| Chapter title |
The Evidence and Conclusion Ontology (ECO): Supporting GO Annotations
|
|---|---|
| Chapter number | 18 |
| Book title |
The Gene Ontology Handbook
|
| Published in |
Methods in molecular biology, January 2017
|
| DOI | 10.1007/978-1-4939-3743-1_18 |
| Pubmed ID | |
| Book ISBNs |
978-1-4939-3741-7, 978-1-4939-3743-1
|
| Authors |
Marcus C. Chibucos, Deborah A. Siegele, James C. Hu, Michelle Giglio, Chibucos, Marcus C., Siegele, Deborah A., Hu, James C., Giglio, Michelle |
| Editors |
Christophe Dessimoz, Nives Škunca |
| Abstract |
The Evidence and Conclusion Ontology (ECO) is a community resource for describing the various types of evidence that are generated during the course of a scientific study and which are typically used to support assertions made by researchers. ECO describes multiple evidence types, including evidence resulting from experimental (i.e., wet lab) techniques, evidence arising from computational methods, statements made by authors (whether or not supported by evidence), and inferences drawn by researchers curating the literature. In addition to summarizing the evidence that supports a particular assertion, ECO also offers a means to document whether a computer or a human performed the process of making the annotation. Incorporating ECO into an annotation system makes it possible to leverage the structure of the ontology such that associated data can be grouped hierarchically, users can select data associated with particular evidence types, and quality control pipelines can be optimized. Today, over 30 resources, including the Gene Ontology, use the Evidence and Conclusion Ontology to represent both evidence and how annotations are made. |
X Demographics
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Mexico | 1 | 5% |
| Spain | 1 | 5% |
| Unknown | 20 | 91% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 7 | 32% |
| Researcher | 6 | 27% |
| Lecturer | 1 | 5% |
| Professor | 1 | 5% |
| Student > Doctoral Student | 1 | 5% |
| Other | 2 | 9% |
| Unknown | 4 | 18% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 7 | 32% |
| Biochemistry, Genetics and Molecular Biology | 6 | 27% |
| Computer Science | 2 | 9% |
| Mathematics | 1 | 5% |
| Pharmacology, Toxicology and Pharmaceutical Science | 1 | 5% |
| Other | 1 | 5% |
| Unknown | 4 | 18% |