Evidence map›Paper›PMID 22962330›Full record

ArticleBriefings in functional genomics2012

Biological function through network topology: a survey of the human diseasome.

Vuk Janjić, Nataša Pržulj

Abstract read
In one paragraph

Article in Briefings in functional genomics, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
26citing papers in PubMed, 1 pooled it
–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

26 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Functional Interpretation of Omics Data: From Pathways to Networks.Advances in experimental medicine and biology · 2026
    Review
  4. Review
  5. Article
  6. Article
  7. Frontiers in nutrition · 2022
    Article
  8. Journal of biosciences · 2022
    Review
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  10. Article
  11. Review
  12. Article
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  15. Article
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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.

Vuk JanjićDepartment of Computing, Imperial College London, 180 Queen's Gate, SW7 2AZ London, UK.
Nataša Pržulj

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Molecular network data are increasingly becoming available, necessitating the development of well performing computational tools for their analyses. Such tools enabled conceptually different approaches for exploring human diseases to be undertaken, in particular, those that study the relationship between a multitude of biomolecules within a cell. Hence, a new field of network biology has emerged as part of systems biology, aiming to untangle the complexity of cellular network organization. We survey current network analysis methods that aim to give insight into human disease.

Indexed as

Computational BiologyDiseaseHumansSystems Biology

Identifiers

PMID22962330
PMCPMC7109924

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.