Fantastic databases and where to find them: Web applications for researchers in a rush |
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Authors: | Gerda Cristal Villalba Ursula Matte |
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Institution: | 1.Hospital de Clínicas de Porto Alegre, Laboratório de células, tecidos e genes, Porto Alegre, RS, Brazil.; 2.Universidade Federal do Rio Grande do Sul, Programa de Pós-Graduação em Genética e Biologia Molecular, Porto Alegre, RS, Brazil.; 3.Hospital de Clínicas de Porto Alegre, Bioinformatics Core, Porto Alegre, RS, Brazil.; 4.Universidade Federal do Rio Grande do Sul, Departamento de Genética, Porto Alegre, RS, Brazil. |
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Abstract: | Public databases are essential to the development of multi-omics resources. The amount of data created by biological technologies needs a systematic and organized form of storage, that can quickly be accessed, and managed. This is the objective of a biological database. Here, we present an overview of human databases with web applications. The databases and tools allow the search of biological sequences, genes and genomes, gene expression patterns, epigenetic variation, protein-protein interactions, variant frequency, regulatory elements, and comparative analysis between human and model organisms. Our goal is to provide an opportunity for exploring large datasets and analyzing the data for users with little or no programming skills. Public user-friendly web-based databases facilitate data mining and the search for information applicable to healthcare professionals. Besides, biological databases are essential to improve biomedical search sensitivity and efficiency and merge multiple datasets needed to share data and build global initiatives for the diagnosis, prognosis, and discovery of new treatments for genetic diseases. To show the databases at work, we present a a case study using ACE2 as example of a gene to be investigated. The analysis and the complete list of databases is available in the following website <https://kur1sutaru.github.io/fantastic_databases_and_where_to_find_them/>. |
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Keywords: | Human databases bioinformatics tools web application data mining big data |
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