Evidence map›Paper›PMID 25538939›Full record

ReviewFrontiers in bioengineering and biotechnology2014

Improving collaboration by standardization efforts in systems biology.

Andreas Dräger, Bernhard Ø Palsson

Abstract readReview
In one paragraph

Review in Frontiers in bioengineering and biotechnology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers.

0numbers the graph read from it
0cells of the map it votes in
31citing 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

31 citing papers in PubMed.

  1. Article
  2. Towards a comprehensive assessment of QSP models: what would it take?Journal of pharmacokinetics and pharmacodynamics · 2024
    Review
  3. Article
  4. Publishing reproducible dynamic kinetic models.Briefings in bioinformatics · 2021
    Article
  5. Article
  6. Article
  7. Finding new edges: systems approaches to MTOR signaling.Biochemical Society transactions · 2021
    Review
  8. Review
  9. High-Quality Genome-Scale Reconstruction ofFrontiers in microbiology · 2021
    Article
  10. Article
  11. Review
  12. Article
  13. Article
  14. Article
  15. Article
  16. Harnessing Big Data for Systems Pharmacology.Annual review of pharmacology and toxicology · 2017
    Review
  17. Article
  18. Guidelines for Reproducibly Building and Simulating Systems Biology Models.IEEE transactions on bio-medical engineering · 2016
    Article
  19. Metabolic modeling with Big Data and the gut microbiome.Applied & translational genomics · 2016
    Review
  20. 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

2 authors.

Andreas DrägerSystems Biology Research Group, Department of Bioengineering, University of California , San Diego, La Jolla, CA , USA ; Cognitive Systems, Center for Bioinformatics Tübingen (ZBIT), Department of Computer Science, University of Tübingen , Tübingen , Germany.
Bernhard Ø PalssonSystems Biology Research Group, Department of Bioengineering, University of California , San Diego, La Jolla, CA , USA.

Funding

Continued Support of Essential SBML Software and Community ResourcesR01GM070923 · NIGMS · CALIFORNIA INSTITUTE OF TECHNOLOGY · PI HUCKA, MICHAEL · 2004 to 2018
$8.0M
NIGMS NIH HHS R01 GM070923
6 · The paper itself

Abstract

Collaborative genome-scale reconstruction endeavors of metabolic networks would not be possible without a common, standardized formal representation of these systems. The ability to precisely define biological building blocks together with their dynamic behavior has even been considered a prerequisite for upcoming synthetic biology approaches. Driven by the requirements of such ambitious research goals, standardization itself has become an active field of research on nearly all levels of granularity in biology. In addition to the originally envisaged exchange of computational models and tool interoperability, new standards have been suggested for an unambiguous graphical display of biological phenomena, to annotate, archive, as well as to rank models, and to describe execution and the outcomes of simulation experiments. The spectrum now even covers the interaction of entire neurons in the brain, three-dimensional motions, and the description of pharmacometric studies. Thereby, the mathematical description of systems and approaches for their (repeated) simulation are clearly separated from each other and also from their graphical representation. Minimum information definitions constitute guidelines and common operation protocols in order to ensure reproducibility of findings and a unified knowledge representation. Central database infrastructures have been established that provide the scientific community with persistent links from model annotations to online resources. A rich variety of open-source software tools thrives for all data formats, often supporting a multitude of programing languages. Regular meetings and workshops of developers and users lead to continuous improvement and ongoing development of these standardization efforts. This article gives a brief overview about the current state of the growing number of operation protocols, mark-up languages, graphical descriptions, and fundamental software support with relevance to systems biology.

Indexed as

model databasesmodel formatsmodeling guidelinesnetwork visualizationontologiessoftware support

Identifiers

PMID25538939
PMCPMC4259112

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.