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Network analysis and juvenile idiopathic arthritis (JIA): a new horizon for the understanding of disease pathogenesis and therapeutic target identification

Overview of attention for article published in Pediatric Rheumatology, July 2016
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Title
Network analysis and juvenile idiopathic arthritis (JIA): a new horizon for the understanding of disease pathogenesis and therapeutic target identification
Published in
Pediatric Rheumatology, July 2016
DOI 10.1186/s12969-016-0078-4
Pubmed ID
Authors

Rachelle Donn, Chiara De Leonibus, Stefan Meyer, Adam Stevens

Abstract

Juvenile idiopathic arthritis (JIA) is a clinically diverse and genetically complex autoimmune disease. Currently, there is very limited understanding of the potential underlying mechanisms that result in the range of phenotypes which constitute JIA.The elucidation of the functional relevance of genetic associations with phenotypic traits is a fundamental problem that hampers the translation of genetic observations to plausible medical interventions. Genome wide association studies, and subsequent fine-mapping studies in JIA patients, have identified many genetic variants associated with disease. Such approaches rely on 'tag' single nucleotide polymorphisms (SNPs). The associated SNPs are rarely functional variants, so the extrapolation of genetic association data to the identification of biologically meaningful findings can be a protracted undertaking. Integrative genomics aims to bridge the gap between genotype and phenotype.Systems biology, principally through network analysis, is emerging as a valuable way to identify biological pathways of relevance to complex genetic diseases. This review aims to highlight recent findings in systems biology related to JIA in an attempt to assist in the understanding of JIA pathogenesis and therapeutic target identification.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 37 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 3%
Canada 1 3%
Unknown 35 95%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 6 16%
Researcher 5 14%
Other 4 11%
Student > Ph. D. Student 4 11%
Student > Master 4 11%
Other 10 27%
Unknown 4 11%
Readers by discipline Count As %
Medicine and Dentistry 18 49%
Biochemistry, Genetics and Molecular Biology 4 11%
Agricultural and Biological Sciences 3 8%
Social Sciences 2 5%
Environmental Science 1 3%
Other 3 8%
Unknown 6 16%