New methods for network visualizations enable change of perspectives and
views
Date:
February 24, 2022
Source:
CeMM Research Center for Molecular Medicine of the Austrian Academy
of Sciences
Summary:
Researchers have developed a new method for generating network
layouts that allow for visualizing different information of a
network in two- and three-dimensional virtual space and exploring
different perspectives. The results could also facilitate
future research on rare diseases by providing more versatile,
comprehensible representations of complex protein interactions.
FULL STORY ==========================================================================
When visualizing data using networks, the type of representation
is crucial for extracting hidden information and relationships. The
research group of Jo"rg Menche, Adjunct Principal Investigator at the
CeMM Research Center for Molecular Medicine of the Austrian Academy
of Sciences, Professor at the University of Vienna, and Group leader
at Max Perutz Labs, developed a new method for generating network
layouts that allow for visualizing different information of a network
in two- and three-dimensional virtual space and exploring different perspectives. The results could also facilitate future research on rare diseases by providing more versatile, comprehensible representations of
complex protein interactions.
========================================================================== Network visualizations allow for exploring connections between individual
data points. However, the more complex and larger the networks, the more difficult it becomes to find the information you are looking for. For
lack of suitable layouts, so-called "hairballs" visualizations emerge,
that often obscure network structure, rather than elucidate it. Scientists
from Jo"rg Menche's research group at CeMM and Max Perutz Labs (a joint
venture of the University of Vienna and the Medical University of Vienna), developed a method that makes it possible to specify in advance which
network properties and information should be visually represented in
order to explore them interactively. The results have now been published
in Nature Computational Science.
Reducing complexity For the study, first author Christiane V. R. Hu"tter,
a PhD student in Joerg Menche's research group, used the latest
dimensionality reduction techniques that allow visualizations for networks
with thousands of points to be computed within a very short time on
a standard laptop. "The key idea behind our research was to develop
different views for large networks to capture the complexity and get a
more comprehensive view and present it in a visually understandable way -- similar to looking at maps of the same region with different information content, detailed views and perspectives." Menche Lab scientists developed
four different network layouts, which they termed cartographs, as well as
two- and three-dimensional visualizations, each following different rules
to open up new perspectives on a given dataset. Any network information
can be encoded and visualized in this fashion, for example, the structural significance of a particular point, but also functional features. Users
can switch between different layouts to get a comprehensive picture. Study leader Jo"rg Menche explains: "Using the new layouts, we can now
specify in advance that we want to see, for example, the number of
connections of a point within the network represented, or a particular functional characteristic. In a biological network, for instance, I can
explore connections between genes that are associated with a particular
disease and what they might have in common." The interplay of genes The scientists performed a proof-of-concept on both simple model networks
and the complex interactome network, which maps all the proteins of the
human body and their interactions. This consists of more than 16,000
points and over 300,000 connections. Christiane V.R. Hu"tter explains:
"Using our new layouts, we are now able to visually represent different features of proteins and their connections, such as the close relationship between the biological importance of a protein and its centrality within
the network. We can also visualize connection patterns between a group of proteins associated with the same disease that are difficult to decipher
using conventional methods." Tailored solutions The flexibility of
the new framework allows users to tailor network visualizations for
a specific application. For example, the study authors were able to
develop 3D interactome layouts specifically for studying the biological functions of certain genes whose mutations are suspected to cause rare diseases. Jo"rg Menche adds, "To facilitate the visual representation
and also analysis of large networks such as the interactome,
our layouts can also be integrated into a virtual reality platform." ========================================================================== Story Source: Materials provided by CeMM_Research_Center_for_Molecular_Medicine_of_the Austrian_Academy_of_Sciences. Note: Content may be edited for style
and length.
========================================================================== Journal Reference:
1. Christiane V. R. Hu"tter, Celine Sin, Felix Mu"ller, Jo"rg Menche.
Network cartographs for interpretable visualizations. Nature
Computational Science, 2022; DOI: 10.1038/s43588-022-00199-z ==========================================================================
Link to news story:
https://www.sciencedaily.com/releases/2022/02/220224112645.htm
--- up 11 weeks, 5 days, 7 hours, 13 minutes
* Origin: -=> Castle Rock BBS <=- Now Husky HPT Powered! (1:317/3)