Evidence map›Paper›PMID 33625717›Full record

ArticleJournal of mammary gland biology and neoplasia2020

How to Use Online Tools to Generate New Hypotheses for Mammary Gland Biology Research: A Case Study for Wnt7b.

Yorick Bernardus Cornelis van de Grift, Nika Heijmans, Renée van Amerongen

Abstract read
In one paragraph

Article in Journal of mammary gland biology and neoplasia, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Unraveling the Breast: Advances in Mammary Biology and Cancer Methods.Journal of mammary gland biology and neoplasia · 2020
    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

3 authors.

Yorick Bernardus Cornelis van de GriftDevelopmental, Stem Cell and Cancer Biology, Swammerdam Institute for Life Sciences, University of Amsterdam, Science Park 904, 1098 XH, Amsterdam, the Netherlands.ORCID http://orcid.org/0000-0003-0920-9030
Nika HeijmansDevelopmental, Stem Cell and Cancer Biology, Swammerdam Institute for Life Sciences, University of Amsterdam, Science Park 904, 1098 XH, Amsterdam, the Netherlands.ORCID http://orcid.org/0000-0002-5639-9407
Renée van AmerongenDevelopmental, Stem Cell and Cancer Biology, Swammerdam Institute for Life Sciences, University of Amsterdam, Science Park 904, 1098 XH, Amsterdam, the Netherlands. r.vanamerongen@uva.nl.ORCID http://orcid.org/0000-0002-8808-2092

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

An increasing number of '-omics' datasets, generated by labs all across the world, are becoming available. They contain a wealth of data that are largely unexplored. Not every scientist, however, will have access to the required resources and expertise to analyze such data from scratch. Fortunately, a growing number of investigators is dedicating their time and effort to the development of user friendly, online applications that allow researchers to use and investigate these datasets. Here, we will illustrate the usefulness of such an approach. Using regulation of Wnt7b expression as an example, we will highlight a selection of accessible tools and resources that are available to researchers in the area of mammary gland biology. We show how they can be used for in silico analyses of gene regulatory mechanisms, resulting in new hypotheses and providing leads for experimental follow up. We also call out to the mammary gland community to join forces in a coordinated effort to generate and share additional tissue-specific '-omics' datasets and thereby expand the in silico toolbox.

Indexed as

AnimalsBreast NeoplasmsComputational BiologyDatabases, GeneticDatasets as TopicFeasibility StudiesFemaleGene Expression Regulation, NeoplasticHumansInternetMammary Glands, HumanMiceProto-Oncogene ProteinsRNA-SeqSingle-Cell AnalysisSpatio-Temporal AnalysisProto-Oncogene ProteinsWNT7B protein, humanWnt7b protein, mouseWnt ProteinsBeta-cateninCTNNB1Gene regulationIn silico analysisWnt7bWnt signaling

Identifiers

PMID33625717
PMCPMC7960620

What OpenQuestion holds

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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.