SalivaDB-a Comprehensive Database for Salivary Biomarkers in Humans

Overview

Journal Database (Oxford)

Specialty Biology

Date 2023 Feb 7

PMID 36747479

Authors

Akanksha Arora

Dashleen Kaur

Sumeet Patiyal

Dilraj Kaur

Ritu Tomer

Gajendra P S Raghava

Affiliations

Soon will be listed here.

Abstract

Saliva as a non-invasive diagnostic fluid has immense potential as a tool for early diagnosis and prognosis of patients. The information about salivary biomarkers is broadly scattered across various resources and research papers. It is important to bring together all the information on salivary biomarkers to a single platform. This will accelerate research and development in non-invasive diagnosis and prognosis of complex diseases. We collected widespread information on five types of salivary biomarkers-proteins, metabolites, microbes, micro-ribonucleic acid (miRNA) and genes found in humans. This information was collected from different resources that include PubMed, the Human Metabolome Database and SalivaTecDB. Our database SalivaDB contains a total of 15 821 entries for 201 different diseases and 48 disease categories. These entries can be classified into five categories based on the type of biomolecules; 6067, 3987, 2909, 2272 and 586 entries belong to proteins, metabolites, microbes, miRNAs and genes, respectively. The information maintained in this database includes analysis methods, associated diseases, biomarker type, regulation status, exosomal origin, fold change and sequence. The entries are linked to relevant biological databases to provide users with comprehensive information. We developed a web-based interface that provides a wide range of options like browse, keyword search and advanced search. In addition, a similarity search module has been integrated which allows users to perform a similarity search using Basic Local Alignment Search Tool and Smith-Waterman algorithm against biomarker sequences in SalivaDB. We created a web-based database-SalivaDB, which provides information about salivary biomarkers found in humans. A wide range of web-based facilities have been integrated to provide services to the scientific community. https://webs.iiitd.edu.in/raghava/salivadb/.

Citing Articles

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PMID: 37850638 PMC: 10767989. DOI: 10.1093/nar/gkad862.

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