{"title":"所有遗传密码的关系模型。","authors":"Nikola Štambuk , Paško Konjevoda , Albert Štambuk","doi":"10.1016/j.biosystems.2025.105600","DOIUrl":null,"url":null,"abstract":"<div><div>The most common way to display the rules of all genetic codes is the Standard Genetic Code (SGC) table and its variants. This article takes an alternative approach to the genetic code table based on the relational model (Konjevoda and Štambuk, 2021). The relational model (RM) proposes distributed storage of the data into a collection of tables, which are called relations. Basic elements of the SGC table are rows (called records or tuples) and columns (called attributes). The SGC table, according to the RM, represents the so-called unnormalized form of a table, and it can be decomposed or divided into 4 tables using a set of rules called normal forms. The rows and columns of a single table are defined by the first and second base, and individual tables are specified by the third codon base. The result of this model is an approach to managing genetic code data, represented in terms of tuples and grouped into relations, with table structure and language consistent with the first-order logic, and sixteen truth functions defined by IUPAC ambiguity codes for incomplete nucleic acid specification. It is concluded that the relational model is a suitable method to display the rules of the Standard Genetic Code and its 28 variants according to Marcello Barbieri's concepts of ambiguity reduction and codepoiesis.</div></div>","PeriodicalId":50730,"journal":{"name":"Biosystems","volume":"257 ","pages":"Article 105600"},"PeriodicalIF":1.9000,"publicationDate":"2025-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Relational model of all genetic codes\",\"authors\":\"Nikola Štambuk , Paško Konjevoda , Albert Štambuk\",\"doi\":\"10.1016/j.biosystems.2025.105600\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>The most common way to display the rules of all genetic codes is the Standard Genetic Code (SGC) table and its variants. This article takes an alternative approach to the genetic code table based on the relational model (Konjevoda and Štambuk, 2021). The relational model (RM) proposes distributed storage of the data into a collection of tables, which are called relations. Basic elements of the SGC table are rows (called records or tuples) and columns (called attributes). The SGC table, according to the RM, represents the so-called unnormalized form of a table, and it can be decomposed or divided into 4 tables using a set of rules called normal forms. The rows and columns of a single table are defined by the first and second base, and individual tables are specified by the third codon base. The result of this model is an approach to managing genetic code data, represented in terms of tuples and grouped into relations, with table structure and language consistent with the first-order logic, and sixteen truth functions defined by IUPAC ambiguity codes for incomplete nucleic acid specification. It is concluded that the relational model is a suitable method to display the rules of the Standard Genetic Code and its 28 variants according to Marcello Barbieri's concepts of ambiguity reduction and codepoiesis.</div></div>\",\"PeriodicalId\":50730,\"journal\":{\"name\":\"Biosystems\",\"volume\":\"257 \",\"pages\":\"Article 105600\"},\"PeriodicalIF\":1.9000,\"publicationDate\":\"2025-09-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Biosystems\",\"FirstCategoryId\":\"99\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0303264725002102\",\"RegionNum\":4,\"RegionCategory\":\"生物学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"BIOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Biosystems","FirstCategoryId":"99","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0303264725002102","RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"BIOLOGY","Score":null,"Total":0}
The most common way to display the rules of all genetic codes is the Standard Genetic Code (SGC) table and its variants. This article takes an alternative approach to the genetic code table based on the relational model (Konjevoda and Štambuk, 2021). The relational model (RM) proposes distributed storage of the data into a collection of tables, which are called relations. Basic elements of the SGC table are rows (called records or tuples) and columns (called attributes). The SGC table, according to the RM, represents the so-called unnormalized form of a table, and it can be decomposed or divided into 4 tables using a set of rules called normal forms. The rows and columns of a single table are defined by the first and second base, and individual tables are specified by the third codon base. The result of this model is an approach to managing genetic code data, represented in terms of tuples and grouped into relations, with table structure and language consistent with the first-order logic, and sixteen truth functions defined by IUPAC ambiguity codes for incomplete nucleic acid specification. It is concluded that the relational model is a suitable method to display the rules of the Standard Genetic Code and its 28 variants according to Marcello Barbieri's concepts of ambiguity reduction and codepoiesis.
期刊介绍:
BioSystems encourages experimental, computational, and theoretical articles that link biology, evolutionary thinking, and the information processing sciences. The link areas form a circle that encompasses the fundamental nature of biological information processing, computational modeling of complex biological systems, evolutionary models of computation, the application of biological principles to the design of novel computing systems, and the use of biomolecular materials to synthesize artificial systems that capture essential principles of natural biological information processing.