<abstract>
<p>Among the most sought after breakthroughs nowadays to combat computational saturation in the electronic hardware realm, neuromorphic and cytomorphic mimetics of biological structures seem potentially promising. Biological circuits are distinguishable due to their minuscule dimensions and immensely low power consumption; yet they achieve extremely complex and magnificent tasks of life, such as, thinking, memorizing, decision making and self-regulating in response to the surroundings. Low power analog circuit solutions are edged over digital ones as they are inherently noisy and fuzzy like bio-systems. In this paper, an analog circuit equivalent for a well-known biological pathway, cyclic adenosine monophosphate (cAMP), has been proposed, exploiting the fabrication characteristics of an analog transistor. The work demonstrates an application of previously published research of the authors, where it was shown that a single transistor operating in analog mode can mimic some fundamental biological circuit processes like receptor-ligand binding, Michaelis Menten and Hill process reactions. Since biological pathways are chain connections of such reactions, same modular approach can be used to build electronic pathways using those basic transistor circuits. Although the idea of creating silicon life seems far-fetched at this stage, this work supplements the idea of cytomorphic chips which is already gaining interest of bio-engineering community.</p>
</abstract>
<abstract>
<p>The <italic>lac</italic> operon in <italic>E. coli</italic> has been extensively studied by computational biologists. The bacterium uses it to survive in the absence of glucose, utilizing lactose for growth. This paper presents a novel modeling mechanism for the <italic>lac</italic> operon, transferring the process of lactose metabolism from the cell to a finite state machine (FSM). This FSM is implemented in field-programmable gate array (FPGA) and simulations are run in random conditions. A Markov chain is also proposed for the <italic>lac</italic> operon, which helps study its behavior in terms of probabilistic variables, validating the finite state machine at the same time. This work is focused towards conversion of biological processes into computing machines.</p>
</abstract>
<abstract>
<p>Among the most sought after breakthroughs nowadays to combat computational saturation in the electronic hardware realm, neuromorphic and cytomorphic mimetics of biological structures seem potentially promising. Biological circuits are distinguishable due to their minuscule dimensions and immensely low power consumption; yet they achieve extremely complex and magnificent tasks of life, such as, thinking, memorizing, decision making and self-regulating in response to the surroundings. Low power analog circuit solutions are edged over digital ones as they are inherently noisy and fuzzy like bio-systems. In this paper, an analog circuit equivalent for a well-known biological pathway, cyclic adenosine monophosphate (cAMP), has been proposed, exploiting the fabrication characteristics of an analog transistor. The work demonstrates an application of previously published research of the authors, where it was shown that a single transistor operating in analog mode can mimic some fundamental biological circuit processes like receptor-ligand binding, Michaelis Menten and Hill process reactions. Since biological pathways are chain connections of such reactions, same modular approach can be used to build electronic pathways using those basic transistor circuits. Although the idea of creating silicon life seems far-fetched at this stage, this work supplements the idea of cytomorphic chips which is already gaining interest of bio-engineering community.</p>
</abstract>
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.