Statistical Analysis of Protein Microarray Data: A Case Study in Type 1 Diabetes Research

2015 ◽  
Vol 08 (02) ◽  
Author(s):  
Le TT An Anna Pursiheimo
Diabetes ◽  
2019 ◽  
Vol 68 (Supplement 1) ◽  
pp. 209-OR ◽  
Author(s):  
ANA MARIA ARBELAEZ ◽  
STEFANI O’DONOGHUE ◽  
NELLY MAURAS ◽  
BRUCE A. BUCKINGHAM ◽  
NEIL H. WHITE ◽  
...  

2015 ◽  
Vol 2015 ◽  
pp. 1-7 ◽  
Author(s):  
Sharad Purohit ◽  
Ashok Sharma ◽  
Jin-Xiong She

Complex interactions between a series of environmental factors and genes result in progression to clinical type 1 diabetes in genetically susceptible individuals. Despite several decades of research in the area, these interactions remain poorly understood. Several studies have yielded associations of certain foods, infections, and immunizations with the onset and progression of diabetes autoimmunity, but most findings are still inconclusive. Environmental triggers are difficult to identify mainly due to (i) large number and complex nature of environmental exposures, including bacteria, viruses, dietary factors, and environmental pollutants, (ii) reliance on low throughput technology, (iii) less efforts in quantifying host response, (iv) long silent period between the exposure and clinical onset of T1D which may lead to loss of the exposure fingerprints, and (v) limited sample sets. Recent development in multiplex technologies has enabled systematic evaluation of different classes of molecules or macroparticles in a high throughput manner. However, the use of multiplex assays in type 1 diabetes research is limited to cytokine assays. In this review, we will discuss the potential use of multiplex high throughput technologies in identification of environmental triggers and host response in type 1 diabetes.


2009 ◽  
Vol 29 (2) ◽  
pp. 85 ◽  
Author(s):  
VR Rao ◽  
Oindrila Raha ◽  
Subhankar Chowdhury ◽  
Samir Dasgupta ◽  
P Raychaudhuri ◽  
...  

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