MiRs
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== Problems Solved == | == Problems Solved == | ||
| - | '' | + | ''Existing computational miRNA target prediction methods may vary in the algorithm used; and one can state opinions about the strengths or weaknesses of each particular algorithm, the fact of the matter is that all methods fall substantially short of capturing the full detail of physical, temporal, and spatial requirements of biologically significant miRNA::mRNA interactions. The performance of current tools is largely dependent on the overall number of predicted targets (hits). Some tools may be very efficiency in predicting true targets sites (high sensitivity) but at the same time display an extremely large number of overall hits (low specificity). In contrast other tools display an overall high specificity but a very low sensitivity. It is evident that there is great need for a more sophisticated target prediction tool that achieves a balance between sensitivity and specificity. |
| + | Performing this large scale scan of all miRNAs in the online registry and all the genes of the human genome, will allow us to compare our tool with other available tools on a large scale basis. The results will be stored on an online database that will allow users to query the database using miRNA name or gene name. This will shed some light into new gene targets for miRNAs and the molecular processes that they regulate. | ||
| + | Finally experimental verification of computational predictions will be the ultimate step in revealing the molecular pathways of miRNA regulation and characterizing their involvement in disease. '' | ||
== Scientific and Social Impact == | == Scientific and Social Impact == | ||
Revision as of 15:10, 1 July 2011
Contents |
General Information
- Application's name: Searching for novel miRNA genes and their targets
- Virtual Research Community: Life Sciences
- Scientific contact: Dr. Panayiota Poirazi, poirazi@imbb.forth.gr
- Technical contact: Dr Anastasis Oulas, oulas@imbb.forth.gr
- Developers: Dr Anastasis Oulas, IMBB, FORTH, Greece
- Web site: http://www.imbb.forth.gr/people/poirazi/drupal/?q=node/6/
Short Description
The mode of action of the mature miRNA in mammalian systems is dependent on complementary base pairing to the 3’UTR region of the target mRNA, thereafter causing the inhibition of translation and/or the degradation of the mRNA. Despite the body of evidence supporting a role of miRNAs in numerous molecular processes and diseases, their exact mechanism of action remains to be elucidated because the downstream targets of miRNAs implicated in these prcesses have yet to be defined. Towards this goal, miRNA target prediction tools can offer a first assessment as to which target genes are regulated by miRNAs, thus providing new insights regarding their specific functions and guiding future experiments.
There is great need for a more sophisticated target prediction tool that achieves an inmprved balance between sensitivity and specificity. In order to maximize sensitivity and specificity to the extent that outperforms existing target prediction tools, we implement a new target prediction tool using Hidden Markov Models (HMM). The first step for the successful implementation of this tool is the selection of significant biological features that are implicated in the miRNA::mRNA interaction. Once again careful training and validation has to be performed to obtain statistical evidence for the prediction accuracy of our tool. We have validated our methodology and are now ready to utilize it to scan all human 3’UTR regions for novel miRNA targets. This prediction pipeline will require a great deal of computational power in order to complete these experiments.
Problems Solved
Existing computational miRNA target prediction methods may vary in the algorithm used; and one can state opinions about the strengths or weaknesses of each particular algorithm, the fact of the matter is that all methods fall substantially short of capturing the full detail of physical, temporal, and spatial requirements of biologically significant miRNA::mRNA interactions. The performance of current tools is largely dependent on the overall number of predicted targets (hits). Some tools may be very efficiency in predicting true targets sites (high sensitivity) but at the same time display an extremely large number of overall hits (low specificity). In contrast other tools display an overall high specificity but a very low sensitivity. It is evident that there is great need for a more sophisticated target prediction tool that achieves a balance between sensitivity and specificity. Performing this large scale scan of all miRNAs in the online registry and all the genes of the human genome, will allow us to compare our tool with other available tools on a large scale basis. The results will be stored on an online database that will allow users to query the database using miRNA name or gene name. This will shed some light into new gene targets for miRNAs and the molecular processes that they regulate. Finally experimental verification of computational predictions will be the ultimate step in revealing the molecular pathways of miRNA regulation and characterizing their involvement in disease.
Scientific and Social Impact
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Collaborations and Beneficiaries
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Technical Features and HP-SEE Implementation
- Primary programming language: Tobefilledin
- Parallel programming paradigm: Tobefilledin
- Main parallel code: Tobefilledin
- Pre/post processing code: Tobefilledin
- Application tools and libraries: Enumerate (comma separated)
- Number of cores required: Tobefilledin
- Minimum RAM/core required: Tobefilledin
- Storage space during a single run: Tobefilledin
- Long-term data storage: Tobefilledin
Usage Example
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Publications
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