scholarly journals A Meta-Path-Based Prediction Method for Human miRNA-Target Association

2016 ◽  
Vol 2016 ◽  
pp. 1-9 ◽  
Author(s):  
Jiawei Luo ◽  
Cong Huang ◽  
Pingjian Ding
Keyword(s):  
Mirna Target ◽  
Prediction Method ◽  
Enrichment Analysis ◽  
Pathway Enrichment Analysis ◽  
Sequence Information ◽  
Considerable Problem ◽  
Meta Path ◽  
Target Association ◽  
The Relationship ◽  
Gene Expressing

MicroRNAs (miRNAs) are short noncoding RNAs that play important roles in regulating gene expressing, and the perturbed miRNAs are often associated with development and tumorigenesis as they have effects on their target mRNA. Predicting potential miRNA-target associations from multiple types of genomic data is a considerable problem in the bioinformatics research. However, most of the existing methods did not fully use the experimentally validated miRNA-mRNA interactions. Here, we developed RMLM and RMLMSe to predict the relationship between miRNAs and their targets. RMLM and RMLMSe are global approaches as they can reconstruct the missing associations for all the miRNA-target simultaneously and RMLMSe demonstrates that the integration of sequence information can improve the performance of RMLM. In RMLM, we use RM measure to evaluate different relatedness between miRNA and its target based on different meta-paths; logistic regression and MLE method are employed to estimate the weight of different meta-paths. In RMLMSe, sequence information is utilized to improve the performance of RMLM. Here, we carry on fivefold cross validation and pathway enrichment analysis to prove the performance of our methods. The fivefold experiments show that our methods have higher AUC scores compared with other methods and the integration of sequence information can improve the performance of miRNA-target association prediction.

scholarly journals Hidden in plain sight: The effects of BCG vaccination in COVID-19 pandemic

2020 ◽  
Author(s):  
Eman Ali Toraih ◽  
Jessica Ashraf Sedhom ◽  
Titilope Modupe Dokunmu ◽  
Mohammad Hosny Hussein ◽  
Emmanuelle ML Ruiz ◽  
...  
Keyword(s):  
Enrichment Analysis ◽  
Protective Role ◽  
Pathway Enrichment Analysis ◽  
Infection Group ◽  
Bcg Vaccination ◽  
Pathway Enrichment ◽  
Kegg Pathways ◽  
The Relationship ◽  
Bioinformatic Approach ◽  
Cross Reference

AbstractTo investigate the relationship between BCG vaccination and SARS-CoV-2 by bioinformatic approach. Two datasets for Sars-CoV-2 infection group and BCG-vaccinated group were downloaded. Differentially Expressed Genes were identified. Gene ontology and pathways were functionally enriched, and networking was constructed in NetworkAnalyst. Lastly, correlation between post-BCG vaccination and COVID-19 transcriptome signatures were established. A total of 161 DEGs (113 upregulated DEGs and 48 downregulated genes) were identified in the Sars-CoV-2 group. In the pathway enrichment analysis, cross-reference of upregulated KEGG pathways in Sars-CoV-2 with downregulated counterparts in the BCG-vaccinated group, resulted in the intersection of 45 common pathways, accounting for 86.5% of SARS-CoV-2 upregulated pathways. Of these intersecting pathways, a vast majority were immune and inflammatory pathways with top significance in IL-17, TNF, NOD-like receptors, and NF-κB signaling pathways. Our data suggests BCG-vaccination may incur a protective role in COVID-19 patients until a targeted vaccine is developed.Supplementary Materials(https://drive.google.com/open?id=15Na738L282XNaQAJUh0cZf1WoG9jJfzJ)

scholarly journals A Network Pharmacology Approach to Uncover the Pharmacological Mechanism of XuanHuSuo Powder on Osteoarthritis

2016 ◽  
Vol 2016 ◽  
pp. 1-10 ◽  
Author(s):  
Huaqi Tang ◽  
Shuaibing He ◽  
Xinyue Zhang ◽  
Shilin Luo ◽  
Baixia Zhang ◽  
...  
Keyword(s):  
Interleukin 1 ◽  
Enrichment Analysis ◽  
Global Scale ◽  
Network Pharmacology ◽  
Pathway Enrichment Analysis ◽  
Pathway Enrichment ◽  
Complementary Method ◽  
Pharmacological Mechanism ◽  
First Time ◽  
The Relationship

As the most familiar type of arthritis and a chronic illness of the joints, Osteoarthritis (OA) affects a great number of people on the global scale. XuanHuSuo powder (XHSP), a conventional herbal formula from China, has been extensively applied in OA treatment. Nonetheless, its pharmacological mechanism has not been completely expounded. In this research, a network pharmacology approach has been chosen to study the pharmacological mechanism of XHSP on OA, and the pharmacology networks were established based on the relationship between four herbs found in XHSP, compound targets, and OA targets. The pathway enrichment analysis revealed that the significant bioprocess networks of XHSP on OA were regulation of inflammation, interleukin-1β(IL-1β) production and nitric oxide (NO) biosynthetic process, response to cytokine or estrogen stimuli, and antiapoptosis. These effects have not been reported previously. The comprehensive network pharmacology approach developed by our research has revealed, for the first time, a connection between four herbs found in XHSP, corresponding compound targets, and OA pathway systems that are conducive to expanding the clinical application of XHSP. The proposed network pharmacology approach could be a promising complementary method by which researchers might better evaluate multitarget or multicomponent drugs on a systematic level.

scholarly journals Profiling of MicroRNAs and Their Targets in Roots and Shoots Reveals a Potential MiRNA-Mediated Interaction Network in Response to Phosphate Deficiency in the Forestry Tree Betula luminifera

2021 ◽  
Vol 12 ◽  
Author(s):  
Junhong Zhang ◽  
Yan Lin ◽  
Fangmin Wu ◽  
Yuting Zhang ◽  
Longjun Cheng ◽  
...  
Keyword(s):  
Mirna Target ◽  
Interaction Network ◽  
Enrichment Analysis ◽  
Woody Species ◽  
Differentially Expressed ◽  
Phosphate Deficiency ◽  
Pathway Enrichment Analysis ◽  
Adaptive Responses ◽  
Betula Luminifera ◽  
Use Efficiency

Inorganic phosphate (Pi) is often lacking in natural and agro-climatic environments, which impedes the growth of economically important woody species. Plants have developed strategies to cope with low Pi (LP) availability. MicroRNAs (miRNAs) play important roles in responses to abiotic stresses, including nutrition stress, by regulating target gene expression. However, the miRNA-mediated regulation of these adaptive responses and their underlying coordinating signals are still poorly understood in forestry trees such as Betula luminifera. Transcriptomic libraries, small RNA (sRNA) libraries, and a mixed degradome cDNA library of B. luminifera roots and shoots treated under LP and normal conditions (CK) were constructed and sequenced using next-generation deep sequencing. A comprehensive B. luminifera transcriptome derived from its roots and shoots was constructed, and a total of 76,899 unigenes were generated. Analysis of the transcriptome identified 8,095 and 5,584 differentially expressed genes in roots and shoots, respectively, under LP conditions. sRNA sequencing analyses indicated that 66 and 60 miRNAs were differentially expressed in roots and shoots, respectively, under LP conditions. A total of 109 and 112 miRNA–target pairs were further validated in the roots and shoots, respectively, using degradome sequencing. Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis of differential miRNA targets indicated that the “ascorbate and aldarate metabolism” pathway responded to LP, suggesting miRNA-target pairs might participating in the removing of reactive oxidative species under LP stress. Moreover, a putative network of miRNA–target interactions involved in responses to LP stress in B. luminifera is proposed. Taken together, these findings provide useful information to decipher miRNA functions and establish a framework for exploring P signaling networks regulated by miRNAs in B. luminifera and other woody plants. It may provide new insights into the genetic engineering of high use efficiency of Pi in forestry trees.

scholarly journals Effects of EFNA1 on cell phenotype and prognosis of esophageal carcinoma

2021 ◽  
Vol 19 (1) ◽  
Author(s):  
Yongqiang Zhang ◽  
Jinning Zhang ◽  
Guanlong Pan ◽  
Tianhao Guan ◽  
Changhao Zhang ◽  
...  
Keyword(s):  
Esophageal Carcinoma ◽  
Cell Model ◽  
Enrichment Analysis ◽  
Tnm Staging ◽  
Cell Phenotype ◽  
Pathway Enrichment Analysis ◽  
Tissue Samples ◽  
Paired Samples ◽  
The Relationship ◽  
Inhibit Cell Proliferation

Abstract Background To investigate the expression and clinical significance of EFNA1 in broad-spectrum tumors, and to evaluate its relationship with prognosis and biological functions of esophageal carcinoma (ESCA). Methods EFNA1 expression in various cancers was analyzed according to the data in the TCGA database. The clinical data were integrated, to analyze the relationship with ESCA clinical parameters and prognosis, and EFNA1 expression in ESCA tissue samples was detected by immunohistochemistry (IHC). Based on bioinformatics, the functional background of EFNA1 overexpression was analyzed. EFNA1 knockout cell model was established by EFNA1-shRNA transfecting ESCA cells, and the effect of knocking down EFNA1 on the proliferation of ESCA cells was detected by MTT. Results Among 7563 samples from TCGA, the EFNA1 gene highly expressed in 15 samples with common cancers and endangered the prognosis of patients with tumors. Its overexpression in ESCA and its influence on the prognosis were most significant. EFNA1 expression in 80 samples with ESCA and their paired samples was tested by IHC to verify its high expression (paired t test, P < 0.001) in ESCA tissues. It was found that EFNA1 expression was related to clinical factors (TNM staging, P = 0.031; lymph node metastasis, P = 0.043; infiltration, P = 0.016). Meanwhile, EFNA1 was found to be an independent risk factor based on the COX multi-factor analysis. And to further explore the importance of EFNA1 in tumors, EC-9706 and ECA109 cells were screened from 8 ESCA-related cell lines to build EFNA1 knockdown cell models. The results showed that EFNA1 knockdown significantly inhibited the proliferation of tumor cells (P < 0.05). In terms of molecular mechanism, EFNA1 related genes were significantly enriched in the proliferative pathway according to the pathway enrichment analysis. It was found that knocking down EFNA1 did inhibit cell proliferation based on cell experiments. Conclusions EFNA1 overexpression in ESCA tissue is related to the prognosis of patients. Knocking down EFNA1 can significantly inhibit the proliferation of ESCA cells.

A Method of Pathway Enrichment Analysis Based Gene Expression Variability

2013 ◽  
Vol 40 (12) ◽  
pp. 1256
Author(s):  
XiaoDong JIA ◽  
XiuJie CHEN ◽  
Xin WU ◽  
JianKai XU ◽  
FuJian TAN ◽  
...  
Keyword(s):  
Gene Expression ◽  
Enrichment Analysis ◽  
Pathway Enrichment Analysis ◽  
Expression Variability ◽  
Pathway Enrichment

Systematic Investigation of Quercetin for Treating Cardiovascular Disease Based on Network Pharmacology

2019 ◽  
Vol 22 (6) ◽  
pp. 411-420 ◽  
Author(s):  
Xian-Jun Wu ◽  
Xin-Bin Zhou ◽  
Chen Chen ◽  
Wei Mao
Keyword(s):  
Cardiovascular Disease ◽  
Cardiovascular Diseases ◽  
Signaling Pathway ◽  
Kegg Pathway ◽  
Enrichment Analysis ◽  
Network Pharmacology ◽  
Pathway Enrichment Analysis ◽  
Therapeutic Effects ◽  
Pathway Enrichment ◽  
Compound Target

Aim and Objective: Cardiovascular disease is a serious threat to human health because of its high mortality and morbidity rates. At present, there is no effective treatment. In Southeast Asia, traditional Chinese medicine is widely used in the treatment of cardiovascular diseases. Quercetin is a flavonoid extract of Ginkgo biloba leaves. Basic experiments and clinical studies have shown that quercetin has a significant effect on the treatment of cardiovascular diseases. However, its precise mechanism is still unclear. Therefore, it is necessary to exploit the network pharmacological potential effects of quercetin on cardiovascular disease. Materials and Methods: In the present study, a novel network pharmacology strategy based on pharmacokinetic filtering, target fishing, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis, compound-target-pathway network structured was performed to explore the anti- cardiovascular disease mechanism of quercetin. Results:: The outcomes showed that quercetin possesses favorable pharmacokinetic profiles, which have interactions with 47 cardiovascular disease-related targets and 12 KEGG signaling pathways to provide potential synergistic therapeutic effects. Following the construction of Compound-Target-Pathway (C-T-P) network, and the network topological feature calculation, we obtained top 10 core genes in this network which were AKT1, IL1B, TNF, IL6, JUN, CCL2, FOS, VEGFA, CXCL8, and ICAM1. KEGG pathway enrichment analysis. These indicated that quercetin produced the therapeutic effects against cardiovascular disease by systemically and holistically regulating many signaling pathways, including Fluid shear stress and atherosclerosis, AGE-RAGE signaling pathway in diabetic complications, TNF signaling pathway, MAPK signaling pathway, IL-17 signaling pathway and PI3K-Akt signaling pathway.

Determination of Usnic Acid Responsive miRNAs in Breast Cancer Cell Lines

2019 ◽  
Vol 19 (12) ◽  
pp. 1463-1472 ◽  
Author(s):  
Nil Kiliç ◽  
Yasemin Ö. Islakoğlu ◽  
İlker Büyük ◽  
Bala Gür-Dedeoğlu ◽  
Demet Cansaran-Duman
Keyword(s):  
Breast Cancer ◽  
Hedgehog Signaling ◽  
Treatment Options ◽  
Usnic Acid ◽  
Enrichment Analysis ◽  
Breast Cancer Cell Lines ◽  
Pathway Enrichment Analysis ◽  
Molecular Heterogeneity ◽  
Proliferative Effect ◽  
Mcf 7

Objective: Breast Cancer (BC) is the most common type of cancer diagnosed in women. A common treatment strategy for BC is still not available because of its molecular heterogeneity and resistance is developed in most of the patients through the course of treatment. Therefore, alternative medicine resources as being novel treatment options are needed to be used for the treatment of BC. Usnic Acid (UA) that is one of the secondary metabolites of lichens used for different purposes in the field of medicine and its anti-proliferative effect has been shown in certain cancer types, suggesting its potential use for the treatment. Methods: Anti-proliferative effect of UA in BC cells (MDA-MB-231, MCF-7, BT-474) was identified through MTT analysis. Microarray analysis was performed in cells treated with the effective concentration of UA and UA-responsive miRNAs were detected. Their targets and the pathways that they involve were determined using a miRNA target prediction tool. Results: Microarray experiments showed that 67 miRNAs were specifically responsive to UA in MDA-MB-231 cells while 15 and 8 were specific to BT-474 and MCF-7 cells, respectively. The miRNA targets were mostly found to play role in Hedgehog signaling pathway. TGF-Beta, MAPK and apoptosis pathways were also the prominent ones according to the miRNA enrichment analysis. Conclusion: The current study is important as being the first study in the literature which aimed to explore the UA related miRNAs, their targets and molecular pathways that may have roles in the BC. The results of pathway enrichment analysis and anti-proliferative effects of UA support the idea that UA might be used as a potential alternative therapeutic agent for BC treatment.

scholarly journals Signature RNAS and related regulatory roles in type 1 diabetes mellitus based on competing endogenous RNA regulatory network analysis

2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Qinghong Shi ◽  
Hanxin Yao
Keyword(s):  
Diabetes Mellitus ◽  
Type 1 Diabetes ◽  
Network Analysis ◽  
Type 1 Diabetes Mellitus ◽  
Regulatory Network ◽  
Enrichment Analysis ◽  
Pathway Enrichment Analysis ◽  
Competing Endogenous Rna ◽  
Pathway Enrichment

Abstract Background Our study aimed to investigate signature RNAs and their potential roles in type 1 diabetes mellitus (T1DM) using a competing endogenous RNA regulatory network analysis. Methods Expression profiles of GSE55100, deposited from peripheral blood mononuclear cells of 12 T1DM patients and 10 normal controls, were downloaded from the Gene Expression Omnibus to uncover differentially expressed long non-coding RNAs (lncRNAs), mRNAs, and microRNAs (miRNAs). The ceRNA regulatory network was constructed, then functional and pathway enrichment analysis was conducted. AT1DM-related ceRNA regulatory network was established based on the Human microRNA Disease Database to carry out pathway enrichment analysis. Meanwhile, the T1DM-related pathways were retrieved from the Comparative Toxicogenomics Database (CTD). Results In total, 847 mRNAs, 41 lncRNAs, and 38 miRNAs were significantly differentially expressed. The ceRNA regulatory network consisted of 12 lncRNAs, 10 miRNAs, and 24 mRNAs. Two miRNAs (hsa-miR-181a and hsa-miR-1275) were screened as T1DM-related miRNAs to build the T1DM-related ceRNA regulatory network, in which genes were considerably enriched in seven pathways. Moreover, three overlapping pathways, including the phosphatidylinositol signaling system (involving PIP4K2A, INPP4A, PIP4K2C, and CALM1); dopaminergic synapse (involving CALM1 and PPP2R5C); and the insulin signaling pathway (involving CBLB and CALM1) were revealed by comparing with T1DM-related pathways in the CTD, which involved four lncRNAs (LINC01278, TRG-AS1, MIAT, and GAS5-AS1). Conclusion The identified signature RNAs may serve as important regulators in the pathogenesis of T1DM.

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