Use of Laplacian Heat Diffusion Algorithm to Infer Novel Genes With Functions Related to Uveitis

Lu, Shiheng; Zhao, Ke; Wang, Xuefei; Liu, Hui; Ainiwaer, Xiamuxiya; Xu, Yixin; Ye, Min

doi:10.3389/fgene.2018.00425

Cited by 6 publications

(3 citation statements)

References 76 publications

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“…Literature mining in PubMed 1 is used to collect uveitisrelated genes. In previous studies, Lu et al (2017Lu et al ( , 2018 conducted a PubMed search by using the keywords "uveitis" and obtained 744 relevant articles. A total of 98 review publications with basic summary of uveitis-related genes are manually reviewed.…”

Section: Data Acquisitionmentioning

confidence: 99%

Identification of uveitis-associated functions based on the feature selection analysis of gene ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment scores

Wang

Zhang

2022

Front. Mol. Neurosci.

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Uveitis is a typical type of eye inflammation affecting the middle layer of eye (i.e., uvea layer) and can lead to blindness in middle-aged and young people. Therefore, a comprehensive study determining the disease susceptibility and the underlying mechanisms for uveitis initiation and progression is urgently needed for the development of effective treatments. In the present study, 108 uveitis-related genes are collected on the basis of literature mining, and 17,560 other human genes are collected from the Ensembl database, which are treated as non-uveitis genes. Uveitis- and non-uveitis-related genes are then encoded by gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment scores based on the genes and their neighbors in STRING, resulting in 20,681 GO term features and 297 KEGG pathway features. Subsequently, we identify functions and biological processes that can distinguish uveitis-related genes from other human genes by using an integrated feature selection method, which incorporate feature filtering method (Boruta) and four feature importance assessment methods (i.e., LASSO, LightGBM, MCFS, and mRMR). Some essential GO terms and KEGG pathways related to uveitis, such as GO:0001841 (neural tube formation), has04612 (antigen processing and presentation in human beings), and GO:0043379 (memory T cell differentiation), are identified. The plausibility of the association of mined functional features with uveitis is verified on the basis of the literature. Overall, several advanced machine learning methods are used in the current study to uncover specific functions of uveitis and provide a theoretical foundation for the clinical treatment of uveitis.

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Section: Data Acquisitionmentioning

confidence: 99%

Identification of uveitis-associated functions based on the feature selection analysis of gene ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment scores

Wang

Zhang

2022

Front. Mol. Neurosci.

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“…According to the network propagation theory, nodes with a larger diffusion value may be affected preferentially [21]. This research assumed that the network-related nodes and corresponding interactions will change when each VFA node changing.…”

Section: Heat Diffusion On the Multilayer Networkmentioning

confidence: 99%

“…It then produces a list of nodes ranked by the accumulated heat. The node with amount connections tends to have a higher ranking, while an isolated node tends to have a low ranking [20,21].…”

Section: Introductionmentioning

confidence: 99%

A heat diffusion multilayer network approach for the identification of functional biomarkers in rumen methane emissions

Wang

Zheng

et al. 2021

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A better understanding of rumen microbial interactions is crucial for the study of rumen metabolism and methane emissions. Metagenomics-based methods can explore the relationship between microbial genes and metabolites to clarify the effect of microbial function on the host phenotype. This study investigated the rumen microbial mechanisms of methane metabolism in cattle by combining metagenomic data and network-based methods. Based on the relative abundance of 1461 rumen microbial genes and the main volatile fatty acids (VFAs), a multilayer heterogeneous network was constructed, and the functional modules associated with metabolite-microbial genes were obtained by heat diffusion. The PLS model by integrating data from VFAs and microbial genes explained 72.98% variation of methane emissions. Compared with single-layer networks, more previously reported biomarkers of methane prediction can be captured by the multilayer network. More biomarkers with the rank of top 20 topological centralities are from the PLS model of diffusion subset. The heat diffusion algorithm is different from the strategy used by the microbial metabolic system to understand methane phenotype. It inferred 24 novel biomarkers that were preferentially affected by changes in specific VFAs. Results showed that the heat diffusion multilayer network approach improved the understanding of the microbial patterns of VFA affecting methane emissions which represented by the functional genes.

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

Zhang

Zhao

et al. 2020

Biochimica et Biophysica Acta (BBA) - Molecular Basis of Diseas

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Use of Laplacian Heat Diffusion Algorithm to Infer Novel Genes With Functions Related to Uveitis

Cited by 6 publications

References 76 publications

Identification of uveitis-associated functions based on the feature selection analysis of gene ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment scores

Identification of uveitis-associated functions based on the feature selection analysis of gene ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment scores

A heat diffusion multilayer network approach for the identification of functional biomarkers in rumen methane emissions

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

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