Table 1 |
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|
The current LODD datasets.Further information about content and accessibility (URIs, SPARQL endpoints) of these linked datasets can be found online at [27]. |
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|
Name |
Short Description |
Size and coverage (rounded) |
Sources |
Provider (1. original dataset, 2. RDF version of dataset) |
|
|
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|
DrugBank |
Chemical, pharmacological and pharmaceutical drug data; data about drug targets (e.g., sequences, structure, pathways) |
767,000 triples; 4,800 drugs, 2,500 protein sequences |
Aggregated from various biomedical and pharmaceutical databases |
1. University of Alberta 2. Free University of Berlin |
|
|
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|
ClinicalTrials.gov/LinkedCT |
Information about clinical trials |
9.8 million triples, 80,000 trials |
Data submitted by study sponsors or their representatives |
1. US National Institute of Health 2. LinkedCT.org; University of Toronto |
|
|
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|
DailyMed |
Information about approved prescription drugs, including FDA approved labels (package inserts) |
164,000 triples; 4,000 drugs |
Package inserts, data from the US food and drug administration (FDA) |
1. US National Library of Medicine 2. Free University of Berlin |
|
|
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|
ChEMBL |
Information on drugs, e.g., activity against drug targets such as proteins, chemical properties. Linked to primary literature |
24 million triples; 8000 drug targets, 660,000 compounds |
Aggregated from various biomedical and pharmaceutical databases |
1. European Bioinformatics Institute 2. Uppsala University |
|
|
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|
Diseasome |
Characteristics of disorders and disease genes linked by known disease-gene associations |
91,000 triples; 2,600 genes |
Generated from data in Online Mendelian Inheritance in Man (OMIM) |
1. Consortium of several labs 2. Free University of Berlin |
|
|
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|
TCMGeneDIT/RDF-TCM |
Gene-disease-drug associations mined from literature about Chinese medicine |
117,000 triples |
Mined from research articles |
1. National Taiwan University 2. Oxford University |
|
|
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|
RxNorm |
Prescription drugs, their ingredients, and national drug codes |
7.7 million triples; 166,000 unique drugs and ingredients |
FDA databases |
1. US National Library of Medicine 2. Stony Brook School of Medicine |
|
|
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|
UMLS |
Unified Medical Language System (UMLS) sources available without restrictions |
55 million triples |
Ontologies created by third parties |
1. US National Library of Medicine 2. Stony Brook School of Medicine |
|
|
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|
SIDER |
Reported adverse effects of marketed drugs |
193,000 triples; 63,000 adverse effect reports |
Mined package inserts |
1. European Molecular Biology Laboratory, Heidelberg 2. Free University of Berlin |
|
|
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|
STITCH |
Molecular interactions between chemicals and proteins |
7.5 million chemicals, 500,000 proteins, 370 organisms |
Aggregated from various biomedical and pharmaceutical databases |
1. European Molecular Biology Laboratory, Heidelberg 2. Free University of Berlin |
|
|
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|
Medicare |
The Medicare formulary |
44,500 triples; 6800 drugs |
Primary data |
1. US Government 2. Free University of Berlin |
|
|
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|
WHO Global Health Observatory |
Data and statistics for infectious diseases at country, regional, and global levels. |
354,000 triples |
Primary data collected by the World Health Organization |
1. World Health Organization 2. Leipzig University |
|
|
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|
Statistics about size and coverage were last checked on March 24, 2011. |
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|
Samwald et al. Journal of Cheminformatics 2011 3:19 doi:10.1186/1758-2946-3-19 |
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