Contextual Hub Analysis Tool (CHAT): A Cytoscape app for identifying contextually relevant hubs in biological networks

@article{Muetze2016ContextualHA,
  title={Contextual Hub Analysis Tool (CHAT): A Cytoscape app for identifying contextually relevant hubs in biological networks},
  author={Tanja Muetze and Ivan H. Goenawan and Heather L. Wiencko and Manuel Bernal-Llinares and Kenneth Bryan and David J. Lynn},
  journal={F1000Research},
  year={2016},
  volume={5}
}
Highly connected nodes (hubs) in biological networks are topologically important to the structure of the network and have also been shown to be preferentially associated with a range of phenotypes of interest. The relative importance of a hub node, however, can change depending on the biological context. Here, we report a Cytoscape app, the Contextual Hub Analysis Tool (CHAT), which enables users to easily construct and visualize a network of interactions from a gene or protein list of interest… 

Figures and Tables from this paper

Using the Contextual Hub Analysis Tool (CHAT) in Cytoscape to Identify Contextually Relevant Network Hubs
TLDR
A step‐by‐step protocol for using the Contextual Hub Analysis Tool (CHAT), an application within Cytoscape 3, which enables users to easily construct and visualize a network of interactions from a gene or protein list of interest, integrate contextual information, and identify hub nodes that are more highly connected to contextual nodes than expected by chance.
In Silico Protein Interaction Network Analysis of Virulence Proteins Associated with Invasive Aspergillosis for Drug Discovery.
TLDR
Manual curation of PPI data identified three proteins of A. fumigatus possessing the highest interacting partners and targeting the hub protein as a new antifungal drug target will help in treating the invasive aspergillosis.
Bioinformatic analysis of differential expression and core GENEs in breast cancer.
TLDR
It is demonstrated that DEGs and hub genes, such as IGF1, might regulate the development of gastric cancer and could be used as new biomarkers for diagnosis and to guide the combination medicine of BRCA.
Up-regulated iNOS/NOS2 is associated with the poor prognosis of colorectal cancer: an integrated bioinformatics analysis
TLDR
iNOS/NOS2 was up-regulated in CRC and associated with poor prognosis of CRC which maybe a potential biomarker for this disease.
Immune system and zinc are associated with recurrent aphthous stomatitis. An assessment using a network-based approach.
TLDR
Molecules and processes associated with immune system recur robustly in all analyzed information and the molecular zinc ion binding function could be an area for exploring more specific and effective therapeutic interventions.
Network Approaches for Charting the Transcriptomic and Epigenetic Landscape of the Developmental Origins of Health and Disease
TLDR
This review outlines the major transcriptomic and epigenetic processes and the respective datasets that are most relevant for studying the periconceptional period and covers both basic data processing and analysis steps, as well as more advanced data integration methods.
Systems Genomics of Thigh Adipose Tissue From Asian Indian Type-2 Diabetics Revealed Distinct Protein Interaction Hubs
TLDR
The analyses comprising significant hubs suggest that thigh subcutaneous adipose tissue plays a role in pathophysiology of AIT2DM, and various clinical, biochemical, and radiological parameters which show significant correlation with distinct hubs are identified.
Molecular profiling of lymphovascular invasive cancer cells in TNBC using G&T-seq
TLDR
The findings improve the understanding of LVI metastatic mechanisms, and reveal that poor breast cancer survival outcomes may be related to the extensive down-regulation of transcripts encoding ribosomal proteins.
Peptidomics-Driven Strategy Reveals Peptides and Predicted Proteases Associated With Oral Cancer Prognosis
TLDR
This integrated pipeline provided better comprehension and discovery of molecular features with implications in the oral cancer metastasis prognosis and indicated that proteolytic activity is accentuated in the saliva of patients with OSCC and lymph-node metastasis and, at least in part, is modulated by reduced levels of salivary peptidase inhibitors.
Peptidomics-driven strategy reveals peptides and predicted proteases associated with oral cancer prognosis.
TLDR
This integrated pipeline provided better comprehension and discovery of molecular features with implications in the oral cancer metastasis prognosis and indicated that proteolytic activity is accentuated in the saliva of OSCC patients with lymph node metastasis and, at least in part, this is modulated by reduced levels of salivary peptidase inhibitors.
...
...

References

SHOWING 1-10 OF 37 REFERENCES
Revisiting Date and Party Hubs: Novel Approaches to Role Assignment in Protein Interaction Networks
TLDR
It is suggested that thinking in terms of a date/party dichotomy for hubs in protein interaction networks is not meaningful, and it might be more useful to conceive of roles for protein-protein interactions rather than for individual proteins.
Biological context networks: a mosaic view of the interactome
TLDR
This paper introduces a novel graph construct called a biological context network that explicitly captures changing patterns of interaction from one biological context to another, and shows that aggregating small process‐specific protein interaction sub‐networks leads to the emergence of observed scale‐free properties.
cytoHubba: identifying hub objects and sub-networks from complex interactome
TLDR
A novel Cytoscape plugin cytoHubba is introduced for ranking nodes in a network by their network features and the new proposed method, MCC, has a better performance on the precision of predicting essential proteins from the yeast PPI network.
Biological network analysis with CentiScaPe: centralities and experimental dataset integration
TLDR
CentiScaPe is a Cytoscape app specifically designed to calculate centrality indexes used for the identification of the most important nodes in a network, a comprehensive suite of algorithms dedicated to network nodes centrality analysis.
Cytoscape: a software environment for integrated models of biomolecular interaction networks.
TLDR
Several case studies of Cytoscape plug-ins are surveyed, including a search for interaction pathways correlating with changes in gene expression, a study of protein complexes involved in cellular recovery to DNA damage, inference of a combined physical/functional interaction network for Halobacterium, and an interface to detailed stochastic/kinetic gene regulatory models.
Computing topological parameters of biological networks
TLDR
The versatile Cytoscape plugin NetworkAnalyzer computes and displays a comprehensive set of topological parameters, which includes the number of nodes, edges, and connected components, the network diameter, radius, density, centralization, heterogeneity, and clustering coefficient, and the characteristic path length.
Topological analysis and interactive visualization of biological networks and protein structures
TLDR
This protocol describes three workflows based on the NetworkAnalyzer and RINalyzer plug-ins for Cytoscape, a popular software platform for networks, to perform a topological analysis of biological networks.
ModuleBlast: identifying activated sub-networks within and across species
TLDR
Temporal analysis of expression and interaction data from mouse, macaque and human revealed cascades of modules that are dynamically activated within and across species, leading to new insights into the mechanisms used by a key mammalian aging protein.
PhenomeExpress: A refined network analysis of expression datasets by inclusion of known disease phenotypes
TLDR
A new method for the analysis of transcriptomic datasets to identify pathogenic disease mechanisms, PhenomeExpress, which includes input from both protein-protein interaction and phenotype similarity networks and reveals how it may enhance the detection of molecular phenotypes and provide a more detailed context to those previously identified as possible candidates.
Identification of highly synchronized subnetworks from gene expression data
TLDR
Application of TopoPL to simulated data and to the yeast cell cycle data showed that it can more sensitively identify biologically meaningful subnetworks than the method that only utilizes the static PPI topology, or the additive scoring method.
...
...