ArticleNucleic acids research2012
MAGIA²: from miRNA and genes expression data integrative analysis to microRNA-transcription factor mixed regulatory circuits (2012 update).
Article in Nucleic acids research, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 65 papers.
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65 citing papers in PubMed, 129 citations in OpenAlex.
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- Extensive transcriptional responses are co-ordinated by microRNAs as revealed by Exon-Intron Split Analysis (EISA).Nucleic acids research · 2019Article
- Clustering analysis of microRNA and mRNA expression data from TCGA using maximum edge-weighted matching algorithms.BMC medical genomics · 2019Article
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- Differentially-Expressed miRNAs in Ectopic Stromal Cells Contribute to Endometriosis Development: The Plausible Role of miR-139-5p and miR-375.International journal of molecular sciences · 2018Article
5 more citing papers are in PubMed but not listed here.
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5 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
MAGIA(2) (http://gencomp.bio.unipd.it/magia2) is an update, extension and evolution of the MAGIA web tool. It is dedicated to the integrated analysis of in silico target prediction, microRNA (miRNA) and gene expression data for the reconstruction of post-transcriptional regulatory networks. miRNAs are fundamental post-transcriptional regulators of several key biological and pathological processes. As miRNAs act prevalently through target degradation, their expression profiles are expected to be inversely correlated to those of the target genes. Low specificity of target prediction algorithms makes integration approaches an interesting solution for target prediction refinement. MAGIA(2) performs this integrative approach supporting different association measures, multiple organisms and almost all target predictions algorithms. Nevertheless, miRNAs activity should be viewed as part of a more complex scenario where regulatory elements and their interactors generate a highly connected network and where gene expression profiles are the result of different levels of regulation. The updated MAGIA(2) tries to dissect this complexity by reconstructing mixed regulatory circuits involving either miRNA or transcription factor (TF) as regulators. Two types of circuits are identified: (i) a TF that regulates both a miRNA and its target and (ii) a miRNA that regulates both a TF and its target.
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Registered trials
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