BIOINTMED: integrated biomedical knowledge base with ontologies and clinical trials

• Published in: Medical & biological engineering & computing Vol. 58; no. 10; pp. 2339 - 2354
• Main Authors: Saha, Ankita, Mukhopadhyay, Jayanta, Sarkar, Sudeshna, Gattu, Mahanandeeshwar
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.10.2020; Springer Nature B.V
• Subjects: Biomedical and Life Sciences; Biomedical data; Biomedical Engineering and Bioengineering; Biomedicine; Clinical trials; Computer Applications; Human Physiology; Imaging; Knowledge bases (artificial intelligence); Original Article; Radiology; Statistical analysis; Clinical trials; Dictionaries; Biomedical integrated system; Data integration; Biomedical knowledge base
• ISSN: 0140-0118; 1741-0444
• DOI: 10.1007/s11517-020-02201-0

Biomedical data are complex and heterogeneous. An ample reliable quantity of data is important for understanding and exploring the domain. The work aims to integrate biomedical data from various heterogeneous sources like dictionaries or corpus and amalgamate them into a uniform format for easier access by the end-user like biologist, pharmacist, and data scientist. The proposed integrated biomedical knowledge base, BIOINTMED, has 11,299, 12,981, 4428, 61,491, 48,663, and 13,146 unique entities for drugs, diseases, targets, genes, biomedical pathways, and adverse events, respectively. The uniform aggregated collection is also explored to study the interaction among these entity pairs. Finally, a complete statistical analysis of the consolidated biomedical entities is provided.