Evidence map›Paper›PMID 25210953›Full record

ArticlePLoS computational biology2014

SANTA: quantifying the functional content of molecular networks.

Alex J Cornish, Florian Markowetz

Abstract read
In one paragraph

Article in PLoS computational biology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers.

0numbers the graph read from it
0cells of the map it votes in
30citing 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

30 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. NetMix2: A Principled Network Propagation Algorithm for Identifying Altered Subnetworks.Journal of computational biology : a journal of computational molecular cell biology · 2022
    Article
  9. Article
  10. NAR genomics and bioinformatics · 2021
    Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
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  18. Review
  19. Large-scale analysis of disease pathways in the human interactome.Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing · 2018
    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.

Alex J CornishDepartment of Life Sciences, Imperial College London, London, United Kingdom.
Florian MarkowetzCancer Research UK Cambridge Institute, University of Cambridge, Cambridge, Cambridgeshire, United Kingdom.

Funding

Cancer Research UK 19274
6 · The paper itself

Abstract

Linking networks of molecular interactions to cellular functions and phenotypes is a key goal in systems biology. Here, we adapt concepts of spatial statistics to assess the functional content of molecular networks. Based on the guilt-by-association principle, our approach (called SANTA) quantifies the strength of association between a gene set and a network, and functionally annotates molecular networks like other enrichment methods annotate lists of genes. As a general association measure, SANTA can (i) functionally annotate experimentally derived networks using a collection of curated gene sets and (ii) annotate experimentally derived gene sets using a collection of curated networks, as well as (iii) prioritize genes for follow-up analyses. We exemplify the efficacy of SANTA in several case studies using the S. cerevisiae genetic interaction network and genome-wide RNAi screens in cancer cell lines. Our theory, simulations, and applications show that SANTA provides a principled statistical way to quantify the association between molecular networks and cellular functions and phenotypes. SANTA is available from http://bioconductor.org/packages/release/bioc/html/SANTA.html.

Indexed as

Gene Regulatory NetworksModels, BiologicalModels, MolecularSignal TransductionCell Line, TumorHumansRNA InterferenceSaccharomyces cerevisiaeSystems Biology

Identifiers

PMID25210953
PMCPMC4161294

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.