82,821 research outputs found
A signaling visualization toolkit to support rational design of combination therapies and biomarker discovery: SiViT
Targeted cancer therapy aims to disrupt aberrant cellular signalling pathways. Biomarkers are surrogates of pathway state, but there is limited success in translating candidate biomarkers to clinical practice due to the intrinsic complexity of pathway networks. Systems biology approaches afford better understanding of complex, dynamical interactions in signalling pathways targeted by anticancer drugs. However, adoption of dynamical modelling by clinicians and biologists is impeded by model inaccessibility. Drawing on computer games technology, we present a novel visualisation toolkit, SiViT, that converts systems biology models of cancer cell signalling into interactive simulations that can be used without specialist computational expertise. SiViT allows clinicians and biologists to directly introduce for example loss of function mutations and specific inhibitors. SiViT animates the effects of these introductions on pathway dynamics, suggesting further experiments and assessing candidate biomarker effectiveness. In a systems biology model of Her2 signalling we experimentally validated predictions using SiViT, revealing the dynamics of biomarkers of drug resistance and highlighting the role of pathway crosstalk. No model is ever complete: the iteration of real data and simulation facilitates continued evolution of more accurate, useful models. SiViT will make accessible libraries of models to support preclinical research, combinatorial strategy design and biomarker discovery
How to understand the cell by breaking it: network analysis of gene perturbation screens
Modern high-throughput gene perturbation screens are key technologies at the
forefront of genetic research. Combined with rich phenotypic descriptors they
enable researchers to observe detailed cellular reactions to experimental
perturbations on a genome-wide scale. This review surveys the current
state-of-the-art in analyzing perturbation screens from a network point of
view. We describe approaches to make the step from the parts list to the wiring
diagram by using phenotypes for network inference and integrating them with
complementary data sources. The first part of the review describes methods to
analyze one- or low-dimensional phenotypes like viability or reporter activity;
the second part concentrates on high-dimensional phenotypes showing global
changes in cell morphology, transcriptome or proteome.Comment: Review based on ISMB 2009 tutorial; after two rounds of revisio
Differentiation Therapy Targeting the β-Catenin/CBP Interaction in Pancreatic Cancer.
BACKGROUND:Although canonical Wnt signaling is known to promote tumorigenesis in pancreatic ductal adenocarcinoma (PDAC), a cancer driven principally by mutant K-Ras, the detailed molecular mechanisms by which the Wnt effector β-catenin regulates such tumorigenesis are largely unknown. We have previously demonstrated that β-catenin's differential usage of the Kat3 transcriptional coactivator cyclic AMP-response element binding protein-binding protein (CBP) over its highly homologous coactivator p300 increases self-renewal and suppresses differentiation in other types of cancer. AIM/METHODS:To investigate Wnt-mediated carcinogenesis in PDAC, we have used the specific small molecule CBP/β-catenin antagonist, ICG-001, which our lab identified and has extensively characterized, to examine its effects in human pancreatic cancer cells and in both an orthotopic mouse model and a human patient-derived xenograft (PDX) model of PDAC. RESULTS/CONCLUSION:We report for the first time that K-Ras activation increases the CBP/β-catenin interaction in pancreatic cancer; and that ICG-001 specific antagonism of the CBP/β-catenin interaction sensitizes pancreatic cancer cells and tumors to gemcitabine treatment. These effects were associated with increases in the expression of let-7a microRNA; suppression of K-Ras and survivin; and the elimination of drug-resistant cancer stem/tumor-initiating cells
Dynamic Influence Networks for Rule-based Models
We introduce the Dynamic Influence Network (DIN), a novel visual analytics
technique for representing and analyzing rule-based models of protein-protein
interaction networks. Rule-based modeling has proved instrumental in developing
biological models that are concise, comprehensible, easily extensible, and that
mitigate the combinatorial complexity of multi-state and multi-component
biological molecules. Our technique visualizes the dynamics of these rules as
they evolve over time. Using the data produced by KaSim, an open source
stochastic simulator of rule-based models written in the Kappa language, DINs
provide a node-link diagram that represents the influence that each rule has on
the other rules. That is, rather than representing individual biological
components or types, we instead represent the rules about them (as nodes) and
the current influence of these rules (as links). Using our interactive DIN-Viz
software tool, researchers are able to query this dynamic network to find
meaningful patterns about biological processes, and to identify salient aspects
of complex rule-based models. To evaluate the effectiveness of our approach, we
investigate a simulation of a circadian clock model that illustrates the
oscillatory behavior of the KaiC protein phosphorylation cycle.Comment: Accepted to TVCG, in pres
NaviCell: a web-based environment for navigation, curation and maintenance of large molecular interaction maps
Molecular biology knowledge can be systematically represented in a
computer-readable form as a comprehensive map of molecular interactions. There
exist a number of maps of molecular interactions containing detailed
description of various cell mechanisms. It is difficult to explore these large
maps, to comment their content and to maintain them. Though there exist several
tools addressing these problems individually, the scientific community still
lacks an environment that combines these three capabilities together. NaviCell
is a web-based environment for exploiting large maps of molecular interactions,
created in CellDesigner, allowing their easy exploration, curation and
maintenance. NaviCell combines three features: (1) efficient map browsing based
on Google Maps engine; (2) semantic zooming for viewing different levels of
details or of abstraction of the map and (3) integrated web-based blog for
collecting the community feedback. NaviCell can be easily used by experts in
the field of molecular biology for studying molecular entities of their
interest in the context of signaling pathways and cross-talks between pathways
within a global signaling network. NaviCell allows both exploration of detailed
molecular mechanisms represented on the map and a more abstract view of the map
up to a top-level modular representation. NaviCell facilitates curation,
maintenance and updating the comprehensive maps of molecular interactions in an
interactive fashion due to an imbedded blogging system. NaviCell provides an
easy way to explore large-scale maps of molecular interactions, thanks to the
Google Maps and WordPress interfaces, already familiar to many users. Semantic
zooming used for navigating geographical maps is adopted for molecular maps in
NaviCell, making any level of visualization meaningful to the user. In
addition, NaviCell provides a framework for community-based map curation.Comment: 20 pages, 5 figures, submitte
eXamine: a Cytoscape app for exploring annotated modules in networks
Background. Biological networks have growing importance for the
interpretation of high-throughput "omics" data. Statistical and combinatorial
methods allow to obtain mechanistic insights through the extraction of smaller
subnetwork modules. Further enrichment analyses provide set-based annotations
of these modules.
Results. We present eXamine, a set-oriented visual analysis approach for
annotated modules that displays set membership as contours on top of a
node-link layout. Our approach extends upon Self Organizing Maps to
simultaneously lay out nodes, links, and set contours.
Conclusions. We implemented eXamine as a freely available Cytoscape app.
Using eXamine we study a module that is activated by the virally-encoded
G-protein coupled receptor US28 and formulate a novel hypothesis about its
functioning
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