ArticleDatabase : the journal of biological databases and curation2023
SalivaDB-a comprehensive database for salivary biomarkers in humans.
Article in Database : the journal of biological databases and curation, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed, 15 citations in OpenAlex.
- The Oral and Nasal Gateway Microbiomes: Salivaomics and Systemic Health at the Airway-Digestive Interface.Microorganisms · 2026Review
- Effects of extreme mountain ultramarathon on stress-related biomarkers from multiple biological matrices in adult male runners.Physiological reports · 2026Article
- Artificial Intelligence-Based Wearable Sensing Technologies for the Management of Cancer, Diabetes, and COVID-19.Biosensors · 2025Review
- A comprehensive experimental comparison between federated and centralized learning.Database : the journal of biological databases and curation · 2025Article
- TheMarker: a comprehensive database of therapeutic biomarkers.Nucleic acids research · 2024Article
Corrections and comments
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Authors and funding
6 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
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/.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.