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1.
Nucleic Acids Res ; 43(Database issue): D784-8, 2015 Jan.
Article in English | MEDLINE | ID: mdl-25414323

ABSTRACT

It has been 12 years since the Allele Frequency Net Database (AFND; http://www.allelefrequencies.net) was first launched, providing the scientific community with an online repository for the storage of immune gene frequencies in different populations across the world. There have been a significant number of improvements from the first version, making AFND a primary resource for many clinical and scientific areas including histocompatibility, immunogenetics, pharmacogenetics and anthropology studies, among many others. The most widely used part of AFND stores population frequency data (alleles, genes or haplotypes) related to human leukocyte antigens (HLA), killer-cell immunoglobulin-like receptors (KIR), major histocompatibility complex class I chain-related genes (MIC) and a number of cytokine gene polymorphisms. AFND now contains >1400 populations from more than 10 million healthy individuals. Here, we report how the main features of AFND have been updated to include a new section on 'HLA epitope' frequencies in populations, a new section capturing the results of studies identifying HLA associations with adverse drug reactions (ADRs) and one for the examination of infectious and autoimmune diseases associated with KIR polymorphisms-thus extending AFND to serve a new user base in these growing areas of research. New criteria on data quality have also been included.


Subject(s)
Databases, Genetic , Epitopes/genetics , Gene Frequency , HLA Antigens/genetics , Receptors, KIR/genetics , Disease/genetics , Drug-Related Side Effects and Adverse Reactions/genetics , HLA Antigens/immunology , Histocompatibility Antigens Class I/genetics , Humans , Internet
2.
Transfus Med Hemother ; 41(5): 352-5, 2014 Oct.
Article in English | MEDLINE | ID: mdl-25538537

ABSTRACT

This review describes a database for the collection, archiving, sorting, searching and display of gene and allele frequencies for immunogenetic genes.

3.
Database (Oxford) ; 2013: bat021, 2013.
Article in English | MEDLINE | ID: mdl-23584834

ABSTRACT

The killer cell immunoglobulin-like receptors (KIR) play a fundamental role in the innate immune system, through their interactions with human leucocyte antigen (HLA) molecules, leading to the modulation of activity in natural killer (NK) cells, mainly related to killing pathogen-infected cells. KIR genes are hugely polymorphic both in the number of genes an individual carries and in the number of alleles identified. We have previously developed the Allele Frequency Net Database (AFND, http://www.allelefrequencies.net), which captures worldwide frequencies of alleles, genes and haplotypes for several immune genes, including KIR genes, in healthy populations, covering >4 million individuals. Here, we report the creation of a new database within AFND, named KIR and Diseases Database (KDDB), capturing a large quantity of data derived from publications in which KIR genes, alleles, genotypes and/or haplotypes have been associated with infectious diseases (e.g. hepatitis C, HIV, malaria), autoimmune disorders (e.g. type I diabetes, rheumatoid arthritis), cancer and pregnancy-related complications. KDDB has been created through an extensive manual curation effort, extracting data on more than a thousand KIR-disease records, comprising >50 000 individuals. KDDB thus provides a new community resource for understanding not only how KIR genes are associated with disease, but also, by working in tandem with the large data sets already present in AFND, where particular genes, genotypes or haplotypes are present in worldwide populations or different ethnic groups. We anticipate that KDDB will be an important resource for researchers working in immunogenetics. Database URL: http://www.allelefrequencies.net/diseases/.


Subject(s)
Data Mining , Databases, Genetic , Disease/genetics , Genetic Association Studies , Genetic Predisposition to Disease , Internationality , Receptors, KIR/genetics , Genetics, Population , Humans , Internet , Search Engine
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