Downloads provided by UsageCounts
pmid: 33188839
The principal objective of this article is a brief overview of the main parts of p-adic mathematics, which have already had valuable applications and may have a significant impact in the near future on the further development of some fields of theoretical and mathematical biology. In particular, we present the basics of ultrametrics, p-adic numbers and p-adic analysis, as well as insight into their applications for modeling some cognitive processes, genetic code and protein dynamics. We also argue that ultrametric concepts and p-adic mathematics are natural tools for the viable description of biological systems and phenomena with a hierarchical structure.
Models, Genetic, Genetic code, Systems Biology, Intelligence, p-adic modeling, Biological information, Protein dynamics, p-adic numbers, Evolution, Molecular, Hierarchical systems, Cognition, Genetic Code, Theoretical biology, Mathematical biology, Ultrametrics, Animals, Humans, Codon, Biological complexity, Algorithms, Mathematics
Models, Genetic, Genetic code, Systems Biology, Intelligence, p-adic modeling, Biological information, Protein dynamics, p-adic numbers, Evolution, Molecular, Hierarchical systems, Cognition, Genetic Code, Theoretical biology, Mathematical biology, Ultrametrics, Animals, Humans, Codon, Biological complexity, Algorithms, Mathematics
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 21 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
| views | 5 | |
| downloads | 1 |

Views provided by UsageCounts
Downloads provided by UsageCounts