Identification of Novel Choroidal Neovascularization-Related Genes Using Laplacian Heat Diffusion Algorithm.
Minjie ShengHaiying CaiMing ChengJing LiJian ZhangLihua LiuPublished in: BioMed research international (2021)
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.
Keyphrases
- bioinformatics analysis
- genome wide
- genome wide identification
- protein protein
- machine learning
- small molecule
- deep learning
- genome wide analysis
- optical coherence tomography
- squamous cell carcinoma
- gene expression
- vascular endothelial growth factor
- oxidative stress
- transcription factor
- heat stress
- diabetic retinopathy
- single molecule
- neoadjuvant chemotherapy
- anti inflammatory
- network analysis
- optic nerve
- locally advanced
- rectal cancer