ArticleBriefings in bioinformatics2018
Notions of similarity for systems biology models.
Article in Briefings in bioinformatics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed.
- A group theoretic approach to model comparison with simplicial representations.Journal of mathematical biology · 2022Article
- Evaluation of statistical approaches for association testing in noisy drug screening data.BMC bioinformatics · 2022Article
- Model comparison via simplicial complexes and persistent homology.Royal Society open science · 2021Article
- A property-response perspective on modern toxicity assessment and drug toxicity index (DTI).In silico pharmacology · 2021Review
- The changes of triacylglycerol and inflammatory factors during dialysis treatment of hypertriglyceridemia during pregnancy and analysis of nursing countermeasure.American journal of translational research · 2021Article
- SBML Level 3: an extensible format for the exchange and reuse of biological models.Molecular systems biology · 2020Review
- Harmonizing semantic annotations for computational models in biology.Briefings in bioinformatics · 2019Review
- Multi-scale stochastic organization-oriented coarse-graining exemplified on the human mitotic checkpoint.Scientific reports · 2019Article
- Network Features and Dynamical Landscape of Naive and Primed Pluripotency.Biophysical journal · 2018Article
- Identifying frequent patterns in biochemical reaction networks: a workflow.Database : the journal of biological databases and curation · 2018Article
Corrections and comments
- Erratum issued
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Systems biology models are rapidly increasing in complexity, size and numbers. When building large models, researchers rely on software tools for the retrieval, comparison, combination and merging of models, as well as for version control. These tools need to be able to quantify the differences and similarities between computational models. However, depending on the specific application, the notion of 'similarity' may greatly vary. A general notion of model similarity, applicable to various types of models, is still missing. Here we survey existing methods for the comparison of models, introduce quantitative measures for model similarity, and discuss potential applications of combined similarity measures. To frame model comparison as a general problem, we describe a theoretical approach to defining and computing similarities based on a combination of different model aspects. The six aspects that we define as potentially relevant for similarity are underlying encoding, references to biological entities, quantitative behaviour, qualitative behaviour, mathematical equations and parameters and network structure. We argue that future similarity measures will benefit from combining these model aspects in flexible, problem-specific ways to mimic users' intuition about model similarity, and to support complex model searches in databases.
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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.