V. Langraf, A. Svoradová, K. Petrovičová, V. Brygadyrenko
{"title":"Structure of data in cell biology research","authors":"V. Langraf, A. Svoradová, K. Petrovičová, V. Brygadyrenko","doi":"10.15421/10.15421/022370","DOIUrl":null,"url":null,"abstract":"Bioinformatics is a scientific field on the border between informatics and biology where problems in the field of biology are solved using statistical methods. Another part of it are database systems which serve to store data necessary for meta-analysis. In recent years, there has been a boom mainly thanks to enabling technologies that make it possible to obtain big data about the functioning of living cells of organisms. Bioinformatics tools are necessary to process these data and form an integral part of research in modern biological and medical sciences. Scientific research focused on molecular biology, as well as medicine, is increasingly focusing on data storage. It is understood that the correct structure of the database is important for the correct interpretation of the results of their research activities. For communication between tables in the database, it is essential to set the data type, assign Primary key and Foreign key, ensure data integrity, remove data plurality and understand the research logic. Based on these needs, we created a relational database using SQL Server 2017 and Microsoft SQL Server Management Studio 2017 (SSMS). We created the source code for programming the database and filling it with data in Structured Query Language (SQL) and T-SQL on the Microsoft platform. Of the data types, we used float for numbers with a floating decimal line, integer values were assigned an integer (int), date had a date data type, and text strings had a defined nvarchar data type. Our results bring new information in the field of bioinformatics about the creation of a database structure for data storage in cell biology research. These new insights will help big data in meta-analyses of data and applying scientific results to medical and scientific practice. The database will store data obtained in real time, which will ensure relevance in pointing out biological trends, regularities, relationships and links between cellular structures. All these aspects are very important for the spatial modeling of data and the creation of models of interactions of cell structures with use for applications in medical and biological practice.","PeriodicalId":21094,"journal":{"name":"Regulatory Mechanisms in Biosystems","volume":"39 1","pages":""},"PeriodicalIF":0.5000,"publicationDate":"2023-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Regulatory Mechanisms in Biosystems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.15421/10.15421/022370","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"BIOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
Bioinformatics is a scientific field on the border between informatics and biology where problems in the field of biology are solved using statistical methods. Another part of it are database systems which serve to store data necessary for meta-analysis. In recent years, there has been a boom mainly thanks to enabling technologies that make it possible to obtain big data about the functioning of living cells of organisms. Bioinformatics tools are necessary to process these data and form an integral part of research in modern biological and medical sciences. Scientific research focused on molecular biology, as well as medicine, is increasingly focusing on data storage. It is understood that the correct structure of the database is important for the correct interpretation of the results of their research activities. For communication between tables in the database, it is essential to set the data type, assign Primary key and Foreign key, ensure data integrity, remove data plurality and understand the research logic. Based on these needs, we created a relational database using SQL Server 2017 and Microsoft SQL Server Management Studio 2017 (SSMS). We created the source code for programming the database and filling it with data in Structured Query Language (SQL) and T-SQL on the Microsoft platform. Of the data types, we used float for numbers with a floating decimal line, integer values were assigned an integer (int), date had a date data type, and text strings had a defined nvarchar data type. Our results bring new information in the field of bioinformatics about the creation of a database structure for data storage in cell biology research. These new insights will help big data in meta-analyses of data and applying scientific results to medical and scientific practice. The database will store data obtained in real time, which will ensure relevance in pointing out biological trends, regularities, relationships and links between cellular structures. All these aspects are very important for the spatial modeling of data and the creation of models of interactions of cell structures with use for applications in medical and biological practice.
生物信息学是介于信息学和生物学之间的一个科学领域,在这一领域中,生物学领域的问题通过统计方法得以解决。它的另一部分是数据库系统,用于存储元分析所需的数据。近年来,生物信息学的蓬勃发展主要归功于使获取生物活细胞功能大数据成为可能的使能技术。生物信息学工具是处理这些数据的必要手段,也是现代生物和医学研究不可或缺的一部分。以分子生物学和医学为重点的科学研究越来越重视数据存储。据了解,数据库的正确结构对于正确解释其研究活动的结果非常重要。为了实现数据库表之间的通信,必须设置数据类型、分配主键和外键、确保数据完整性、消除数据多重性并了解研究逻辑。根据这些需求,我们使用 SQL Server 2017 和 Microsoft SQL Server Management Studio 2017(SSMS)创建了一个关系数据库。我们在微软平台上使用结构化查询语言(SQL)和 T-SQL 创建了源代码,用于对数据库进行编程并填充数据。在数据类型中,我们对带有浮动小数行的数字使用了 float,对整数值分配了整数(int),对日期使用了日期数据类型,对文本字符串使用了定义好的 nvarchar 数据类型。我们的研究结果为生物信息学领域带来了新的信息,即在细胞生物学研究中创建用于数据存储的数据库结构。这些新见解将有助于大数据的数据荟萃分析,并将科学成果应用于医疗和科学实践。数据库将存储实时获得的数据,这将确保在指出生物学趋势、规律性、细胞结构之间的关系和联系方面的相关性。所有这些方面对于数据的空间建模和细胞结构相互作用模型的创建都非常重要,可用于医学和生物学实践。