Evidence map›Paper›PMID 24725073›Full record

ReviewBritish journal of clinical pharmacology2014

Understanding genetic variation - the value of systems biology.

Marc-Thorsten Hütt

Abstract readReview
In one paragraph

Review in British journal of clinical pharmacology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. The E. coli transcriptional regulatory network and its spatial embedding.The European physical journal. E, Soft matter · 2019
    Article
  6. Review
  7. Article
  8. Article
  9. Article
  10. Parsing interindividual drug variability: an emerging role for systems pharmacology.Wiley interdisciplinary reviews. Systems biology and medicine
    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

1 author.

Marc-Thorsten HüttSchool of Engineering and Science, Jacobs University Bremen, Campus Ring 1, D-28759, Bremen, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Pharmacology is currently transformed by the vast amounts of genome-associated information available for system-level interpretation. Here I review the potential of systems biology to facilitate this interpretation, thus paving the way for the emerging field of systems pharmacology. In particular, I will show how gene regulatory and metabolic networks can serve as a framework for interpreting high throughput data and as an interface to detailed dynamical models. In addition to the established connectivity analyses of effective networks, I suggest here to also analyze higher order architectural properties of effective networks.

Indexed as

Genetic VariationMetabolic Networks and PathwaysGene Expression RegulationHumansModels, BiologicalSystems Biologybiological networksmathematical modelingnonlinear dynamics

Identifiers

PMID24725073
PMCPMC3971976

What OpenQuestion holds

Textmetadata
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.