ArticleBMC bioinformatics2014
MOSBIE: a tool for comparison and analysis of rule-based biochemical models.
Article in BMC bioinformatics, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
9 citing papers in PubMed.
- Roses Have Thorns: Understanding the Downside of Oncological Care Delivery Through Visual Analytics and Sequential Rule Mining.IEEE transactions on visualization and computer graphics · 2024Article
- Explainable Spatial Clustering: Leveraging Spatial Data in Radiation Oncology.IEEE Visualization Conference : VIS. IEEE Conference on Visualization · 2020Article
- Cohort-based T-SSIM Visual Computing for Radiation Therapy Prediction and Exploration.IEEE transactions on visualization and computer graphics · 2020Article
- A spatial neighborhood methodology for computing and analyzing lymph node carcinoma similarity in precision medicine.Journal of biomedical informatics · 2020Article
- Modeling heterogeneous tumor growth dynamics and cell-cell interactions at single-cell and cell-population resolution.Current opinion in systems biology · 2019Article
- Ten simple rules to create biological network figures for communication.PLoS computational biology · 2019Article
- Activity-Centered Domain Characterization for Problem-Driven Scientific Visualization.IEEE transactions on visualization and computer graphics · 2018Article
- BioNetGen 2.2: advances in rule-based modeling.Bioinformatics (Oxford, England) · 2016Article
- Modeling for (physical) biologists: an introduction to the rule-based approach.Physical biology · 2015Review
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
backgroundMechanistic models that describe the dynamical behaviors of biochemical systems are common in computational systems biology, especially in the realm of cellular signaling. The development of families of such models, either by a single research group or by different groups working within the same area, presents significant challenges that range from identifying structural similarities and differences between models to understanding how these differences affect system dynamics.
resultsWe present the development and features of an interactive model exploration system, MOSBIE, which provides utilities for identifying similarities and differences between models within a family. Models are clustered using a custom similarity metric, and a visual interface is provided that allows a researcher to interactively compare the structures of pairs of models as well as view simulation results.
conclusionsWe illustrate the usefulness of MOSBIE via two case studies in the cell signaling domain. We also present feedback provided by domain experts and discuss the benefits, as well as the limitations, of the approach.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.