ArticleMethods in molecular biology (Clifton, N.J.)2026
Rapid Exploratory Data Visualization for Cancer Genomics.
Article in Methods in molecular biology (Clifton, N.J.), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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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Authors and funding
1 author.
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Abstract
This section describes the development and use of a toolbox of software programs for rapid data visualization of large-scale high-throughput datasets such as those found in The Cancer Genome Atlas (TCGA) and other multidimensional datasets. While the toolboxes are described in the context of cancer genomics and long noncoding RNAs, they can be easily applied for the visualization of any large-scale dataset in the form of box plots. The front-end of the toolbox is a simple graphical user interface (GUI), while the customizable back-end holds the data and has numerous modules related to various computations needed for genomic analysis.
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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.