ABSTRACT
The laminin (LM)-database, hosted at http://www.lm.lncc.br, was published in the NAR database 2011 edition. It was the first database that provided comprehensive information concerning a non-collagenous family of extracellular matrix proteins, the LMs. In its first version, this database contained a large amount of information concerning LMs related to health and disease, with particular emphasis on the haemopoietic system. Users can easily access several tabs for LMs and LM-related molecules, as well as LM nomenclatures and direct links to PubMed. The LM-database version 2.0 integrates data from several publications to achieve a more comprehensive knowledge of LMs in health and disease. The novel features include the addition of two new tabs, 'Neuromuscular Disorders' and 'miRNA--LM Relationship'. More specifically, in this updated version, an expanding set of data has been displayed concerning the role of LMs in neuromuscular and neurodegenerative diseases, as well as the putative involvement of microRNAs. Given the importance of LMs in several biological processes, such as cell adhesion, proliferation, differentiation, migration and cell death, this upgraded version expands for users a panoply of information, regarding complex molecular circuitries that involve LMs in health and disease, including neuromuscular and neurodegenerative disorders.
Subject(s)
Databases, Protein , Laminin/metabolism , Neuromuscular Diseases/metabolism , Animals , Humans , Internet , Mice , MicroRNAs/metabolism , Neurodegenerative Diseases/genetics , Neurodegenerative Diseases/metabolism , RatsABSTRACT
Object-oriented programming (OOP) embodies a software development paradigm grounded in representing real-world entities as objects, facilitating a more efficient and structured modelling approach. In this article, we explore the synergy between OOP principles and the TypeScript (TS) programming language to create a JSON-formatted database designed for storing arrays of biological features. This fusion of technologies fosters a controlled and modular code script, streamlining the integration, manipulation, expansion, and analysis of biological data, all while enhancing syntax for improved human readability, such as through the use of dot notation. We advocate for biologists to embrace Git technology, akin to the practices of programmers and coders, for initiating versioned and collaborative projects. Leveraging the widely accessible and acclaimed IDE, Visual Studio Code, provides an additional advantage. Not only does it support running a Node.js environment, which is essential for running TS, but it also efficiently manages GitHub versioning. We provide a use case involving taxonomic data structure, focusing on angiosperm legume plants. This method is characterized by its simplicity, as the tools employed are both fully accessible and free of charge, and it is widely adopted by communities of professional programmers. Moreover, we are dedicated to facilitating practical implementation and comprehension through a comprehensive tutorial, a readily available pre-built database at GitHub, and a new package at npm.