Evidence map›Paper›PMID 23906711›Full record

ReviewCold Spring Harbor perspectives in biology2013

Complexity of receptor tyrosine kinase signal processing.

Natalia Volinsky, Boris N Kholodenko

Abstract readReview
In one paragraph

Review in Cold Spring Harbor perspectives in biology, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 49 papers.

0numbers the graph read from it
0cells of the map it votes in
49citing 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

49 citing papers in PubMed.

  1. Review
  2. Article
  3. Review
  4. Article
  5. Article
  6. Article
  7. Article
  8. Review
  9. Article
  10. Towards the Idea of Molecular Brains.International journal of molecular sciences · 2021
    Review
  11. Review
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Targeting Phosphatases and Kinases: How to Checkmate Cancer.Frontiers in cell and developmental biology · 2021
    Review
  18. Emerging RAS-directed therapies for cancer.Cancer drug resistance (Alhambra, Calif.) · 2021
    Review
  19. Article
  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.

Natalia VolinskySystems Biology Ireland, University College Dublin, Belfield, Dublin 4, Ireland.
Boris N Kholodenko

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Our knowledge of molecular mechanisms of receptor tyrosine kinase (RTK) signaling advances with ever-increasing pace. Yet our understanding of how the spatiotemporal dynamics of RTK signaling control specific cellular outcomes has lagged behind. Systems-centered experimental and computational approaches can help reveal how overlapping networks of signal transducers downstream of RTKs orchestrate specific cell-fate decisions. We discuss how RTK network regulatory structures, which involve the immediate posttranslational and delayed transcriptional controls by multiple feed forward and feedback loops together with pathway cross talk, adapt cells to the combinatorial variety of external cues and conditions. This intricate network circuitry endows cells with emerging capabilities for RTK signal processing and decoding. We illustrate how mathematical modeling facilitates our understanding of RTK network behaviors by unraveling specific systems properties, including bistability, oscillations, excitable responses, and generation of intricate landscapes of signaling activities.

Indexed as

Models, BiologicalFeedback, PhysiologicalGene Expression Regulation, EnzymologicGene Regulatory NetworksReceptor Cross-TalkReceptor Protein-Tyrosine KinasesSignal TransductionSystems BiologyReceptor Protein-Tyrosine Kinases

Identifiers

PMID23906711
PMCPMC3721286

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.