Paper Info
Title
Drug target ontology to classify and integrate drug discovery data.
Abstract
DTO was built based on the need for a formal semantic model for druggable targets including various related information such as protein, gene, protein domain, protein structure, binding site, small molecule drug, mechanism of action, protein tissue localization, disease association, and many other types of information. DTO will further facilitate the otherwise challenging integration and formal linking to biological assays, phenotypes, disease models, drug poly-pharmacology, binding kinetics and many other processes, functions and qualities that are at the core of drug discovery. The first version of DTO is publically available via the website http://drugtargetontology.org/ , Github ( http://github.com/DrugTargetOntology/DTO ), and the NCBO Bioportal ( http://bioportal.bioontology.org/ontologies/DTO ). The long-term goal of DTO is to provide such an integrative framework and to populate the ontology with this information as a community resource.
Year
DOI
Venue
2017
10.1186/s13326-017-0161-x
J. Biomedical Semantics
Field
DocType
Volume
Ontology (information science),Ontology,Drug discovery,Druggability,Biology,Open Biomedical Ontologies,Formal ontology,Bioinformatics,Knowledge acquisition,Semantic data model
Journal
8
Issue
ISSN
Citations 
1
2041-1480
1
PageRank 
References 
Authors
0.36
26
22
Name
Order
Citations
PageRank
Yu Lin110110.36
Saurabh Mehta210.70
Hande Küçük-McGinty3181.14
John Paul Turner410.36
Dusica Vidovic510.70
Michele Forlin660.83
Amar Koleti7262.34
Dac-Trung Nguyen8123.10
Lars Juhl Jensen92202137.56
Rajarshi Guha1044234.84
Stephen L. Mathias11364.80
Oleg Ursu12394.57
Vasileios Stathias1372.57
Jianbin Duan1410.70
Nooshin Nabizadeh15171.53
Caty Chung16243.01
Christopher Mader1710.36
Ubbo Visser1829040.77
Jeremy J. Yang19434.62
Cristian Bologa20293.54
Tudor I Oprea2135946.89
Stephan C Schürer2213114.74