Evidence map›Paper›PMID 22828391›Full record

ReviewParasitology2012

Parasites, proteomes and systems: has Descartes' clock run out of time?

J M Wastling, S D Armstrong, R Krishna, D Xia

Abstract readReview
In one paragraph

Review in Parasitology, 2012. 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. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Proteomic analysis of the Theileria annulata schizont.International journal for parasitology · 2013
    Article
  9. Systems analysis of host-parasite interactions.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

4 authors.

J M WastlingDepartment of Infection Biology, Institute of Infection and Global Health, University of Liverpool, Liverpool L69 7ZJ, UK. j.wastling@liv.ac.uk
S D Armstrong
R Krishna
D Xia

Funding

Biotechnology and Biological Sciences Research Council BB/G010781/1
6 · The paper itself

Abstract

Systems biology aims to integrate multiple biological data types such as genomics, transcriptomics and proteomics across different levels of structure and scale; it represents an emerging paradigm in the scientific process which challenges the reductionism that has dominated biomedical research for hundreds of years. Systems biology will nevertheless only be successful if the technologies on which it is based are able to deliver the required type and quality of data. In this review we discuss how well positioned is proteomics to deliver the data necessary to support meaningful systems modelling in parasite biology. We summarise the current state of identification proteomics in parasites, but argue that a new generation of quantitative proteomics data is now needed to underpin effective systems modelling. We discuss the challenges faced to acquire more complete knowledge of protein post-translational modifications, protein turnover and protein-protein interactions in parasites. Finally we highlight the central role of proteome-informatics in ensuring that proteomics data is readily accessible to the user-community and can be translated and integrated with other relevant data types.

Indexed as

Protein Processing, Post-TranslationalAnimalsGene Expression ProfilingGenomicsHost-Parasite InteractionsHumansParasitesProteinsProteomicsSystems BiologyProteins

Identifiers

PMID22828391
PMCPMC3428110

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-SA
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.