A relational database of protein structures designed for flexible enquiries about conformation.

Structured Query Language (SQL) is commonly used in Relational Database Management Systems (RDBMS) and is currently one of the most popular data definition and manipulation languages. Its core functionality is implemented, with only some minor variations, throughout all RDBMS products. It is an effective tool in the process of managing and querying data in relational databases. This paper describes a method to effectively automate the conversion of a data query from a Natural Language Query (NLQ) to Structured Query Language (SQL) with Online Analytical Processing (OLAP) cube data warehouse objects. To obtain or manipulate the data from relational databases, the user must be familiar with SQL and must also write an appropriate and valid SQL statement. However, users who are not familiar with SQL are unable to obtain relevant data through relational databases. To address this, we propose a Natural Language Processing (NLP) model to convert an NLQ into an SQL query. This allows novice users to obtain the required data without having to know any complicated SQL details. The model is also capable of handling complex queries using the OLAP cube technique, which allows data to be pre-calculated and stored in a multi-dimensional and ready-to-use format. A multi-dimensional cube (hypercube) is used to connect with the NLP interface, thereby eliminating long-running data queries and enabling self-service business intelligence. The study demonstrated how the use of hypercube technology helps to increase the system response speed and the ability to process very complex query sentences. The system achieved impressive performance in terms of NLP and the accuracy of generating different query sentences. Using OLAP hypercube technology, the study achieved distinguished results compared to previous studies in terms of the speed of the response of the model to NLQ analysis, the generation of complex SQL statements, and the dynamic display of the results. As a plan for future work, it is recommended to use infinite-dimension (n-D) cubes instead of 4-D cubes to enable ingesting as much data as possible in a single object and to facilitate the execution of query statements that may be too complex in query interfaces running in a data warehouse. The study demonstrated how the use of hypercube technology helps to increase system response speed and process very complex query sentences.

Enzymes are the same biomolecules such as proteins, has only a functional difference. Enzymes are bio catalyst that recently applied to many industrial fields. To be applied in the field of industrial enzymes should be enhanced stability against temperature. Analysis of the salt bridge is able to demonstrate the potential of residues mutated to improve thermal stability. Molecular dynamics simulations performed by observing the unfolding process. Variations in temperature used is 400 K, 450 K and 500 K, respectively performed for 2.5 ns. Then analyzed the pair a salt bridge is formed. There are 25 pairs of salt bridges at a temperature of 400 K, 24 pairs of salt bridges at a temperature of 450 K, and there are 30 pairs of the salt bridge is formed at a temperature of 500 K. To determine the salt bridge partner is a key enzyme kesstabilan we then plotted salt bridge between distances (A ) with time (ns) only at a temperature of 500 K, for allegedly at these temperatures has been a process of unfolding. Of the 30 pairs of the salt bridge that had plotted the distance with time, the pair obtained a salt bridge that pattern similar to the pattern chart graph analysis Root-mean-square deviation (RMSD). There are three curves salt bridge that pattern is similar to the pattern of RMSD curve and SASA, namely the salt bridge Glu84-Arg134, Asp104-Arg134 and Asp113-Arg115. The sharp rise in the value of RMSD and the resulting rupture SASA three pairs of the salt bridges. So when carried mutations in-silico candidate mutants that will be transferred is the amino acid residues are thought to play a role in electrostatic interactions and replace it with another amino acid residue on the basis of structural similarities. Keywords : Salt bridge, Electrostatic bond, Mutation, Unfolding

Chapter 2 - Querying

Biodiversity data exchange depends on established standards, such as Darwin Core, Audiovisual Core, Taxon Concept Schema, etc. Standards provide terms with defined semantic meaning and structures for data exchange. Standards simplify interchange of biodiversity data among government agencies, researchers, and engineers. A notable challenge during such data transfers is the complexity involved in processing data for various uses. Most data exchanges are performed via Comma Separated Value (CSV), Extensible Markup Language (XML), or JavaScript Object Notation (JSON), and need to be parsed and imported into a database before being queryable. For example, to explore the data in a Darwin Core Archive zipped file, it is necessary to decompress it, parse XML-based metadata about the content of the file, parse and read Ecological Metadata Language (EML) to extract provenance metadata, and correctly open the text-delimited files that use a wide variety of character encodings, delimiters, enclosures, and escape characters. All of it requires non-trivial data management and programming skills from users. We propose a paradigm shift toward using queryable SQLite-based files for more straightforward data interchange. This approach would reduce friction in data processing by directly using Structured Query Language (SQL). SQLite is an open source, high performance, lightweight database already installed on most computers (SQLite 2024). It integrates a database into a single file, facilitating straightforward data exchange and compression. Its robust engine is able to manage terabytes of data. The SQLite developers are committed to maintaining backward compatibility of both binary and SQL text file versions until 2050 (SQLite 2024). Connectivity to SQLite databases is supported by all popular programming languages. Furthermore, the United States Library of Congress endorses SQLite alongside XML and JSON for data archives, attesting to its long-term reliability (United States Library of Congress 2024). We at the Species File Group are experimenting with using SQLite to create a universal data converter, in which an SQLite database serves as an intermediate data storage format. This provides several useful advantages: 1. Universal data converter By learning a standard SQL schema for biodiversity data, users are able to efficiently write importers and exporters to/from the intermediate schema for a variety of other biodiversity data-exchange formats. Any programming language can be used to develop the conversion scripts. Import and export are completely decoupled from each other, allowing mixing and matching of converters in a flexible way. For example, we aim to use SQLite as an intermediary archive to convert data between Darwin Core Archives, Catalogue of Life Data Package (ColDP), Global Names Verifier, and TaxonWorks (Fig. 1). 2. Semantic versioning of the archive Like any other data format, the intermediate data exchange SQLite schema will evolve over time. Using Git tags and branches, it is straightforward to follow a semantic versioning paradigm (Semantic Versioning 2024). For example, in "v1.2.5" the numbers respectively indicate major, minor, and patch versions. Major versions include substantial changes that might not be backwards compatible, while minor versions are backwards compatible and patch versions indicate tiny bug fixes. 3. Data querying With SQLite-based archives being relational databases, they can immediately be queried without any additional parsing and importing. This allows the archives to be explored with ease by anyone familiar with SQL. The Carpentries also provide online learning resources and courses for researchers to learn SQLite (Martinez and Poisot 2017). 4. Biodiversity application development As SQLite-based archives are relational databases, and the intermediate data exchange schema is standardized and stable, a database file can be used directly by a variety of applications. For example, it would be possible to develop a web application frontend that utilizes the SQLite archive as a backend. It could be possible to develop an ecosystem of biodiversity informatics applications based on SQLite archives. We believe that adopting SQLite for biodiversity data exchange can reduce operational friction, enhance data accessibility, and promise a streamlined and universally compatible data management framework.

3D protein structure similarity searching is one of the most popular processes performed in the structural bioinformatics. The process is usually performed through dedicated websites or desktop software tools, which makes a secondary processing of the search results difficult. One of the alternatives is to store macromolecular data in relational databases and perform the similarity searching on the server-side of the client-server architecture. Unfortunately, relational database management systems (DBMSs) are not designed for efficient storage and processing of biological data, such as 3D protein structures. In this paper, we present the P3D-SQL extension to the Oracle PL/SQL language that allows invoking protein similarity searching in SQL queries and perform the process efficiently against a database of 3D protein structures. Availability: P3D-SQL is available from P3D-SQL project home page at: http://zti.polsl.pl/w3/dmrozek/science/p3dsql.htm

It is noted that, even though SQL (structured query language) was invented in 1974, it did not become a standard until late 1986. Between 1974 and 1986, many vendors developed relational database systems based on the SQL language. Thus, even though many vendors support the SQL language, the implementations are not necessarily compatible because they were developed before an official standard was available. Additionally, users are requesting connectivity between relational databases on personal computers, minicomputers, and mainframe computers. The steps that are being taken by the DEC SQL Access Group to solve these problems are described. >

A systematic study of helix-helix packing in a comprehensive database of protein structures revealed that the side chains inside helix-helix interfaces on average are shorter than those in the noninterface parts of the helices. The study follows our earlier study of this effect in transmembrane helices. The results obtained on the entire database of protein structures are consistent with those obtained on the transmembrane helices. The difference in the length of interface and noninterface side chains is small but statistically significant. It indicates that helices, if viewed along their main axis, statistically are not circular, but have a flattened interface. This effect brings the helices closer to each other and creates a tighter structural packing. The results provide an interesting insight into the aspects of protein structure and folding.

Many types of maritime incident databases have been established that allow people to learn from past incidents and develop corresponding mitigation measures. However, our investigation of multiple international and national databases shows that most existing databases only record basic information regarding incidents in a single table. Lots of useful information is not included in the database (i.e., limited extension of the database). Meanwhile, some basic information is recorded tautologically (i.e., data redundancy). In this paper, two widely used databases are taken as examples, the Global Integrated Shipping Information System and the Lloyd's List Intelligence, to explain these common problems of existing databases. To overcome these limitations and improve the efficiency of data maintenance, this paper develops a relational maritime safety management database. The entity-relationship model is first used to depict the inter-related semantic information surrounding maritime incidents, and a relational database model is subsequently formed. Microsoft Access is employed to implement the proposed database, and a database application is also designed to demonstrate the utility of the database. Our preliminary study shows that the proposed database is implementable and has potential usage for both industry and academic research.

A Web-Based Perioperative Dashboard as a Platform for Anesthesia Informatics Innovation.

We present a method (ENERGI) for extracting energy-like quantities from a data base of protein structures. In this paper, we use the method to generate pairwise additive amino acid "energy" scores. These scores are obtained by iteration until they correctly discriminate a set of known protein folds from decoy conformations. The method succeeds in lattice model tests and in the gapless threading problem as defined by Maiorov and Crippen [Maiorov, V. N. & Crippen, G. M. (1992) J. Mol. Biol. 227, 876-888]. A more challenging test of threading a larger set of test proteins derived from the representative set of Hobohm and Sander [Hobohm, U. & Sander, C. (1994) Protein Sci. 3, 522-524] is used as a "workbench" for exploring how the ENERGI scores depend on their parameter sets.

In recent past, the bookstores generate more data such as customer details, transaction details, book details, etc. for analyzing them to make data-driven decisions. These data are stored in a centralized database. In centralized database system, the data are stored in a single site or location and that are managed. The major drawback is that if the centralized system gets crashed the entire data are lost and also it makes access bottleneck when more users need to access the database. In order to overcome these limitations, the distributed database system is used to store the business data by locating them in different databases that are located in different sites in different location. The distributed database maintains the replication and duplication that ensure the availability and fault tolerance on the data. The distributed system also provides the high accessibility to the users. Thus, this paper presents a distributed database for a bookstore to improve availability, fault tolerance, and accessibility. This distribution also maintains the transparency and supports the database properties such as atomicity, consistency, inheritance and durability (ACID). Furthermore, this distributed database is designed with four sites and each site keeps the bookstore data for access and analyses. This distributed database is constructed and accessed using structured query language (SQL) with MySQL relational database management system (RDBMS). It also provides the security and work even in offline mode. Keywords: distributed databases; query processing; relational database management; structured query language; bookstore database;

Structures of a transition metal transporter spanning the entire Mn2+ transport cycle reveal distinct coordination geometries and dynamic polar networks that enable Mn2+ import, and a Cd2+-bound structure helps explain how Cd2+ behaves differently as a substrate.

Today, relational databases are widely used in information systems. SQL (structured query language) is taught extensively in universities and professional schools across the globe as a programming language for its data management and accesses. Previously, we have studied a web-based programming learning assistant system (PLAS) to help novice students learn popular programming languages by themselves through solving various types of exercises. For SQL programming, we have implemented the grammar-concept understanding problem (GUP) and the comment insertion problem (CIP) for its initial studies. In this paper, we propose an SQL Query Description Problem (SDP) as a new exercise type for describing the SQL query to a specified request in a MySQL database system. To reduce teachers’ preparation workloads, we integrate a generative AI-assisted SQL query generator to automatically generate a new SDP instance with a given dataset. An SDP instance consists of a table, a set of questions and corresponding queries. Answer correctness is determined by enhanced string matching against an answer module that includes multiple semantically equivalent canonical queries. For evaluation, we generated 11 SDP instances on basic topics using the generator, where we found that Gemini 3.0 Pro exhibited higher pedagogical consistency compared to ChatGPT-5.0, achieving perfect scores in Sensibleness, Topicality, and Readiness metrics. Then, we assigned the generated instances to 32 undergraduate students at the Indonesian Institute of Business and Technology (INSTIKI). The results showed an average correct answer rate of 95.2% and a mean SUS score of 78, which demonstrates strong initial student performance and system acceptance.

Background: Relational databases have been a prevalent technology for decades, using SQL (Structured Query Language) to manage data. However, the emergence of new technologies, such as the web and the cloud, has brought the requirement to handle more complex data. NewSQL is the latest technology that incorporates the ability to scale and ensures the availability of NoSQL (Not Only SQL) without losing the ACID properties (Atomicity, Consistency, Isolation, Durability) associated with relational databases. Methods: We evaluated CockroachDB, MariaDB Xpand, and VoltDB with OSSpal methodology and experimentally using the Star Schema Benchmark (SSB). The scalability and performance capabilities of each database were assessed. Results: Applying the OSSpal methodology, the results showed that MariaDB Xpand outperformed CockroachDB and VoltDB. On the other hand, we concluded that with Star Schema Benchmark, CockroachDB had better scalability, while VoltDB had a faster query execution time. Conclusions: CockroachDB and VoltDB are the best performing databases in terms of scalability and performance.

Chapter 3 - SQL