AgeFactDB—the JenAge Ageing Factor Database—towards data integration in ageing research

Abstract

AgeFactDB (http://agefactdb.jenage.de) is a database aimed at the collection and integration of ageing phenotype data including lifespan information. Ageing factors are considered to be genes, chemical compounds or other factors such as dietary restriction, whose action results in a changed lifespan or another ageing phenotype. Any information related to the effects of ageing factors is called an observation and is presented on observation pages. To provide concise access to the complete information for a particular ageing factor, corresponding observations are also summarized on ageing factor pages. In a first step, ageing-related data were primarily taken from existing databases such as the Ageing Gene Database—GenAge, the Lifespan Observations Database and the Dietary Restriction Gene Database—GenDR. In addition, we have started to include new ageing-related information. Based on homology data taken from the HomoloGene Database, AgeFactDB also provides observation and ageing factor pages of genes that are homologous to known ageing-related genes. These homologues are considered as candidate or putative ageing-related genes. AgeFactDB offers a variety of search and browse options, and also allows the download of ageing factor or observation lists in TSV, CSV and XML formats.

The DrugAge database of aging-related drugs

“…HAGR focuses mostly on genes, and thus there is a need for a curated database of drugs and compounds that can extend lifespan in model organisms. Existing databases with lifespan‐extending drugs include AgeFactDB (http://agefactdb.jenage.de/) (Huhne et al ., 2014), in turn based on data from HAGR and SAGEWEB (http://sageweb.org/), and Geroprotectors.org (http://geroprotectors.org/) (Moskalev et al ., 2015). DrugAge incorporates data from all these resources and improves on them by providing a more extensive and systematic repertoire of lifespan‐extending drugs, compounds and substances.…”

Systems Epigenomics and Applications to Ageing and Cancer

“…Although the methylation of H3K4 has been widely observed to vary with age (see, e.g. Lui et al 2014;Walter et al 2014), RBBP5's potential role in ageing was only implied from homology (JenAge AgeFactDB database) (Huehne et al 2014). Thus, the new data suggests that the age-induced impairment of RBBP5 binding could lead to the functional disruption of the MLL complex and hence to the loss of H3K4 methylation, a well-known ageing effect (Lui et al 2014;Walter et al 2014).…”

Big data and precision medicine: challenges and strategies with healthcare data

“…Although a plethora of accessible knowledge bases exists [24], they are typically designed for a universal topic rather than for a specific domain of interest. They need to be combined, adapted and/or redesigned for the specific application at hand [25,34]. Gathering domain knowledge should be a dynamic process that is influenced by the evaluation of patient cohorts.…”