Learn to use DrugBank, a free, web-based tool that combines chemoinformatics with bioinformatics. Explore both the chemical and biological nature of drugs in silico using DrugCards, the functional units of DrugBank. Each DrugCard represents a unique drug in the database and contains over 100 information fields collated from numerous scientific sources. DrugCards provide extensive information on approved drugs, biotech drugs, small molecules, experimental drugs, and nutraceuticals, yet DrugCards are easy to read and shuffle through. You can query DrugBank with either chemical or biological terms, including the protein targets of drugs or the enzymes that metabolize them. A new feature correlates genetic single nucleotide polymorphisms with adverse drug reactions and drug effectiveness. Ideal for the student, scientist, drug discoverer, clinician, pharmacist, or general public, DrugBank will help you find the answers to your questions about pharmaceuticals and their underlying biological effects.
You will learn:
This tutorial is a part of the tutorial group Human variations. You might find the other tutorials in the group interesting:
GAD: Genetic Association Database: An archived database associating human genes and polymorphisms with diseases
Madeline 2.0: Human pedigree diagram tools
DGV: Database of Genomic Variants: Database of Genomic Variants, DGV, catalogs and displays structural variation in the human genome
NIEHS SNPs: National Institute for Environmental Health Sciences Environmental Genome Project (EGP) SNPs
OMIM: Online Mendelian Inheritance in Man (OMIM): A database of human genes, genetic diseases and disorders
CGAP: Characterize the molecular genetic changes that cause a normal cell to become a cancer cell
ENCODE Foundations: ENCyclopedia of DNA Elements
GeneSNPs: An integrated view of gene structure and SNP variations
HapMap: HapMap, a database and analysis resource of human variation
Genetics Home Reference: A collection of data describing the effects of genetic variability on human health and disease
dbGaP: A database of genotypes and phenotypes with extensive variation data and clinical details
SeattleSNPs: Human SNPs in genes
dbSNP: NCBI's SNP database
GeneTests: GeneTests, a current, comprehensive genetic testing resource
Genome Databases (euk) : Genomic databases or repositories primarily aimed at eukaryotic organisms. Some may contain prokaryotic data as well.
Friday SNPpets: Welcome to our Friday feature link collection: SNPpets. During the week we come across a lot of links and reads that we think are interesting, but don't make it to a blog post. Here they are for your e...
Video Tip of the Week: VnD Resource for Genetic Variation and Drug Information: In today's tip I am going to feature a resource that I found recently. I've been updating our dbSNP tutorial, which Mary & Trey will be presenting at workshops in Morocco, and also our free PDB tutori...
Recent BioMed Central research articles citing this resource
Krallinger Martin et al., CHEMDNER: The drugs and chemical names extraction challenge Text mining for chemistry and the CHEMDNER track. Journal of Cheminformatics (2015) doi:10.1186/1758-2946-7-S1-S1
Tang Buzhou et al., A comparison of conditional random fields and structured support vector machines for chemical entity recognition in biomedical literature Text mining for chemistry and the CHEMDNER track. Journal of Cheminformatics (2015) doi:10.1186/1758-2946-7-S1-S8
Dai Hong-Jie et al., Enhancing of chemical compound and drug name recognition using representative tag scheme and fine-grained tokenization Text mining for chemistry and the CHEMDNER track. Journal of Cheminformatics (2015) doi:10.1186/1758-2946-7-S1-S14
Akhondi A Saber et al., Recognition of chemical entities: combining dictionary-based and grammar-based approaches Text mining for chemistry and the CHEMDNER track. Journal of Cheminformatics (2015) doi:10.1186/1758-2946-7-S1-S10
Krallinger Martin et al., The CHEMDNER corpus of chemicals and drugs and its annotation principles Text mining for chemistry and the CHEMDNER track. Journal of Cheminformatics (2015) doi:10.1186/1758-2946-7-S1-S2