Micrornas Function Of The Bioinformatics Analysis And Platform

MicroRNAs are a class of small endogenous non-coding RNAs which play important regulatory roles mainly by posttranscriptional depression. To date, there are 678 human microRNA sequences, according to the miRBase sequence database (Release 11, released April, 2008), have been identified. Moreover, there exists a hypothesis that the total number of human microRNAs will be much larger. MicroRNAs have been thought to be involved in many biological processes, such as transcriptional gene regulatory network, developmental timing, neuronal synapses formation, cell proliferation, cell death, and differentiation.Although there are several computational programs served to predict miRNA targets in mammals (miRanda, TargetScan, PicTar), the fact is that there are many predictions while only few of them have been biologically validated. Finding miRNA target genes will help a lot to understand their biological functions. Unfortunately, the prediction of miRNA target genes is more challenging. In the first section of the dissertation, we developed an ensemble machine learning algorithm which helps to improve the prediction of miRNA targets. The performance was evaluated in the training set and in FMRP associated mRNAs. Moreover, using human mir-9 as a test case, our classification was validated in 10 of 16 transcripts tested. From the results we got, we could make the conclusion that our ensemble algorithm can improve the prediction of microRNA targets efficiently.Microarray-based studies have been used to investigate the regulatory properties of microRNAs. However, to integrate both microRNA and mRNA expression profiles to study sophisticated microRNA functions has not been well addressed. In the second section, we proposed a novel concept of in-silico MicroRNA Regulatory Profiles (in-silico MRPs) for quantifying the microRNA's regulatory properties. The in-silico MRPs were constructed for human (involving 157 microRNAs×13041 mRNAs), mouse (72 microRNAs×10729 mRNAs), and rat (152 microRNAs×5108 mRNAs). We proved that the in-silico MRPs are reliable by comparing our in-silico MRPs with the real gene expression profiles after over expressing or knocking down a specific microRNA. Given these in-silico MRPs, we have explored microRNAs that are likely to function through degrading their targets, the results showed about 36% of human microRNA fall into this category. 42% of shared miroRNAs across the three species were found to retain their regulatory ability through the evolution. A web server (http://www.biosino.org/VirtualOverExpressWebApp/) has been provided where our constructed in-silico MRPs can be downloaded for research use, and customerized in-silico MRPs can be generated if users load their real experimental data. A few other possible applications of the web service were suggested.Numerous computational tools have been developed for studying the function of this class of small nucleotides, and resources and tools are quite useful for studying the function of microRNA; however, they are distributed in different websites and loosely connected. So far, there is no tool to provide an open-source, user-friendly, integrated interface for microRNA related analysis. We have developed an R package, named miRE, which provides a graphical user interface for conducting microRNA related analysis.