Quantitative Biology

2001 Submissions

[2] viXra:2001.0165 [pdf] submitted on 2020-01-09 10:54:09

Studies on Protein Synthesis Within a Theoretical Model

Authors: Tumpa Saha, Biplab Chattopadhyay
Comments: 11 pages, 3 figures, published in IOSR Journal Of Pharmacy And Biological Sciences (IOSR-JPBS), Volume 14, Issue 5 Ser. II (2019), PP. 10-20

Synthesis of proteins through the phenomenological pathway of transcription and translation, that constitutes the central dogma, has been explored theoretically. Emphasizing the closed-cycle character of the phenomenon, a prototype of the same is framed in mathematical terms with the biological inputs from allied literature. The mathematical prototype is actually a set of three coupled time differential equations signifying time rate of change of DNA, RNA and protein densities occurring in the biological cells of eukaryotes. The prototype has been scrutinized by well-set mathematical tools in regard of its sustainability under detailed stability tests. To judge exact behavioural pattern of the prototype solutions, rigorous numerical simulations of the time differential equations are carried out. Analyses of numerical simulation results with various changing parameters lead to predictive conclusions about different regulatory mechanisms existing in the protein synthesis phenomenology. Some future research directions are indicated too.
Category: Quantitative Biology

[1] viXra:2001.0055 [pdf] submitted on 2020-01-04 12:21:58

Analogy Inspired Biology

Authors: Prashanth R. Rao
Comments: 1 Page.

In this hypothesis paper, we identify a potential biological principle purely inspired by real life analogy. It is most likely that real examples in biology, disease, and pharmacology exist for this principle and have already been identified. The principle suggests how in an attempt to restore the level of a biological processes at one location or one instance, organisms/living systems may unintentionally end up dysregulating the process at another location or instance.
Category: Quantitative Biology