Interactive Multiresolution Visualization of Cellular Network Processes

Abstract

SummaryVisualization plays a central role in the analysis of biochemical network models to identify patterns that arise from reaction dynamics and perform model exploratory analysis. To facilitate these analyses, we developed PyViPR, a visualization tool that generates static and dynamic representations of biochemical network processes within a Python-based environment. PyViPR embeds network visualizations within Jupyter notebooks, thus enabling integration with modeling, simulation, and analysis workflows. To present the capabilities of PyViPR, we explore execution mechanisms of extrinsic apoptosis in HeLa cells. We show that community-detection algorithms identify groups of molecular species that capture key biological functions and ease exploration of the apoptosis network. We then show how different kinetic parameter sets that fit the experimental data equally well exhibit significantly different signal-execution dynamics as the system progresses toward mitochondrial outer-membrane permeabilization. Therefore, PyViPR aids the conceptual understanding of dynamic network processes and accelerates hypothesis generation for further testing and validation.

Atlas: automatic modeling of regulation of bacterial gene expression and metabolism using rule-based languages

“…Complementarily, Atlas provides utilitarian functions that are able to read and check the different networks, analyze the connectivity of the model and obtain data from the BioCyc databases ( Caspi et al , 2016 ; Karp et al , 2018a ). Data could be transformed and exported for visualization with Cytoscape ( Shannon et al , 2003 ; Su et al , 2014 ) and models could be visualized within Jupyter notebooks with pyViPR ( Ortega and Lopez, 2020 ).…”

“…The co-expression and other networks were visualized with the software Cytoscape v3.7.2 ( Shannon et al , 2003 ; Su et al , 2014 ) and models were visualized within Jupyter notebooks with the software pyViPR ( Ortega and Lopez, 2020 ).…”

Programmatic modeling for biological systems

“…Network visualization is perhaps the other major area of model analysis that is addressed in various ways in Python. For example, PyVIPR [58*] is a visualization tool built on Cytoscape.js [59] for rule- and reaction-based models which animates model dynamics over time, overlaid on a graph. MASSPy [60] also provides some visualization capabilities for metabolic models.…”

Multi-resolution visualization and analysis of biomolecular networks through hierarchical community detection and web-based graphical tools

“…multi-resolution visualizations of cellular network processes [36] and biological pathways [37]. However, their focus is mainly centered on the rendering of the communities on the canvas, whereas our focus is on the data and indexing structures adopted for easily retrieving and preparing big graphs to be rendered.…”

“…Divisive methods often poorly scales on large-sized networks, due to the computation of heavy measures to detect “hot” edges like the edge betweenness, whereas the approach [ 33 ] has too many (hyper)parameters to be tuned, making it impracticable for our purpose, having our web-interface the need of providing fast responses to user requests. Approaches and systems for the visual exploration of the hierarchical communities have been proposed [ 34 , 35 ] as well as multi-resolution visualizations of cellular network processes [ 36 ] and biological pathways [ 37 ]. However, their focus is mainly centered on the rendering of the communities on the canvas, whereas our focus is on the data and indexing structures adopted for easily retrieving and preparing big graphs to be rendered.…”