SysKid, the acronym for Systems Biology Towards Novel Chronic Kidney Disease Diagnosis and Treatment, is a large scale, integrated project funded by the European Union focusing on deepening our understanding of early chronic kidney disease in subjects with diabetes and hypertension (www.syskid.eu). The project, scheduled from 2010 to 2014, involves 26 partners from 15 countries, and integrates large scale Omics from the genome to the metabolome level, in vitro and in vivo models, being further complemented with clinical statistics and epidemiology research.
Specific aims of SysKid include
1. Identify persons at risk of developing chronic kidney disease utilizing epidemiology as well as molecular tools.
2. Understand the molecular processes triggering early stage chronic kidney disease and identify associated biomarkers.
3. Develop novel diagnostic and therapeutic strategies to control progression of chronic kidney disease.
4. Perform pre-clinical verification of novel therapy approaches and perform clinical testing of novel diagnostics.
SysKid, utilizing significant molecular background knowledge available on the later stages of the disease together with large scale data on earlier stages generated in the project, implements a Kidney Disease Interactome concept as common denominator for integrative analysis. Core of this concept is a human gene/protein interaction network, delineated as a hybrid, associative network consolidating a specific set of available protein interaction and gene/protein functional classification data. The network includes about 17,000 nodes (protein coding genes) and about 1,0 Mio weighted edges encoding relations of various types.
We use this interaction network as common denominator for consolidating the rich molecular feature profiles from genetic analyses, transcriptomics (both, protein coding as well as miRNAs), proteomics and metabolomics done on human samples, together with the molecular data space generated from in vitro and in vivo models. Technically, this consolidation involves the annotation of each network node with a data structure carrying the specific experiment source and sample annotation (for human samples the specific clinical data profile), in this way generating a data graph embodying the clinical(model) feature space together with the specific molecular profile, all set into context on the level of a human gene/protein interaction network the Kidney Disease Interactome.
View the presentation below:
This was presented at the ISN Forefronts Symposium event “Systems Biology and the Kidney” that took place from 7-10 June 2012 in AnnArbor , Michigan, US.
Additional Info
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Contains Audio:
Yes -
Source:
ISN -
Event:
Forefronts -
Year:
2012 -
Members Only:
No