Sinan Uğur Umu

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Noncoding RNAs are integral to a wide range of biological processes, including translation, gene regulation, host-pathogen interactions and environmental sensing. While genomics is now a mature field, our capacity to identify noncoding RNA elements in bacterial and archaeal genomes is hampered by the difficulty of de novo identification. The emergence of(More)
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(More)
Motivation The aim of this study is to assess the performance of RNA-RNA interaction prediction tools for all domains of life. Results Minimum free energy (MFE) and alignment methods constitute most of the current RNA interaction prediction algorithms. The MFE tools that include accessibility (i.e. RNAup, IntaRNA and RNAplex) to the final predicted(More)
A critical assumption of gene expression analysis is that mRNA abundances broadly correlate with protein abundance, but these two are often imperfectly correlated. Some of the discrepancy can be accounted for by two important mRNA features: codon usage and mRNA secondary structure. We present a new global factor, called mRNA:ncRNA avoidance, and provide(More)
A critical assumption of gene expression analysis is that mRNA abundances broadly correlate with protein abundance. However, they don’t. Some of the discrepancy can be accounted for by codon usage and mRNA structure. We present a new model, called mRNA:ncRNA avoidance, and provide evidence that this model explains translation efficiency. We demonstrate(More)
Computational biology has provided widely used and powerful software tools for testing and making inferences about biological data. In the face of increasing volumes of data, heuristic methods that trade software speed for mathematical completeness must be employed. We are interested in whether trade-offs between speed and accuracy are reasonable. Also,(More)
Classifying sequences is one of the central problems in computational biosciences. Several tools have been released to map an unknown molecular entity to one of the known classes using solely its sequence data. However, all of the existing tools are problem-specific and restricted to an alphabet constrained by relevant biological structure. Here, we(More)
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(More)
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