An extension of Shannon’s entropy to explain taxa diversity and human diseases
| Autor: | Farzin Kamari, Sina Dadmand |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
Entropy (classical thermodynamics)
Taxon Theoretical computer science Computer science Entropy (statistical thermodynamics) Entropy (information theory) Mutual information Entropy (energy dispersal) Information theory Protein network Mathematical theorem Entropy (arrow of time) Entropy (order and disorder) |
| DOI: | 10.1101/2020.08.03.233767 |
| Popis: | In this study, with the use of the information theory, we have proposed and proved a mathematical theorem by which we argue the reason for the existence of human diseases. To introduce our theoretical frame of reference, first, we put forward a modification of Shannon’s entropy, computed for all available proteomes, as a tool to compare systems complexity and distinguish between the several levels of biological organizations. We establish a new approach, namely the wave of life, to differentiate several taxa and corroborate our findings through the latest tree of life. Furthermore, we found that human proteins with higher mutual information, derived from our theorem, are more prone to be involved in human diseases. Our results illuminate the dynamics of protein network stability and offer probable scenarios for the existence of human diseases and their varying occurrence rates. The current study presents the fundamentals in understanding human diseases by means of information theory. In practice, the theorem proposes multiple-protein approach as therapeutic agents targeting protein networks as a whole, rather than approaching a single receptor. |
| Databáze: | OpenAIRE |
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