Journal
NUCLEIC ACIDS RESEARCH
Volume 40, Issue W1, Pages W13-W21Publisher
OXFORD UNIV PRESS
DOI: 10.1093/nar/gks460
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Funding
- CINECA [HP10BDJ9X8]
- University of Padova [CPDA119031]
- Associazione Italiana per la Ricerca sul Cancro (AIRC, Milano)
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MAGIA(2) (http://gencomp.bio.unipd.it/) 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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