ArticlePLoS computational biology2013
Visual data mining of biological networks: one size does not fit all.
Article in PLoS computational biology, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
What it found
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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.
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.
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Who cites it
9 citing papers in PubMed.
- Bioinformatic challenges for pharmacogenomic study: tools for genomic data analysis.Frontiers in pharmacology · 2025Article
- Article
- Nine quick tips for pathway enrichment analysis.PLoS computational biology · 2022Article
- Challenges and Limitations of Biological Network Analysis.Biotech (Basel (Switzerland)) · 2022Article
- An Integrated Approach Identifies Mediators of Local Recurrence in Head and Neck Squamous Carcinoma.Clinical cancer research : an official journal of the American Association for Cancer Research · 2017Article
- Inhibition of the hexosamine biosynthetic pathway promotes castration-resistant prostate cancer.Nature communications · 2016Article
- Integrative transcriptome analysis identifies deregulated microRNA-transcription factor networks in lung adenocarcinoma.Oncotarget · 2016Article
- STAT3 pathway regulates lung-derived brain metastasis initiating cell capacity through miR-21 activation.Oncotarget · 2015Article
- Kinome-wide screening of HER2+ breast cancer cells for molecules that mediate cell proliferation or sensitize cells to trastuzumab therapy.Oncogenesis · 2014Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
High-throughput technologies produce massive amounts of data. However, individual methods yield data specific to the technique used and biological setup. The integration of such diverse data is necessary for the qualitative analysis of information relevant to hypotheses or discoveries. It is often useful to integrate these datasets using pathways and protein interaction networks to get a broader view of the experiment. The resulting network needs to be able to focus on either the large-scale picture or on the more detailed small-scale subsets, depending on the research question and goals. In this tutorial, we illustrate a workflow useful to integrate, analyze, and visualize data from different sources, and highlight important features of tools to support such analyses.
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Registered trials
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.