Warning: Undefined variable $zfal in C:\Inetpub\vhosts\kidney.de\httpdocs\mlpefetch.php on line 525
Deprecated: str_replace(): Passing null to parameter #3 ($subject) of type array|string is deprecated in C:\Inetpub\vhosts\kidney.de\httpdocs\mlpefetch.php on line 525
Warning: Undefined variable $sterm in C:\Inetpub\vhosts\kidney.de\httpdocs\mlpefetch.php on line 530
free
Warning: Undefined variable $sterm in C:\Inetpub\vhosts\kidney.de\httpdocs\mlpefetch.php on line 531
free free
English Wikipedia
Nephropedia Template TP (
Twit Text
DeepDyve Pubget Overpricing |
lüll Finding microRNA regulatory modules in human genome using rule induction Tran DH; Satou K; Ho TBBMC Bioinformatics 2008[Dec]; 9 Suppl 12 (Suppl 12): S5BACKGROUND: MicroRNAs (miRNAs) are a class of small non-coding RNA molecules (20-24 nt), which are believed to participate in repression of gene expression. They play important roles in several biological processes (e.g. cell death and cell growth). Both experimental and computational approaches have been used to determine the function of miRNAs in cellular processes. Most efforts have concentrated on identification of miRNAs and their target genes. However, understanding the regulatory mechanism of miRNAs in the gene regulatory network is also essential to the discovery of functions of miRNAs in complex cellular systems. To understand the regulatory mechanism of miRNAs in complex cellular systems, we need to identify the functional modules involved in complex interactions between miRNAs and their target genes. RESULTS: We propose a rule-based learning method to identify groups of miRNAs and target genes that are believed to participate cooperatively in the post-transcriptional gene regulation, so-called miRNA regulatory modules (MRMs). Applying our method to human genes and miRNAs, we found 79 MRMs. The MRMs are produced from multiple information sources, including miRNA-target binding information, gene expression and miRNA expression profiles. Analysis of two first MRMs shows that these MRMs consist of highly-related miRNAs and their target genes with respect to biological processes. CONCLUSION: The MRMs found by our method have high correlation in expression patterns of miRNAs as well as mRNAs. The mRNAs included in the same module shared similar biological functions, indicating the ability of our method to detect functionality-related genes. Moreover, review of the literature reveals that miRNAs in a module are involved in several types of human cancer.|*Gene Expression Regulation[MESH]|*Gene Expression Regulation, Neoplastic[MESH]|*Gene Regulatory Networks[MESH]|*MicroRNAs[MESH]|Computational Biology/*methods[MESH]|Databases, Factual[MESH]|Genome, Human[MESH]|Humans[MESH]|Models, Biological[MESH]|Models, Genetic[MESH]|Models, Statistical[MESH]|Neoplasms/genetics/*metabolism[MESH]|RNA Processing, Post-Transcriptional[MESH]|Transcription, Genetic[MESH] |