ArticleDatabase : the journal of biological databases and curation2021
Development of a biomarker database toward performing disease classification and finding disease interrelations.
Article in Database : the journal of biological databases and curation, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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4 citing papers in PubMed, 3 citations in OpenAlex.
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- Bioinformatics-led identification of pathophysiological hallmark genes in diabesotension via graph clustering method.Journal of diabetes and metabolic disorders · 2025Article
- Circulating microRNAs as the Potential Diagnostic and Prognostic Biomarkers for Nasopharyngeal Carcinoma.Genes · 2022Review
- A system biology approach based on metabolic biomarkers and protein-protein interactions for identifying pathways underlying schizophrenia and bipolar disorder.Scientific reports · 2021Article
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Authors and funding
6 authors at 1 institution in 1 country.
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No grant is acknowledged in the PubMed record.
Abstract
A biomarker is a measurable indicator of a disease or abnormal state of a body that plays an important role in disease diagnosis, prognosis and treatment. The biomarker has become a significant topic due to its versatile usage in the medical field and in rapid detection of the presence or severity of some diseases. The volume of biomarker data is rapidly increasing and the identified data are scattered. To provide comprehensive information, the explosively growing data need to be recorded in a single platform. There is no open-source freely available comprehensive online biomarker database. To fulfill this purpose, we have developed a human biomarker database as part of the KNApSAcK family databases which contain a vast quantity of information on the relationships between biomarkers and diseases. We have classified the diseases into 18 disease classes, mostly according to the National Center for Biotechnology Information definitions. Apart from this database development, we also have performed disease classification by separately using protein and metabolite biomarkers based on the network clustering algorithm DPClusO and hierarchical clustering. Finally, we reached a conclusion about the relationships among the disease classes. The human biomarker database can be accessed online and the inter-disease relationships may be helpful in understanding the molecular mechanisms of diseases. To our knowledge, this is one of the first approaches to classify diseases based on biomarkers. Database URL: http://www.knapsackfamily.com/Biomarker/top.php.
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