A PROBABILISTIC METHOD FOR PREDICTION OF MICRORNA-TARGET INTERACTIONS

Date

2011-10-26

Author

OĞUL, HASAN
Umu, Sinan U.
Tuncel, Y. Yener
Akkaya, Mahinur

Metadata

Show full item record

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Item Usage Stats

109
views

0
downloads

Elucidation of microRNA activity is a crucial step in understanding gene regulation. One key problem in this effort is how to model the pairwise interaction of microRNAs with their targets. As this interaction is strongly mediated by their sequences, it is desired to set up a probabilistic model to explain the binding between a microRNA sequence and the sequence of a putative target. To this end, we introduce a new model of microRNA-target binding, which transforms an aligned duplex to a new sequence and defines the likelihood of this sequence using a Variable Length Markov Chain. It offers a complementary representation of microRNA-mRNA pairs for microRNA target prediction tools or other probabilistic frameworks of integrative gene regulation analysis. The performance of present model is evaluated by its ability to predict microRNA-mRNA interaction given a mature microRNA sequence and a putative mRNA binding site. In regard to classification accuracy, it outperforms a recent method based on support vector machines.

Subject Keywords

MicroRNA target prediction, Markov chains

URI

https://hdl.handle.net/11511/54468

Collections

Graduate School of Natural and Applied Sciences, Conference / Seminar

Suggestions

OpenMETU
Core

A probabilistic approach to microRNA-target binding OĞUL, HASAN; Umu, Sinan U.; Tuncel, Y. Yener; Akkaya, Mahinur (Elsevier BV, 2011-09-16) Elucidation of microRNA activity is a crucial step in understanding gene regulation. One key problem in this effort is how to model the pairwise interactions of microRNAs with their targets. As this interaction is strongly mediated by their sequences, it is desired to set-up a probabilistic model to explain the binding preferences between a microRNA sequence and the sequence of a putative target. To this end, we introduce a new model of microRNA-target binding, which transforms an aligned duplex to a new se...
Data Integration in Functional Analysis of MicroRNAs OĞUL, HASAN; Akkaya, Mahinur (2011-12-01) The discovery of microRNAs (miRNAs), about a decade ago, has completely changed our understanding of the complexity of gene regulatory networks. It has already been shown that they are abundantly found in many organisms and can regulate hundreds of genes in post-transcriptional level. To elucidate the individual or co-operative effects of miRNAs, it is required to place them in the overall network of gene regulation and link them to other pathways and systems-level processes. One key step in this effort is ...
A Structural Perspective on the Modulation of Protein-Protein Interactions with Small Molecules. Demirel, Habibe Cansu; Dogan, Tunca; Tunçbağ, Nurcan (2018-01-01) Protein-Protein Interactions (PPIs) are the key components in many cellular processes including signaling pathways, enzymatic reactions and epigenetic regulation. Abnormal interactions of some proteins may be pathogenic and cause various disorders including cancer and neurodegenerative diseases. Although inhibiting PPIs with small molecules is a challenging task, it gained an increasing interest because of its strong potential for drug discovery and design. The knowledge of the interface as well as the stru...
Modeling the combined effect of RNA-binding proteins and microRNAs in post-transcriptional regulation HAFEZQORANİ, Saber; LAFZİ, Atefeh; de Bruin, Ruben G.; VAN ZONNEVELD, Anton Jan; van der Veer, Eric P.; Aydın Son, Yeşim; Kazan, Hilal (2016-05-19) Recent studies show that RNA-binding proteins (RBPs) and microRNAs (miRNAs) function in coordination with each other to control post-transcriptional regulation (PTR). Despite this, the majority of research to date has focused on the regulatory effect of individual RBPs or miRNAs. Here, we mapped both RBP and miRNA binding sites on human 3'UTRs and utilized this collection to better understand PTR. We show that the transcripts that lack competition for HuR binding are destabilized more after HuR depletion. W...
A mathematical modeling and approximation of gene expression patterns by linear and quadratic regulatory relations and analysis of gene networks Yılmaz, Fatma Bilge; Weber, Gerhard Wilhelm; Department of Scientific Computing (2004) This thesis mainly concerns modeling, approximation and inference of gene regulatory dynamics on the basis of gene expression patterns. The dynamical behavior of gene expressions is represented by a system of ordinary di erential equations. We introduce a gene-interaction matrix with some nonlinear entries, in particular, quadratic polynomials of the expression levels to keep the system solvable. The model parameters are determined by using optimization. Then, we provide the time-discrete approximation of o...

Citation Formats

H. OĞUL, S. U. Umu, Y. Y. Tuncel, and M. Akkaya, “A PROBABILISTIC METHOD FOR PREDICTION OF MICRORNA-TARGET INTERACTIONS,” 2011, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/54468.