Pub Date : 2011-02-22DOI: 10.1038/NPRE.2011.5706.1
E. Keenan, Sarah Warner, A. Crowe, M. Courtney
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Living organisms are the most complex, interesting and significant objects regarding all substructures of the universe. Life science is regarded as a science of the 21st century and one can expect great new discoveries in the near futures. This article contains an introductory brief review of genetic information, its coding and translation of genes to proteins through the genetic code. Some theoretical approaches to the modelling of the genetic code are presented. In particular, connection of the genetic code with number theory is considered and the role of $p$-adic numbers is underlined.
{"title":"Genetic Code and Number Theory","authors":"B. Dragovich","doi":"10.2298/FUPCT1603225D","DOIUrl":"https://doi.org/10.2298/FUPCT1603225D","url":null,"abstract":"Living organisms are the most complex, interesting and significant objects regarding all substructures of the universe. Life science is regarded as a science of the 21st century and one can expect great new discoveries in the near futures. This article contains an introductory brief review of genetic information, its coding and translation of genes to proteins through the genetic code. Some theoretical approaches to the modelling of the genetic code are presented. In particular, connection of the genetic code with number theory is considered and the role of $p$-adic numbers is underlined.","PeriodicalId":8460,"journal":{"name":"arXiv: Other Quantitative Biology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2009-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85404577","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2009-07-21DOI: 10.1142/9789814338998_0006
F. Filatov
The structure of the genetic code is discussed in formal terms. A rectangular table of the code ("the code matrix"), whose properties reveal its arithmetical content tagged with the information symbols in several notations. New parameters used to analyze of the code matrix, the serial numbers of the encoded products and coding elements, ordered by molecular mass. The structural similarity of the amino acid sequences corresponding to two aminoacyl tRNA synthetases classes is found. The code matrix shows how can be organized the so-called second genetic code. The symmetrical pattern of the matrix is supported with the other parameters; it also serves as a basis to construct a 3D model of the genetic code which follows the structure of the simplest Plato solid, tetrahedron. The reasons for this unusual structure of the genetic code remains unclear.
{"title":"A Molecular Mass Gradient is the Key Parameter of the Genetc Code Organization","authors":"F. Filatov","doi":"10.1142/9789814338998_0006","DOIUrl":"https://doi.org/10.1142/9789814338998_0006","url":null,"abstract":"The structure of the genetic code is discussed in formal terms. A rectangular table of the code (\"the code matrix\"), whose properties reveal its arithmetical content tagged with the information symbols in several notations. New parameters used to analyze of the code matrix, the serial numbers of the encoded products and coding elements, ordered by molecular mass. The structural similarity of the amino acid sequences corresponding to two aminoacyl tRNA synthetases classes is found. The code matrix shows how can be organized the so-called second genetic code. The symmetrical pattern of the matrix is supported with the other parameters; it also serves as a basis to construct a 3D model of the genetic code which follows the structure of the simplest Plato solid, tetrahedron. The reasons for this unusual structure of the genetic code remains unclear.","PeriodicalId":8460,"journal":{"name":"arXiv: Other Quantitative Biology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2009-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81471898","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2003-11-03DOI: 10.1201/9781498713917-10
I. Bose, R. Karmakar
We study simple mathematical models of gene expression to explore the possible origins of haploinsufficiency (HI). In a diploid organism, each gene exists in two copies and when one of these is mutated, the amount of proteins synthesized is reduced and may fall below a threshold level for the onset of some desired activity. This can give rise to HI, a manifestation of which is in the form of a disease. We consider both deterministic and stochastic models of gene expression and suggest possible scenarios for the occurrence of HI in the two cases. In the stochastic case, random fluctuations around the mean protein level give rise to a finite probability that the protein level falls below a threshold. Increased gene copy number and faster gene expression kinetics reduce the variance around the mean protein level. The difference between slow and fast gene expression kinetics, as regards response to a signaling gradient, is further pointed out. The majority of results reported in the paper are derived analytically.
{"title":"Mathematical models of haploinsufficiency","authors":"I. Bose, R. Karmakar","doi":"10.1201/9781498713917-10","DOIUrl":"https://doi.org/10.1201/9781498713917-10","url":null,"abstract":"We study simple mathematical models of gene expression to explore the possible origins of haploinsufficiency (HI). In a diploid organism, each gene exists in two copies and when one of these is mutated, the amount of proteins synthesized is reduced and may fall below a threshold level for the onset of some desired activity. This can give rise to HI, a manifestation of which is in the form of a disease. We consider both deterministic and stochastic models of gene expression and suggest possible scenarios for the occurrence of HI in the two cases. In the stochastic case, random fluctuations around the mean protein level give rise to a finite probability that the protein level falls below a threshold. Increased gene copy number and faster gene expression kinetics reduce the variance around the mean protein level. The difference between slow and fast gene expression kinetics, as regards response to a signaling gradient, is further pointed out. The majority of results reported in the paper are derived analytically.","PeriodicalId":8460,"journal":{"name":"arXiv: Other Quantitative Biology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2003-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89206609","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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