Syed, Ali Raza
Schofield, Paul N
KAUST DepartmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
Computational Bioscience Research Center (CBRC)
Computer Science Program
Permanent link to this recordhttp://hdl.handle.net/10754/661031
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AbstractBackground: Inborn errors of metabolism (IEM) represent a subclass of rare inherited diseases caused by a wide range of defects in metabolic enzymes or their regulation. Of over a thousand characterized IEMs, only about half are understood at the molecular level, and overall the development of treatment and management strategies has proved challenging. An overview of the changing landscape of therapeutic approaches is helpful in assessing strategic patterns in the approach to therapy, but the information is scattered throughout the literature and public data resources. Results: We gathered data on therapeutic strategies for 299 diseases into the Drug Database for Inborn Errors of Metabolism (DDIEM). Therapeutic approaches, including both successful and ineffective treatments, were manually classified by their mechanisms of action using a new ontology. Conclusions: We present a manually curated, ontologically formalized knowledgebase of drugs, therapeutic procedures, and mitigated phenotypes. DDIEM is freely available through a web interface and for download at http://ddiem.phenomebrowser.net.
CitationAbdelhakim, M., McMurray, E., Syed, A. R., Kafkas, S., Kamau, A. A., Schofield, P. N., & Hoehndorf, R. (2020). DDIEM: Drug Database for Inborn Errors of Metabolism. doi:10.1101/2020.01.08.897223
SponsorsThe authors acknowledge the support and generous assistance of Prof. Wyeth W. Wasserman, Prof. Nenad Blau and Tamar Av-Shalom in facilitating linkage between DDIEM and IEMbase. We thank Prof Michel Dumontier for advise on the curation process, data representation, and implementation of FAIR principles.
PublisherCold Spring Harbor Laboratory