Evidence map›Paper›PMID 28983521›Full record

ArticleCurrent opinion in systems biology2017

Topological methods for genomics: present and future directions.

Pablo G Cámara

Abstract read
In one paragraph

Article in Current opinion in systems biology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing 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

16 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Article
  5. Review
  6. Article
  7. From calcium imaging to graph topology.Network neuroscience (Cambridge, Mass.) · 2022
    Review
  8. The topology of data: opportunities for cancer research.Bioinformatics (Oxford, England) · 2021
    Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Review
  14. Article
  15. Article
  16. 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

1 author.

Pablo G CámaraDepartment of Systems Biology and Department of Biomedical Informatics, Columbia University Medical Center, New York, NY 10032.

Funding

Topology of Cancer Evolution and HeterogeneityU54CA193313 · NCI · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI IAVARONE, ANTONIO, RABADAN, RAUL · 2015 to 2020
$10.4M
Uncovering Evolutionary History using the Topology of Genomic Data with Applications to HIVR01GM117591 · NIGMS · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI RABADAN, RAUL · 2015 to 2018
$1.3M
NCI NIH HHS U54 CA193313NIGMS NIH HHS R01 GM117591
6 · The paper itself

Abstract

Topological methods are emerging as a new set of tools for the analysis of large genomic datasets. They are mathematically grounded methods that extract information from the geometric structure of data. In the last few years, applications to evolutionary biology, cancer genomics, and the analysis of complex diseases have uncovered significant biological results, highlighting their utility for fulfilling some of the current analytic needs of genomics. In this review, the state of the art in the application of topological methods to genomics is summarized, and some of the present limitations and possible future developments are reviewed.

Identifiers

PMID28983521
PMCPMC5624534

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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.