Week 7 HW: Genetic circuits part II

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Assignment Part 1: Intracellular Artificial Neural Networks (IANNs)

1. What advantages do IANNs have over traditional genetic circuits, whose input/output behaviors are Boolean functions?

  • Boolean functions are limited to discrete on/off states while IANNs are capable of processing analogue signals and, because of that, carry more information. Real world phenomena are analog, inside a cell there is inherent molecular noise, and Boolean circuits are fragile to this, especially at low signal concentrations.

  • Boolean functions can only handle simple logical relationships (AND/OR/etc..) between inputs. IANNs, through weighted connections and nonlinear activation functions are capable of solving problems that are not linearly separable. [1]

  • IANNs have potential for Adaptability and unsupervised learning. There´s a principle known as neurons that fire together, wire together:

    “This means that the strength of the connection between neurons changes based on how often they are activated. When a connection between two neurons is activated frequently, its weight increases and vice-versa: when the activation is less frequent, the weight weakens.” [1]

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.
3. Below is a diagram depicting an intracellular single-layer perceptron where the X1 input is DNA encoding for the Csy4 endoribonuclease and the X2 input is DNA encoding for a fluorescent protein output whose mRNA is regulated by Csy4. Tx: transcription; Tl: translation.
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Draw a diagram for an intracellular multilayer perceptron where layer 1 outputs an endoribonuclease that regulates a fluorescent protein output in layer 2.

Assignment Part 2: Fungal Materials

1. What are some examples of existing fungal materials and what are they used for? What are their advantages and disadvantages over traditional counterparts?
2. What might you want to genetically engineer fungi to do and why? What are the advantages of doing synthetic biology in fungi as opposed to bacteria?
Bibliography

[1] A. Halužan Vasle and M. Moškon, “Synthetic biological neural networks: From current implementations to future perspectives,” BioSystems, vol. 237, p. 105164, Feb. 2024, doi: 10.1016/j.biosystems.2024.105164.