Evidence map›Paper›PMID 25914674›Full record

ReviewFrontiers in microbiology2015

A review on computational systems biology of pathogen-host interactions.

Saliha Durmuş, Tunahan Çakır, Arzucan Özgür, Reinhard Guthke

Open access · goldAbstract readReview
In one paragraph

Review in Frontiers in microbiology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 57 papers.

0numbers the graph read from it
0cells of the map it votes in
57citing papers in PubMed
6.9field-weighted citation impact, top 2% of its field
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

57 citing papers in PubMed, 93 citations in OpenAlex.

  1. Article
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  6. Review
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  10. Review
  11. Review
  12. PHILM2Web: A high-throughput database of macromolecular host-pathogen interactions on the Web.Database : the journal of biological databases and curation · 2022
    Article
  13. Article
  14. Article
  15. Review
  16. Article
  17. Host-pathogen protein-nucleic acid interactions: A comprehensive review.Computational and structural biotechnology journal · 2022
    Review
  18. Article
  19. Article
  20. Molecules (Basel, Switzerland) · 2021
    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

4 authors at 3 institutions in 2 countries.

Saliha DurmuşComputational Systems Biology Group, Department of Bioengineering, Gebze Technical University, Kocaeli Turkey.
Tunahan ÇakırComputational Systems Biology Group, Department of Bioengineering, Gebze Technical University, Kocaeli Turkey.
Arzucan ÖzgürDepartment of Computer Engineering, Boǧaziçi University, Istanbul Turkey.
Reinhard GuthkeLeibniz Institute for Natural Product Research and Infection Biology - Hans-Knoell-Institute, Jena Germany.
Gebze Technical University · TRBoğaziçi University · TRLeibniz-Institut für Naturstoff-Forschung und Infektionsbiologie e. V. - Hans-Knöll-Institut (HKI) · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Pathogens manipulate the cellular mechanisms of host organisms via pathogen-host interactions (PHIs) in order to take advantage of the capabilities of host cells, leading to infections. The crucial role of these interspecies molecular interactions in initiating and sustaining infections necessitates a thorough understanding of the corresponding mechanisms. Unlike the traditional approach of considering the host or pathogen separately, a systems-level approach, considering the PHI system as a whole is indispensable to elucidate the mechanisms of infection. Following the technological advances in the post-genomic era, PHI data have been produced in large-scale within the last decade. Systems biology-based methods for the inference and analysis of PHI regulatory, metabolic, and protein-protein networks to shed light on infection mechanisms are gaining increasing demand thanks to the availability of omics data. The knowledge derived from the PHIs may largely contribute to the identification of new and more efficient therapeutics to prevent or cure infections. There are recent efforts for the detailed documentation of these experimentally verified PHI data through Web-based databases. Despite these advances in data archiving, there are still large amounts of PHI data in the biomedical literature yet to be discovered, and novel text mining methods are in development to unearth such hidden data. Here, we review a collection of recent studies on computational systems biology of PHIs with a special focus on the methods for the inference and analysis of PHI networks, covering also the Web-based databases and text-mining efforts to unravel the data hidden in the literature.

Indexed as

bioinformaticscomputational systems biologydrug targetgene regulatory networkmetabolic interactionomics datapathogen–host interactionprotein–protein interaction

Identifiers

PMID25914674
PMCPMC4391036
OpenAlexW2035252561

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.