NetMatchStar: an enhanced Cytoscape network querying app

Rinnone, Fabio; Micale, Giovanni; Bonnici, Vincenzo; Bader, Gary D.; Shasha, Dennis; Ferro, Alfredo; Pulvirenti, Alfredo; Giugno, Rosalba

doi:10.12688/f1000research.6656.1

Cited by 14 publications

(4 citation statements)

References 45 publications

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“…All motifs were significantly enriched in the SCN GRN relative to a randomly generated network of the same size. First, the number of times a gene appeared in each motif was counted using the NetMatchStar app 46 in Cytoscape. Then, the counts were normalized to a scale from 0 to 1 and summed to calculate the NMS for each gene.…”

Section: Methodsmentioning

confidence: 99%

Stem-cell-ubiquitous genes spatiotemporally coordinate division through regulation of stem-cell-specific gene networks

et al. 2019

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Stem cells are responsible for generating all of the differentiated cells, tissues, and organs in a multicellular organism and, thus, play a crucial role in cell renewal, regeneration, and organization. A number of stem cell type-specific genes have a known role in stem cell maintenance, identity, and/or division. Yet, how genes expressed across different stem cell types, referred to here as stem-cell-ubiquitous genes, contribute to stem cell regulation is less understood. Here, we find that, in the Arabidopsis root, a stem-cell-ubiquitous gene, TESMIN-LIKE CXC2 (TCX2), controls stem cell division by regulating stem cell-type specific networks. Development of a mathematical model of TCX2 expression allows us to show that TCX2 orchestrates the coordinated division of different stem cell types. Our results highlight that genes expressed across different stem cell types ensure cross-communication among cells, allowing them to divide and develop harmonically together.

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Section: Methodsmentioning

confidence: 99%

Stem-cell-ubiquitous genes spatiotemporally coordinate division through regulation of stem-cell-specific gene networks

et al. 2019

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“…In this context, the identified top module was further queried for biologically relevant regulatory subunits through the utilization of motif identification approaches. The PPI data were retrieved from the STRING database version 11.5 [ 18 ], and the NetMatchStar plug-in in the Cytoscape [ 19 ] was used to identify triangle motifs with three nodes and three edges. The choice of the triangle motifs was based on the high frequency with which they are observed in the biological systems and the fact that many larger motifs are comprised of multiple triangle motifs [ 20 ].…”

Section: Methodsmentioning

confidence: 99%

Network-Based and Machine-Learning Approaches Identify Diagnostic and Prognostic Models for EMT-Type Gastric Tumors

Sadeghi

Karimi

et al. 2023

Genes

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The microsatellite stable/epithelial-mesenchymal transition (MSS/EMT) subtype of gastric cancer represents a highly aggressive class of tumors associated with low rates of survival and considerably high probabilities of recurrence. In the era of precision medicine, the accurate and prompt diagnosis of tumors of this subtype is of vital importance. In this study, we used Weighted Gene Co-expression Network Analysis (WGCNA) to identify a differentially expressed co-expression module of mRNAs in EMT-type gastric tumors. Using network analysis and linear discriminant analysis, we identified mRNA motifs and microRNA-based models with strong prognostic and diagnostic relevance: three models comprised of (i) the microRNAs miR-199a-5p and miR-141-3p, (ii) EVC/EVC2/GLI3, and (iii) PDE2A/GUCY1A1/GUCY1B1 gene expression profiles distinguish EMT-type tumors from other gastric tumors with high accuracy (Area Under the Receiver Operating Characteristic Curve (AUC) = 0.995, AUC = 0.9742, and AUC = 0.9717; respectively). Additionally, the DMD/ITGA1/CAV1 motif was identified as the top motif with consistent relevance to prognosis (hazard ratio > 3). Molecular functions of the members of the identified models highlight the central roles of MAPK, Hh, and cGMP/cAMP signaling in the pathology of the EMT subtype of gastric cancer and underscore their potential utility in precision therapeutic approaches.

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“…We use the NetMatchStar plugin [39] in Cytoscape [40] to search the integrated network for the two types of miRScoPPI motifs. Finally, we merge the identified miRSCoPPI motifs to obtain the BRCA-related miRSCoPPI network.…”

Section: Methodsmentioning

confidence: 99%

Inferring miRNA sponge co-regulation of protein-protein interactions in human breast cancer

Zhang

Liu

et al. 2017

BMC Bioinformatics

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BackgroundRecent studies have shown that the crosstalk between microRNA (miRNA) sponges plays an important role in human cancers. However, the co-regulation roles of miRNA sponges in protein-protein interactions (PPIs) are still unknown.ResultsIn this study, we propose a multi-step method called miRSCoPPI to infer miRNA sponge co-regulation of PPIs. We focus on investigating breast cancer (BRCA) related miRNA sponge co-regulation, by integrating heterogeneous data, including miRNA, long non-coding RNA (lncRNA) and messenger RNA (mRNA) expression data, experimentally validated miRNA-target interactions, PPIs and lncRNA-target interactions, and the list of breast cancer genes. We find that the inferred BRCA-related miRSCoPPI network is highly connected and scale free. The top 10% hub genes in the BRCA-related miRSCoPPI network have potential biological implications in breast cancer. By utilizing a graph clustering method, we discover 17 BRCA-related miRSCoPPI modules. Through pathway enrichment analysis of the modules, we find that several modules are significantly enriched in pathways associated with breast cancer. Moreover, 10 modules have good performance in classifying breast tumor and normal samples, and can act as module signatures for prognostication. By using putative computationally predicted miRNA-target interactions, we have consistent results with those obtained using experimentally validated miRNA-target interactions, indicating that miRSCoPPI is robust in inferring miRNA sponge co-regulation of PPIs in human breast cancer.ConclusionsTaken together, the results demonstrate that miRSCoPPI is a promising tool for inferring BRCA-related miRNA sponge co-regulation of PPIs and it can help with the understanding of the co-regulation roles of miRNA sponges on the PPIs.Electronic supplementary materialThe online version of this article (doi:10.1186/s12859-017-1672-2) contains supplementary material, which is available to authorized users.

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NetMatchStar: an enhanced Cytoscape network querying app

Cited by 14 publications

References 45 publications

Stem-cell-ubiquitous genes spatiotemporally coordinate division through regulation of stem-cell-specific gene networks

Stem-cell-ubiquitous genes spatiotemporally coordinate division through regulation of stem-cell-specific gene networks

Network-Based and Machine-Learning Approaches Identify Diagnostic and Prognostic Models for EMT-Type Gastric Tumors

Inferring miRNA sponge co-regulation of protein-protein interactions in human breast cancer

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