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/>.
Highlights
The advent of sequencing technologies has motivated the development of public databases initiatives
There has been an exponential growth in generation of biological data, and these require information technology tools to store, organize and analyze biological data that is available in the form of raw data, annotated sequences, tables, and other archive files generated by omics technologies (Toomula et al, 2012)
We reviewed the databases from two platforms of multi-omic data: Biotools: Bioinformatics Tools and Services Discovery Portal (Ison et al, 2013, ) and OMICtools: an informative directory for multi-omic data analysis (Henry et al, 2014, )
Summary
The advent of sequencing technologies has motivated the development of public databases initiatives. There has been an exponential growth in generation of biological data, and these require information technology tools to store, organize and analyze biological data that is available in the form of raw data, annotated sequences, tables, and other archive files generated by omics technologies (Toomula et al, 2012). The first reported biological database was a protein sequence database developed by Margaret Dayhoff in 1965. She created the first substitution matrix for point accepted mutations (PAM) and the one-letter code for amino acids (Strasser, 2012). In the early 1980s, the EMBL Data Library Ac.uk/ena>) created a catalog of published biological data.
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