ArticleBMC genomics2015
Investigating inter-chromosomal regulatory relationships through a comprehensive meta-analysis of matched copy number and transcriptomics data sets.
Article in BMC genomics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.
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
4 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Pooled it
- Automated Hypothesis Generation to Identify Signals Relevant in the Development of Mammalian Cell and Tissue Bioprocesses, With Validation in a Retinal Culture System.Frontiers in bioengineering and biotechnology · 2020Article
- Interaction network analysis of YBX1 for identification of therapeutic targets in adenocarcinomas.Journal of biosciences · 2019Article
- Article
Corrections and comments
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Authors and funding
2 authors.
Funding
Abstract
backgroundGene regulatory relationships can be inferred using matched array comparative genomics and transcriptomics data sets from cancer samples. The way in which copy numbers of genes in cancer samples are often greatly disrupted works like a natural gene amplification/deletion experiment. There are now a large number of such data sets publicly available making a meta-analysis of the data possible.
resultsWe infer inter-chromosomal acting gene regulatory relationships from a meta-analysis of 31 publicly available matched array comparative genomics and transcriptomics data sets in humans. We obtained statistically significant predictions of target genes for 1430 potential regulatory genes. The regulatory relationships being inferred are either direct relationships, of a transcription factor on its target, or indirect ones, through pathways containing intermediate steps. We analyse the predictions in terms of cocitations, both publications which cite a regulator with any of its inferred targets and cocitations of any genes in a target list.
conclusionsThe most striking observation from the results is the greater number of inter-chromosomal regulatory relationships involving repression compared to those involving activation. The complete results of the meta-analysis are presented in the database METAMATCHED. We anticipate that the predictions contained in the database will be useful in informing experiments and in helping to construct networks of regulatory relationships.
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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.