Evidence map›Paper›PMID 26716837›Full record

ArticlePloS one2015

Semantics-Based Composition of Integrated Cardiomyocyte Models Motivated by Real-World Use Cases.

Maxwell L Neal, Brian E Carlson, Christopher T Thompson, Ryan C James, Karam G Kim, Kenneth Tran, Edmund J Crampin, Daniel L Cook, John H Gennari

Abstract read
In one paragraph

Article in PloS one, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing 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

15 citing papers in PubMed.

  1. Article
  2. Article
  3. Analysing and simulating energy-based models in biology using BondGraphTools.The European physical journal. E, Soft matter · 2021
    Article
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  9. Review
  10. Review
  11. Article
  12. CropsFrontiers in plant science · 2017
    Article
  13. Modular modelling with Physiome standards.The Journal of physiology · 2016
    Article
  14. Article
  15. Article
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

9 authors.

Maxwell L NealDepartment of Biomedical Informatics and Medical Education, University of Washington, Seattle, Washington, United States of America.
Brian E CarlsonDepartment of Molecular and Integrative Physiology, University of Michigan, Ann Arbor, MI, United States of America.
Christopher T ThompsonDepartment of Molecular and Integrative Physiology, University of Michigan, Ann Arbor, MI, United States of America.
Ryan C JamesDepartment of Biomedical Informatics and Medical Education, University of Washington, Seattle, Washington, United States of America.
Karam G KimDepartment of Biomedical Informatics and Medical Education, University of Washington, Seattle, Washington, United States of America.
Kenneth TranAuckland Bioengineering Institute, The University of Auckland, Auckland, New Zealand.
Edmund J CrampinSystems Biology Laboratory, Melbourne School of Engineering, University of Melbourne, Victoria, Australia.
Daniel L CookDepartment of Physiology and Biophysics, University of Washington, Seattle, WA, United States of America.
John H GennariDepartment of Biomedical Informatics and Medical Education, University of Washington, Seattle, Washington, United States of America.

Funding

University of Washington Biomedical Informatics and Data Science Research Training ProgramT15LM007442 · NLM · UNIVERSITY OF WASHINGTON · PI JOHN H. GENNARI, Andrea L. Hartzler · 2002 to 2026
$19.6M
The Virtual Physiological Rat ProjectP50GM094503 · NIGMS · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI BEARD, DANIEL A · 2011 to 2015
$11.6M
Physiological Knowledge Integration and Recombinant Modeling Via Accelerated SemaR01LM011969 · NLM · UNIVERSITY OF WASHINGTON · PI CARLSON, BRIAN E., GENNARI, JOHN H. · 2014 to 2017
$1.7M
NIGMS NIH HHS P50 GM094503NIGMS NIH HHS P50GM094503NLM NIH HHS R01 LM011969NLM NIH HHS R01LM011969NLM NIH HHS T15 LM007442NLM NIH HHS T15LM007442
6 · The paper itself

Abstract

Semantics-based model composition is an approach for generating complex biosimulation models from existing components that relies on capturing the biological meaning of model elements in a machine-readable fashion. This approach allows the user to work at the biological rather than computational level of abstraction and helps minimize the amount of manual effort required for model composition. To support this compositional approach, we have developed the SemGen software, and here report on SemGen's semantics-based merging capabilities using real-world modeling use cases. We successfully reproduced a large, manually-encoded, multi-model merge: the "Pandit-Hinch-Niederer" (PHN) cardiomyocyte excitation-contraction model, previously developed using CellML. We describe our approach for annotating the three component models used in the PHN composition and for merging them at the biological level of abstraction within SemGen. We demonstrate that we were able to reproduce the original PHN model results in a semi-automated, semantics-based fashion and also rapidly generate a second, novel cardiomyocyte model composed using an alternative, independently-developed tension generation component. We discuss the time-saving features of our compositional approach in the context of these merging exercises, the limitations we encountered, and potential solutions for enhancing the approach.

Indexed as

Models, BiologicalModels, TheoreticalSemanticsComputational BiologyComputer SimulationDatabases, FactualMyocytes, CardiacSoftware

Identifiers

PMID26716837
PMCPMC4696653

What OpenQuestion holds

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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.