Evidence map›Paper›PMID 31602314›Full record

ReviewNPJ systems biology and applications2019

ModelBricks-modules for reproducible modeling improving model annotation and provenance.

Ann E Cowan, Pedro Mendes, Michael L Blinov

Abstract readReview
In one paragraph

Review in NPJ systems biology and applications, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

9 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. An automated model annotation system (AMAS) for SBML models.Bioinformatics (Oxford, England) · 2023
    Article
  5. Article
  6. Article
  7. Article
  8. Publishing reproducible dynamic kinetic models.Briefings in bioinformatics · 2021
    Article
  9. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Ann E Cowan1Center for Cell Analysis and Modeling, UConn Health, Farmington, CT USA.ORCID 0000-0002-3215-9951
Pedro Mendes1Center for Cell Analysis and Modeling, UConn Health, Farmington, CT USA.ORCID 0000-0001-6507-9168
Michael L Blinov1Center for Cell Analysis and Modeling, UConn Health, Farmington, CT USA.ORCID 0000-0002-9363-9705

Funding

TR&D4 Spatial Modeling: Modeling Framework for Cell MotilityP41GM103313 · NIGMS · UNIVERSITY OF CONNECTICUT SCH OF MED/DNT · PI LOEW, LESLIE M · 2012 to 2018
$9.7M
COPASI software for modeling and simulation of biochemical networksR01GM080219 · NIGMS · VIRGINIA POLYTECHNIC INST AND ST UNIV · PI HOOPS, STEFAN, MENDES, PEDRO · 2007 to 2019
$5.4M
Bringing BioNetGen Rule-Based Modeling to Virtual Cell UsersR01GM095485 · NIGMS · UNIVERSITY OF CONNECTICUT SCH OF MED/DNT · PI BLINOV, MICHAEL, MORARU, ION I. · 2011 to 2013
$867k
The Virtual Cell: a Computational Resource for Collaborative Modeling and Simulation of Cell BiologyR24GM134211 · NIGMS · UNIVERSITY OF CONNECTICUT SCH OF MED/DNT · PI LOEW, LESLIE M · 2019 to 2019
$528k
NIGMS NIH HHS P41 GM103313NIGMS NIH HHS R01 GM080219NIGMS NIH HHS R01 GM095485NIGMS NIH HHS R24 GM134211
6 · The paper itself

Abstract

Most computational models in biology are built and intended for "single-use"; the lack of appropriate annotation creates models where the assumptions are unknown, and model elements are not uniquely identified. Simply recreating a simulation result from a publication can be daunting; expanding models to new and more complex situations is a herculean task. As a result, new models are almost always created anew, repeating literature searches for kinetic parameters, initial conditions and modeling specifics. It is akin to building a brick house starting with a pile of clay. Here we discuss a concept for building annotated, reusable models, by starting with small well-annotated modules we call ModelBricks. Curated ModelBricks, accessible through an open database, could be used to construct new models that will inherit ModelBricks annotations and thus be easier to understand and reuse. Key features of ModelBricks include reliance on a commonly used standard language (SBML), rule-based specification describing species as a collection of uniquely identifiable molecules, association with model specific numerical parameters, and more common annotations. Physical bricks can vary substantively; likewise, to be useful the structure of ModelBricks must be highly flexible-it should encapsulate mechanisms from single reactions to multiple reactions in a complex process. Ultimately, a modeler would be able to construct large models by using multiple ModelBricks, preserving annotations and provenance of model elements, resulting in a highly annotated model. We envision the library of ModelBricks to rapidly grow from community contributions. Persistent citable references will incentivize model creators to contribute new ModelBricks.

Indexed as

Computational BiologyComputer SimulationDatabases, FactualModels, BiologicalSoftwareSystems BiologyComplexityComputer modellingModularitySoftware

Identifiers

PMID31602314
PMCPMC6783478

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.