Article
Version 1
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A Turing Machine for the Life Sciences
Version 1
: Received: 22 May 2024 / Approved: 22 May 2024 / Online: 23 May 2024 (02:56:04 CEST)
How to cite: Spratt, S. A Turing Machine for the Life Sciences. Preprints 2024, 2024051471. https://doi.org/10.20944/preprints202405.1471.v1 Spratt, S. A Turing Machine for the Life Sciences. Preprints 2024, 2024051471. https://doi.org/10.20944/preprints202405.1471.v1
Abstract
During the development of new medicines mutually exclusive specificity appears to be required but hitherto is most often included at the late clinical trial stage. Here, I describe the use of Hedgehog signalling in Drosophila as a model to represent a mutually exclusive relationship within the context and report the identification of CG43658, a putative Rho guanine nucleotide exchange factor and orthologue of the Charcot-Marie-Tooth disease associated gene ARHGEF10. Furthermore, a Computer that is able to consider the whole and describe the sum of everything in it absolutely in unambiguous terms is a useful tool. Here I describe such a computer with a suggestion for an application to examine any component in the context where a medicine is sought. Taken, together I would like to propose this method as a fundamental necessity and improvement upon current existing methods related not only to Hedgehog signalling but plausibly to life science research and the search for medicines in general.
Keywords
Turing machine; Drosophila; Mutual exclusivity; Specificity; In vivo database searching; Machine learning
Subject
Biology and Life Sciences, Life Sciences
Copyright: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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