PANEV: an R package for a pathway-based network visualization

Palombo, Valentino; Milanesi, Marco; Sferra, Gabriella; Capomaccio, Stefano; Sgorlon, Sandy; D’Andrea, Mariasilvia

doi:10.1186/s12859-020-3371-7

Cited by 16 publications

(16 citation statements)

References 38 publications

(48 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The R package PAthway NEtwork Visualizer (PANEV) uses Kyoto Encyclopedia of Genes and Genomes (KEGG) database to map the correlated first- and second-level pathways using the genes provided by the user ( 29 ). The genes resulted from the ElasticNet feature selection and the top 10 candidate pathways drawn from KEGG database were fed into PANEV.…”

Section: Methodsmentioning

confidence: 99%

Machine Learning–Based Discovery of a Gene Expression Signature in Pediatric Acute Respiratory Distress Syndrome

Grunwell

Rad

Stephenson

et al. 2021

Critical Care Explorations

View full text Add to dashboard Cite

show abstract

Section: Methodsmentioning

confidence: 99%

Machine Learning–Based Discovery of a Gene Expression Signature in Pediatric Acute Respiratory Distress Syndrome

Grunwell

Rad

Stephenson

et al. 2021

Critical Care Explorations

View full text Add to dashboard Cite

show abstract

“…The PANEV (Pathway Network Visualizer) tool [ 168 ] was extensively used to visualize the results in a context of gene/pathway networks, and pinpoint candidate genes associated with a subset of pathways of interest. Briefly, PANEV is an R package set for gene/pathway-based network visualization.…”

Section: Methodsmentioning

confidence: 99%

Unique adaptations in neonatal hepatic transcriptome, nutrient signaling, and one-carbon metabolism in response to feeding ethyl cellulose rumen-protected methionine during late-gestation in Holstein cows

et al. 2021

Self Cite

View full text Add to dashboard Cite

Background Methionine (Met) supply during late-pregnancy enhances fetal development in utero and leads to greater rates of growth during the neonatal period. Due to its central role in coordinating nutrient and one-carbon metabolism along with immune responses of the newborn, the liver could be a key target of the programming effects induced by dietary methyl donors such as Met. To address this hypothesis, liver biopsies from 4-day old calves (n = 6/group) born to Holstein cows fed a control or the control plus ethyl-cellulose rumen-protected Met for the last 28 days prepartum were used for DNA methylation, transcriptome, metabolome, proteome, and one-carbon metabolism enzyme activities. Results Although greater withers and hip height at birth in Met calves indicated better development in utero, there were no differences in plasma systemic physiological indicators. RNA-seq along with bioinformatics and transcription factor regulator analyses revealed broad alterations in ‘Glucose metabolism’, ‘Lipid metabolism, ‘Glutathione’, and ‘Immune System’ metabolism due to enhanced maternal Met supply. Greater insulin sensitivity assessed via proteomics, and efficiency of transsulfuration pathway activity suggested beneficial effects on nutrient metabolism and metabolic-related stress. Maternal Met supply contributed to greater phosphatidylcholine synthesis in calf liver, with a role in very low density lipoprotein secretion as a mechanism to balance metabolic fates of fatty acids arising from the diet or adipose-depot lipolysis. Despite a lack of effect on hepatic amino acid (AA) transport, a reduction in metabolism of essential AA within the liver indicated an AA ‘sparing effect’ induced by maternal Met. Conclusions Despite greater global DNA methylation, maternal Met supply resulted in distinct alterations of hepatic transcriptome, proteome, and metabolome profiles after birth. Data underscored an effect on maintenance of calf hepatic Met homeostasis, glutathione, phosphatidylcholine and taurine synthesis along with greater efficiency of nutrient metabolism and immune responses. Transcription regulators such as FOXO1, PPARG, E2F1, and CREB1 appeared central in the coordination of effects induced by maternal Met. Overall, maternal Met supply induced better immunometabolic status of the newborn liver, conferring the calf a physiologic advantage during a period of metabolic stress and suboptimal immunocompetence.

show abstract

“…GO is a term used to describe the features of genes and gene products, including three parts: BP, cellular component (CC), and molecular function (MF) [13]. KEGG is a gene product analysis in cellular metabolic pathways and often used to analyze metabolic pathways [14]. In this study, to clarify the biological functions of DEGs, based on the DAVID (https://david.ncifcrf.gov/), we performed enrichment analysis of DEGs in GO and KEGG.…”

Section: Enrichment Analysis Of Go Term and Kegg Pathways Of Degsmentioning

confidence: 99%

The Identification of Key Genes and Biological Pathways in Heart Failure by Integrated Bioinformatics Analysis

Yang

Bai

et al. 2021

Computational and Mathematical Methods in Medicine

View full text Add to dashboard Cite

Purpose. Heart failure (HF) is a clinical syndrome caused by ventricular insufficiency. In order to further explore the biomarkers related to HF, we apply the high-throughput database. Materials and Methods. The GSE21610 was applied for the differentially expressed gene (DEG) analysis. The Database for Annotation, Visualization, and Integrated Discovery (DAVID) was performed to assess Gene ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses. The Gene Set Enrichment Analysis (GSEA) was used for gene expression profile GSE21610. The Protein-Protein Interaction (PPI) network and modules were also constructed for research. These hub gene function pathways were estimated in HF progression. Result. We have identified 434 DEGs in total, including 304 downregulated DEGs and 130 upregulated DEGs. GO and KEGG illustrated that DEGs in HF were significantly enriched in G protein-coupled receptor binding, peroxisome, and cAMP signaling pathway. GSEA results showed gene set GSE21610 was gathered in lipid digestion, defense response to fungus, and intestinal lipid absorption. Finally, through analyzing the PPI network, we screened hub genes CDH1, TFRC, CCL2, BUB1B, and CD19 by the Cytoscape software. Conclusion. This study uses a series of bioinformatics technologies to obtain hug genes and key pathways related to HF. These analysis results provide us with new ideas for finding biomarkers and treatment methods for HF.

show abstract

PANEV: an R package for a pathway-based network visualization

Cited by 16 publications

References 38 publications

Machine Learning–Based Discovery of a Gene Expression Signature in Pediatric Acute Respiratory Distress Syndrome

Machine Learning–Based Discovery of a Gene Expression Signature in Pediatric Acute Respiratory Distress Syndrome

Unique adaptations in neonatal hepatic transcriptome, nutrient signaling, and one-carbon metabolism in response to feeding ethyl cellulose rumen-protected methionine during late-gestation in Holstein cows

The Identification of Key Genes and Biological Pathways in Heart Failure by Integrated Bioinformatics Analysis

Contact Info

Product

Resources

About