scholarly journals Identification of proliferative diabetic retinopathy-associated genes on the protein–protein interaction network by using heat diffusion algorithm

Author(s):  
Jian Zhang ◽  
Meihua Zhang ◽  
Huijie Zhao ◽  
Xun Xu
2017 ◽  
Vol 8 (Suppl 1) ◽  
pp. S20-S21 ◽  
Author(s):  
Akram Safaei ◽  
Mostafa Rezaei Tavirani ◽  
Mona Zamanian Azodi ◽  
Alireza Lashay ◽  
Seyed Farzad Mohammadi ◽  
...  

2016 ◽  
Vol 24 (01) ◽  
pp. 117-127 ◽  
Author(s):  
S. UMADEVI ◽  
K. PREMKUMAR ◽  
S. VALARMATHI ◽  
P. M. AYYASAMY ◽  
S. RAJAKUMAR

Diabetic retinopathy is the most common cause of blindness, associated with many biochemical pathways mediated by several genes and proteins. Disease gene identification can be achieved through several approaches but still it is a challenging task. This study, aimed to find out the novel genes associated with diabetic retinopathy. In this study, all the well-known genes associated with diabetic retinopathy were collected from databases and the protein interaction partners were identified. The interacting candidate genes were chosen by chromosomal locations, sharing with disease genes. The protein–protein interaction network was constructed and the key nodes (genes) were identified by degree, betweenness centrality, closeness centrality and eccentricity centrality. Further, the ontological terms, molecular function, biological process and cellular components were related with that of the disease genes with p-value [Formula: see text]. The genes UBC, FOS, ITGB1, FOXA2, CCND1, FOSL1, RXRA and NCAM1 were identified as potential genes associated with diabetic retinopathy. The molecular functions of these genes include protein binding, receptor activity, receptor binding, oxidoreductase activity, protein kinase activity, serine-type peptidase activity and growth factor. Many of the identified genes were clinically related as evidence by the literature.


2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Minjie Sheng ◽  
Haiying Cai ◽  
Ming Cheng ◽  
Jing Li ◽  
Jian Zhang ◽  
...  

Choroidal neovascularization (CNV) is a type of eye disease that can cause vision loss. In recent years, many studies have attempted to investigate the major pathological processes and molecular pathogenic mechanisms of CNV. Because many diseases are related to genes, the genes associated with CNV need to be identified. In this study, we proposed a network-based approach for identifying novel CNV-associated genes. To execute such method, we first employed a protein-protein interaction network reported in STRING. Then, we applied a network diffusion algorithm, Laplacian heat diffusion, on this network by selecting validated CNV-related genes as the seed nodes. As a result, some novel genes that had unknown but strong relationships with validated genes were identified. Furthermore, we used a screening procedure to extract the most essential genes. Eleven latent CNV-related genes were finally obtained. Extensive analyses were performed to confirm that these genes are novel CNV-related genes.


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