CompositeView: A Network-Based Visualization Tool

Allegri, Stephen A.; Mccoy, Kevin; Mitchell, Cassie S.

doi:10.3390/bdcc6020066

Cited by 6 publications

(6 citation statements)

References 43 publications

(42 reference statements)

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“…The architecture is flexible, and input data can be genes, proteins, chemicals, or enzymes [28]. CompositeView has many similarities to Cytoscape and has been successfully implemented and customized to examine SemNet or SemNet 2.0 results [29].…”

Section: Discussionmentioning

confidence: 99%

Cross-Domain Text Mining of Pathophysiological Processes Associated with Diabetic Kidney Disease

Patidar,

Deng,

Mitchell

et al. 2024

Preprint

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Diabetic kidney disease (DKD) remains a significant burden on the healthcare system and is the leading cause of end-stage renal disease worldwide. The pathophysiology of DKD is multifactorial and characterized by various early signs of metabolic impairment, inflammatory biomarkers, and complex pathways that lead to progressive kidney damage. New treatment prospects rely on a comprehensive understanding of disease pathology. The study aimed to identify signaling drivers and pathways that modulate glomerular endothelial dysfunction in DKD via cross-domain text mining with SemNet 2.0. The open-source literature-based discovery approach, SemNet 2.0, leverages the power of text mining 33+ million PubMed articles to provide integrative insight into multiscalar and multifactorial pathophysiology. A set of identified relevant genes and proteins that regulate different pathological events associated with DKD were analyzed and ranked using normalized mean HeteSim scores. High-ranking genes and proteins intersecting three domains\textemdash DKD, immune response, and glomerular endothelial cells\textemdash were analyzed. The top 10$\%$ of ranked concepts mapped to the following biological functions: angiotensin, apoptosis, cell-cell function, cell adhesion, chemotaxis, growth factor signaling, vascular permeability, nitric oxide response, oxidative stress, cytokine response, macrophage signaling, NF$\upkappa$B factor activity, TLR signaling, glucose metabolism, inflammatory response, ERK/MAPK signaling, JAK/STAT signaling, T-cell mediated response, WNT signaling, renin angiotensin system, and NADPH response. High-ranking genes and proteins were used to generate a protein-protein interaction network. This comprehensive analysis identified testable hypotheses for interactions or molecules involved with dysregulated signaling in DKD, which can be further studied through biochemical network models.

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Section: Discussionmentioning

confidence: 99%

Cross-Domain Text Mining of Pathophysiological Processes Associated with Diabetic Kidney Disease

Patidar,

Deng,

Mitchell

et al. 2024

Preprint

Self Cite

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“…There are various open-source and paid alternatives to Cytoscape, including Gephi [76], Tableau [77], NodeXL [78], and Neo4j [79], which can be used to visualize data obtained from text mining techniques. CompositeView has many similarities to Cytoscape and has been successfully implemented and customized to examine SemNet and SemNet 2.0 results [80]. A detailed comparison of the strengths and limitations of CompositeView against other similar software has been provided previously [80].…”

Section: Visualization Of Literature-based Discovery Network Predictionsmentioning

confidence: 99%

“…CompositeView has many similarities to Cytoscape and has been successfully implemented and customized to examine SemNet and SemNet 2.0 results [80]. A detailed comparison of the strengths and limitations of CompositeView against other similar software has been provided previously [80].…”

Section: Visualization Of Literature-based Discovery Network Predictionsmentioning

confidence: 99%

Cross-Domain Text Mining of Pathophysiological Processes Associated with Diabetic Kidney Disease

Patidar,

Deng,

Mitchell

et al. 2024

IJMS

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Diabetic kidney disease (DKD) is the leading cause of end-stage renal disease worldwide. This study’s goal was to identify the signaling drivers and pathways that modulate glomerular endothelial dysfunction in DKD via artificial intelligence-enabled literature-based discovery. Cross-domain text mining of 33+ million PubMed articles was performed with SemNet 2.0 to identify and rank multi-scalar and multi-factorial pathophysiological concepts related to DKD. A set of identified relevant genes and proteins that regulate different pathological events associated with DKD were analyzed and ranked using normalized mean HeteSim scores. High-ranking genes and proteins intersected three domains—DKD, the immune response, and glomerular endothelial cells. The top 10% of ranked concepts were mapped to the following biological functions: angiogenesis, apoptotic processes, cell adhesion, chemotaxis, growth factor signaling, vascular permeability, the nitric oxide response, oxidative stress, the cytokine response, macrophage signaling, NFκB factor activity, the TLR pathway, glucose metabolism, the inflammatory response, the ERK/MAPK signaling response, the JAK/STAT pathway, the T-cell-mediated response, the WNT/β-catenin pathway, the renin–angiotensin system, and NADPH oxidase activity. High-ranking genes and proteins were used to generate a protein–protein interaction network. The study results prioritized interactions or molecules involved in dysregulated signaling in DKD, which can be further assessed through biochemical network models or experiments.

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“…Allegri et al 67 designed and developed a new network-based visualization tool called CompositeView, an open-source application developed in Python. It mainly improves the visualization and extraction of complex interactive networks, increasing the chances of obtaining actionable insights.…”

Section: Network Visualizationmentioning

confidence: 99%

An investigation into various visualization tools for complex biological networks

Alzahrani,

Fernstad

2023

Information Visualization

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Network biology has become crucial to understanding the complex structural characteristics of biological systems. Consequently, advanced visualization approaches are needed to support the investigation of such structures, and several network visualization tools have subsequently been developed to help researchers analyze intricate biological networks. While these tools support a range of analytical and interactive features, it is sometimes unclear to a data analyst or visualization designer which features are of most relevance to biologists. Thus, this study investigates and identifies essential factors for the visualization of complex biological networks using a mixed methodology approach. Based on the findings, essential factors were categorized as either generic and heuristic, where the former concern different analytical and interactive functionalities, such as an efficient layout, advanced search capabilities, plugin availability, graph analysis and user-friendliness, while the latter concern usability, such as information coding, flexibility, orientation and help.1 Furthermore, the findings indicate that 12 of the 15 generic factors identified were moderately important, while all 10 heuristic factors identified herein were moderately important.

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CompositeView: A Network-Based Visualization Tool

Cited by 6 publications

References 43 publications

Cross-Domain Text Mining of Pathophysiological Processes Associated with Diabetic Kidney Disease

Cross-Domain Text Mining of Pathophysiological Processes Associated with Diabetic Kidney Disease

Cross-Domain Text Mining of Pathophysiological Processes Associated with Diabetic Kidney Disease

An investigation into various visualization tools for complex biological networks

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