make positive or negative regulatory output. IANNs also integrate dose-response analysis, from inhibitory to non-inhibitory concentrations of a typical sigmoidal curve. IANNs consider biases such as taking into account whether promoters could be leaky. Advantageous parts are the ability to handle a great level of complexity due to the gradation that living systems have. 2. Describe a useful application for an IANN; include a detailed description of input/output behavior, as well as any limitations an IANN might face to achieve your goal.Hugoen