Title |
TypOn: the microbial typing ontology
|
---|---|
Published in |
Journal of Biomedical Semantics, October 2014
|
DOI | 10.1186/2041-1480-5-43 |
Pubmed ID | |
Authors |
Cátia Vaz, Alexandre P Francisco, Mickael Silva, Keith A Jolley, James E Bray, Hannes Pouseele, Joerg Rothganger, Mário Ramirez, João A Carriço |
Abstract |
Bacterial identification and characterization at subspecies level is commonly known as Microbial Typing. Currently, these methodologies are fundamental tools in Clinical Microbiology and bacterial population genetics studies to track outbreaks and to study the dissemination and evolution of virulence or pathogenicity factors and antimicrobial resistance. Due to advances in DNA sequencing technology, these methods have evolved to become focused on sequence-based methodologies. The need to have a common understanding of the concepts described and the ability to share results within the community at a global level are increasingly important requisites for the continued development of portable and accurate sequence-based typing methods, especially with the recent introduction of Next Generation Sequencing (NGS) technologies. In this paper, we present an ontology designed for the sequence-based microbial typing field, capable of describing any of the sequence-based typing methodologies currently in use and being developed, including novel NGS based methods. This is a fundamental step to accurately describe, analyze, curate, and manage information for microbial typing based on sequence based typing methods. |
X Demographics
As of 1 July 2024, you may notice a temporary increase in the numbers of X profiles with Unknown location. Click here to learn more.
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 1 | 100% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Scientists | 1 | 100% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 1 | 3% |
Sweden | 1 | 3% |
Portugal | 1 | 3% |
Germany | 1 | 3% |
Unknown | 29 | 88% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 10 | 30% |
Student > Master | 6 | 18% |
Student > Ph. D. Student | 4 | 12% |
Student > Postgraduate | 3 | 9% |
Professor | 2 | 6% |
Other | 6 | 18% |
Unknown | 2 | 6% |
Readers by discipline | Count | As % |
---|---|---|
Biochemistry, Genetics and Molecular Biology | 9 | 27% |
Agricultural and Biological Sciences | 8 | 24% |
Computer Science | 5 | 15% |
Medicine and Dentistry | 3 | 9% |
Business, Management and Accounting | 1 | 3% |
Other | 4 | 12% |
Unknown | 3 | 9% |