195 research outputs found

    RNAspa: a shortest path approach for comparative prediction of the secondary structure of ncRNA molecules

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    <p>Abstract</p> <p>Background</p> <p>In recent years, RNA molecules that are not translated into proteins (ncRNAs) have drawn a great deal of attention, as they were shown to be involved in many cellular functions. One of the most important computational problems regarding ncRNA is to predict the secondary structure of a molecule from its sequence. In particular, we attempted to predict the secondary structure for a set of unaligned ncRNA molecules that are taken from the same family, and thus presumably have a similar structure.</p> <p>Results</p> <p>We developed the RNAspa program, which comparatively predicts the secondary structure for a set of ncRNA molecules in linear time in the number of molecules. We observed that in a list of several hundred suboptimal minimal free energy (MFE) predictions, as provided by the RNAsubopt program of the Vienna package, it is likely that at least one suggested structure would be similar to the true, correct one. The suboptimal solutions of each molecule are represented as a layer of vertices in a graph. The shortest path in this graph is the basis for structural predictions for the molecule. We also show that RNA secondary structures can be compared very rapidly by a simple string Edit-Distance algorithm with a minimal loss of accuracy. We show that this approach allows us to more deeply explore the suboptimal structure space.</p> <p>Conclusion</p> <p>The algorithm was tested on three datasets which include several ncRNA families taken from the Rfam database. These datasets allowed for comparison of the algorithm with other methods. In these tests, RNAspa performed better than four other programs.</p

    RNAslider: a faster engine for consecutive windows folding and its application to the analysis of genomic folding asymmetry

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    <p>Abstract</p> <p>Background</p> <p>Scanning large genomes with a sliding window in search of locally stable RNA structures is a well motivated problem in bioinformatics. Given a predefined window size L and an RNA sequence S of size N (L < N), the consecutive windows folding problem is to compute the minimal free energy (MFE) for the folding of each of the L-sized substrings of S. The consecutive windows folding problem can be naively solved in O(NL<sup>3</sup>) by applying any of the classical cubic-time RNA folding algorithms to each of the N-L windows of size L. Recently an O(NL<sup>2</sup>) solution for this problem has been described.</p> <p>Results</p> <p>Here, we describe and implement an O(NLŌą(L)) engine for the consecutive windows folding problem, where Ōą(L) is shown to converge to O(1) under the assumption of a standard probabilistic polymer folding model, yielding an O(L) speedup which is experimentally confirmed. Using this tool, we note an intriguing directionality (5'-3' vs. 3'-5') folding bias, i.e. that the minimal free energy (MFE) of folding is higher in the native direction of the DNA than in the reverse direction of various genomic regions in several organisms including regions of the genomes that do not encode proteins or ncRNA. This bias largely emerges from the genomic dinucleotide bias which affects the MFE, however we see some variations in the folding bias in the different genomic regions when normalized to the dinucleotide bias. We also present results from calculating the MFE landscape of a mouse chromosome 1, characterizing the MFE of the long ncRNA molecules that reside in this chromosome.</p> <p>Conclusion</p> <p>The efficient consecutive windows folding engine described in this paper allows for genome wide scans for ncRNA molecules as well as large-scale statistics. This is implemented here as a software tool, called RNAslider, and applied to the scanning of long chromosomes, leading to the observation of features that are visible only on a large scale.</p

    Psiscan: a computational approach to identify H/ACA-like and AGA-like non-coding RNA in trypanosomatid genomes

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    <p>Abstract</p> <p>Background</p> <p>Detection of non coding RNA (ncRNA) molecules is a major bioinformatics challenge. This challenge is particularly difficult when attempting to detect H/ACA molecules which are involved in converting uridine to pseudouridine on rRNA in trypanosomes, because these organisms have unique H/ACA molecules (termed H/ACA-like) that lack several of the features that characterize H/ACA molecules in most other organisms.</p> <p>Results</p> <p>We present here a computational tool called Psiscan, which was designed to detect H/ACA-like molecules in trypanosomes. We started by analyzing known H/ACA-like molecules and characterized their crucial elements both computationally and experimentally.</p> <p>Next, we set up constraints based on this analysis and additional phylogenic and functional data to rapidly scan three trypanosome genomes (<it>T. brucei</it>, <it>T. cruzi </it>and <it>L. major</it>) for sequences that observe these constraints and are conserved among the species. In the next step, we used minimal energy calculation to select the molecules that are predicted to fold into a lowest energy structure that is consistent with the constraints. In the final computational step, we used a Support Vector Machine that was trained on known H/ACA-like molecules as positive examples and on negative examples of molecules that were identified by the computational analyses but were shown experimentally not to be H/ACA-like molecules. The leading candidate molecules predicted by the SVM model were then subjected to experimental validation.</p> <p>Conclusion</p> <p>The experimental validation showed 11 molecules to be expressed (4 out of 25 in the intermediate stage and 7 out of 19 in the final validation after the machine learning stage). Five of these 11 molecules were further shown to be bona fide H/ACA-like molecules. As snoRNA in trypanosomes are organized in clusters, the new H/ACA-like molecules could be used as starting points to manually search for additional molecules in their neighbourhood. All together this study increased our repertoire by fourteen H/ACA-like and six C/D snoRNAs molecules from <it>T. brucei </it>and <it>L. Major</it>. In addition the experimental analysis revealed that six ncRNA molecules that are expressed are not downregulated in CBF5 silenced cells, suggesting that they have structural features of H/ACA-like molecules but do not have their standard function. We termed this novel class of molecules AGA-like, and we are exploring their function.</p> <p>This study demonstrates the power of tight collaboration between computational and experimental approaches in a combined effort to reveal the repertoire of ncRNA molecles.</p

    A METHODOLOGICAL COMPARISON AMONG DNA SOURCE TYPES FOR MOOSE GENOTYPING

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    Population genetic analyses for moose have been based on DNA extracted from blood and other body tissues. Non-invasive sampling of fecal pellets is another potential source of DNA. We compared DNA extraction from blood, liver tissue, and fecal pellet samples from moose in Minnesota and Yellowstone National Park, USA. Extracted DNA from all source types was sufficient for genotyping using 15 microsatellites. DNA extracted from fecal pellets was of lower quality and quantity than DNA extracted from blood and tissue. We provide comparisons of efficiency and effectiveness of DNA extraction protocols for blood, tissue, and fecal pellets, and demonstrate the suitability of using DNA extracted from non-invasively sampled material in moose

    Technological capabilities and the twin transition in Europe: Opportunities for regional collaboration and economic cohesion

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    Technological capabilities vary substantially across European regions. Combining these diverse sets of capabilities is crucial to develop the technologies necessary to master the green and digital transition. However, collaboration between regions is sparse today. To increase inter-regional cooperation, linkages that spur the development of green and digital technologies must be identified. In this study, we provide an overview of inter-regional collaborations already in place and map new opportunities for these between regions. A special emphasis is placed on potential collaborations between economically leading and lagging regions. Our results provide new impetus for policy designs that strengthen regional innovation capabilities and cohesion across Europe’s regions

    Technological capabilities and the twin transition in Europe: Opportunities for regional collaboration and economic cohesion

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    Technological capabilities vary substantially across European regions. Combining these diverse sets of capabilities is crucial to develop the technologies necessary to master the green and digital transition. However, collaboration between regions is sparse today. To increase inter-regional cooperation, linkages that spur the development of green and digital technologies must be identified. In this study, we provide an overview of inter-regional collaborations already in place and map new opportunities for these between regions. A special emphasis is placed on potential collaborations between economically leading and lagging regions. Our results provide new impetus for policy designs that strengthen regional innovation capabilities and cohesion across Europe’s regions

    Germania and alumina dopant diffusion and viscous flow effects at preparation of doped optical fibers

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    We report on germania and alumina dopant profile shift effects at preparation of compact optical fibers using packaging methods (Stack-and-Draw method, Rod-in-Tube (RiT) technique). The sintering of package hollow volume by viscous flow results in a shift of the core-pitch ratio in all-solid microstructured fibers. The ratio is increased by about 5% in the case of a hexagonal package. The shift by diffusion effects of both dopants is simulated for typical slow speed drawing parameters. Thermodynamic approximations of surface dissociation of germania doped silica suggest the need of an adequate undoped silica barrier layer to prevent an undesired bubble formation at fiber drawing. In contrast, alumina doping does not estimate critical dissociation effects with vaporous aluminium oxide components. We report guide values of diffusion length of germania and alumina for the drawing process by kinetic approximation. The germania diffusion involves a small core enlargement, typically in the sub-micrometer scale. Though, the alumina diffusion enlarges it by a few micrometers. A drawn pure alumina preform core rod transforms to an amorphous aluminosilicate core with a molar alumina concentration of only about 50% and a non-gaussian concentration profile
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