| Chapter title |
Integrating Bio-ontologies and Controlled Clinical Terminologies: From Base Pairs to Bedside Phenotypes
|
|---|---|
| Chapter number | 20 |
| Book title |
The Gene Ontology Handbook
|
| Published in |
Methods in molecular biology, January 2017
|
| DOI | 10.1007/978-1-4939-3743-1_20 |
| Pubmed ID | |
| Book ISBNs |
978-1-4939-3741-7, 978-1-4939-3743-1
|
| Authors |
Spiros C. Denaxas |
| Editors |
Christophe Dessimoz, Nives Škunca |
| Abstract |
Electronic Health Records (EHR) are inherently complex and diverse and cannot be readily integrated and analyzed. Analogous to the Gene Ontology, controlled clinical terminologies were created to facilitate the standardization and integration of medical concepts and knowledge and enable their subsequent use for translational research, official statistics and medical billing. This chapter will introduce several of the main controlled clinical terminologies used to record diagnoses, surgical procedures, laboratory results and medications. The discovery of novel therapeutic agents and treatments for rare or common diseases increasingly requires the integration of genotypic and phenotypic knowledge across different biomedical data sources. Mechanisms that facilitate this linkage, such as the Human Phenotype Ontology, are also discussed. |
Mendeley readers
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Mexico | 1 | 4% |
| Unknown | 24 | 96% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 10 | 40% |
| Student > Ph. D. Student | 5 | 20% |
| Student > Master | 3 | 12% |
| Librarian | 2 | 8% |
| Other | 1 | 4% |
| Other | 2 | 8% |
| Unknown | 2 | 8% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 7 | 28% |
| Agricultural and Biological Sciences | 4 | 16% |
| Computer Science | 4 | 16% |
| Biochemistry, Genetics and Molecular Biology | 3 | 12% |
| Mathematics | 1 | 4% |
| Other | 2 | 8% |
| Unknown | 4 | 16% |