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Sample records for suite predictive rna

  1. The UEA Small RNA Workbench: A Suite of Computational Tools for Small RNA Analysis.

    Mohorianu, Irina; Stocks, Matthew Benedict; Applegate, Christopher Steven; Folkes, Leighton; Moulton, Vincent

    2017-01-01

    RNA silencing (RNA interference, RNAi) is a complex, highly conserved mechanism mediated by short, typically 20-24 nt in length, noncoding RNAs known as small RNAs (sRNAs). They act as guides for the sequence-specific transcriptional and posttranscriptional regulation of target mRNAs and play a key role in the fine-tuning of biological processes such as growth, response to stresses, or defense mechanism.High-throughput sequencing (HTS) technologies are employed to capture the expression levels of sRNA populations. The processing of the resulting big data sets facilitated the computational analysis of the sRNA patterns of variation within biological samples such as time point experiments, tissue series or various treatments. Rapid technological advances enable larger experiments, often with biological replicates leading to a vast amount of raw data. As a result, in this fast-evolving field, the existing methods for sequence characterization and prediction of interaction (regulatory) networks periodically require adapting or in extreme cases, a complete redesign to cope with the data deluge. In addition, the presence of numerous tools focused only on particular steps of HTS analysis hinders the systematic parsing of the results and their interpretation.The UEA small RNA Workbench (v1-4), described in this chapter, provides a user-friendly, modular, interactive analysis in the form of a suite of computational tools designed to process and mine sRNA datasets for interesting characteristics that can be linked back to the observed phenotypes. First, we show how to preprocess the raw sequencing output and prepare it for downstream analysis. Then we review some quality checks that can be used as a first indication of sources of variability between samples. Next we show how the Workbench can provide a comparison of the effects of different normalization approaches on the distributions of expression, enhanced methods for the identification of differentially expressed

  2. SUIT

    Algreen-Ussing, Gregers; Wedebrunn, Ola

    2003-01-01

    Leaflet om project SUIT udgivet af European Commission. Tryksagen forklarer i korte ord resultatet af projektet SUIT. Kulturværdier i Miljøspørgsmål. Vurdering af projekter og indvirkning på miljø....

  3. Planetary Suit Hip Bearing Model for Predicting Design vs. Performance

    Cowley, Matthew S.; Margerum, Sarah; Harvil, Lauren; Rajulu, Sudhakar

    2011-01-01

    , the suited performance trends were comparable between the model and the suited subjects. With the three off-nominal bearing configurations compared to the nominal bearing configurations, human subjects showed decreases in hip flexion of 64%, 6%, and 13% and in hip abduction of 59%, 2%, and 20%. Likewise the solid model showed decreases in hip flexion of 58%, 1%, and 25% and in hip abduction of 56%, 0%, and 30%, under the same condition changes from the nominal configuration. Differences seen between the model predictions and the human subject performance data could be attributed to the model lacking dynamic elements and performing kinematic analysis only, the level of fit of the subjects with the suit, the levels of the subject s suit experience.

  4. Predicting and Modeling RNA Architecture

    Westhof, Eric; Masquida, Benoît; Jossinet, Fabrice

    2011-01-01

    SUMMARY A general approach for modeling the architecture of large and structured RNA molecules is described. The method exploits the modularity and the hierarchical folding of RNA architecture that is viewed as the assembly of preformed double-stranded helices defined by Watson-Crick base pairs and RNA modules maintained by non-Watson-Crick base pairs. Despite the extensive molecular neutrality observed in RNA structures, specificity in RNA folding is achieved through global constraints like lengths of helices, coaxiality of helical stacks, and structures adopted at the junctions of helices. The Assemble integrated suite of computer tools allows for sequence and structure analysis as well as interactive modeling by homology or ab initio assembly with possibilities for fitting within electronic density maps. The local key role of non-Watson-Crick pairs guides RNA architecture formation and offers metrics for assessing the accuracy of three-dimensional models in a more useful way than usual root mean square deviation (RMSD) values. PMID:20504963

  5. RNA-SSPT: RNA Secondary Structure Prediction Tools.

    Ahmad, Freed; Mahboob, Shahid; Gulzar, Tahsin; Din, Salah U; Hanif, Tanzeela; Ahmad, Hifza; Afzal, Muhammad

    2013-01-01

    The prediction of RNA structure is useful for understanding evolution for both in silico and in vitro studies. Physical methods like NMR studies to predict RNA secondary structure are expensive and difficult. Computational RNA secondary structure prediction is easier. Comparative sequence analysis provides the best solution. But secondary structure prediction of a single RNA sequence is challenging. RNA-SSPT is a tool that computationally predicts secondary structure of a single RNA sequence. Most of the RNA secondary structure prediction tools do not allow pseudoknots in the structure or are unable to locate them. Nussinov dynamic programming algorithm has been implemented in RNA-SSPT. The current studies shows only energetically most favorable secondary structure is required and the algorithm modification is also available that produces base pairs to lower the total free energy of the secondary structure. For visualization of RNA secondary structure, NAVIEW in C language is used and modified in C# for tool requirement. RNA-SSPT is built in C# using Dot Net 2.0 in Microsoft Visual Studio 2005 Professional edition. The accuracy of RNA-SSPT is tested in terms of Sensitivity and Positive Predicted Value. It is a tool which serves both secondary structure prediction and secondary structure visualization purposes.

  6. Topology and prediction of RNA pseudoknots

    Reidys, Christian; Huang, Fenix; Andersen, Jørgen Ellegaard

    2011-01-01

    Motivation: Several dynamic programming algorithms for predicting RNA structures with pseudoknots have been proposed that differ dramatically from one another in the classes of structures considered. Results: Here, we use the natural topological classification of RNA structures in terms...

  7. Predicting RNA Structure Using Mutual Information

    Freyhult, E.; Moulton, V.; Gardner, P. P.

    2005-01-01

    , to display and predict conserved RNA secondary structure (including pseudoknots) from an alignment. Results: We show that MIfold can be used to predict simple pseudoknots, and that the performance can be adjusted to make it either more sensitive or more selective. We also demonstrate that the overall...... package. Conclusion: MIfold provides a useful supplementary tool to programs such as RNA Structure Logo, RNAalifold and COVE, and should be useful for automatically generating structural predictions for databases such as Rfam. Availability: MIfold is freely available from http......Background: With the ever-increasing number of sequenced RNAs and the establishment of new RNA databases, such as the Comparative RNA Web Site and Rfam, there is a growing need for accurately and automatically predicting RNA structures from multiple alignments. Since RNA secondary structure...

  8. Characteristics and Prediction of RNA Structure

    Hengwu Li

    2014-01-01

    Full Text Available RNA secondary structures with pseudoknots are often predicted by minimizing free energy, which is NP-hard. Most RNAs fold during transcription from DNA into RNA through a hierarchical pathway wherein secondary structures form prior to tertiary structures. Real RNA secondary structures often have local instead of global optimization because of kinetic reasons. The performance of RNA structure prediction may be improved by considering dynamic and hierarchical folding mechanisms. This study is a novel report on RNA folding that accords with the golden mean characteristic based on the statistical analysis of the real RNA secondary structures of all 480 sequences from RNA STRAND, which are validated by NMR or X-ray. The length ratios of domains in these sequences are approximately 0.382L, 0.5L, 0.618L, and L, where L is the sequence length. These points are just the important golden sections of sequence. With this characteristic, an algorithm is designed to predict RNA hierarchical structures and simulate RNA folding by dynamically folding RNA structures according to the above golden section points. The sensitivity and number of predicted pseudoknots of our algorithm are better than those of the Mfold, HotKnots, McQfold, ProbKnot, and Lhw-Zhu algorithms. Experimental results reflect the folding rules of RNA from a new angle that is close to natural folding.

  9. Efficient RNA extraction protocol for the wood mangrove species Laguncularia racemosa suited for next-generation RNA sequencing

    Wilwerth, M. W.; Rossetto, P.

    2016-01-01

    Mangrove flora and habitat have immeasurable importance in marine and coastal ecology as well as in the economy. Despite their importance, they are constantly threatened by oil spill accidents and environmental contamination; therefore, it is crucial to understand the changes in gene expression to better predict toxicity in these plants. Among the species of Atlantic coast mangrove (Americas and Africa), Laguncularia racemosa, or white mangrove, is a conspicuous species. The wide distribution of L. racemosa in areas where marine oil exploration is rapidly increasing make it a candidate mangrove species model to uncover the impact of oil spills at the molecular level with the use of massive transcriptome sequencing. However, for this purpose, the RNA extraction protocol should ensure low levels of contaminants and structure integrity. In this study, eight RNA extraction methods were tested and analysed using downstream applications. The InviTrap Spin Plant RNA Mini Kit performed best with regard to purity and integrity. Moreover, the obtained RNA was submitted to cDNA synthesis and RT-PCR, successfully generating amplification products of the expected size. These Results show the applicability of the RNA obtained here for downstream methodologies, such as the construction of cDNA libraries for the Illumina Hi-seq platform. (author)

  10. Fast prediction of RNA-RNA interaction using heuristic algorithm.

    Montaseri, Soheila

    2015-01-01

    Interaction between two RNA molecules plays a crucial role in many medical and biological processes such as gene expression regulation. In this process, an RNA molecule prohibits the translation of another RNA molecule by establishing stable interactions with it. Some algorithms have been formed to predict the structure of the RNA-RNA interaction. High computational time is a common challenge in most of the presented algorithms. In this context, a heuristic method is introduced to accurately predict the interaction between two RNAs based on minimum free energy (MFE). This algorithm uses a few dot matrices for finding the secondary structure of each RNA and binding sites between two RNAs. Furthermore, a parallel version of this method is presented. We describe the algorithm's concurrency and parallelism for a multicore chip. The proposed algorithm has been performed on some datasets including CopA-CopT, R1inv-R2inv, Tar-Tar*, DIS-DIS, and IncRNA54-RepZ in Escherichia coli bacteria. The method has high validity and efficiency, and it is run in low computational time in comparison to other approaches.

  11. The UEA sRNA Workbench (version 4.4): a comprehensive suite of tools for analyzing miRNAs and sRNAs.

    Stocks, Matthew B; Mohorianu, Irina; Beckers, Matthew; Paicu, Claudia; Moxon, Simon; Thody, Joshua; Dalmay, Tamas; Moulton, Vincent

    2018-05-02

    RNA interference, a highly conserved regulatory mechanism, is mediated via small RNAs. Recent technical advances enabled the analysis of larger, complex datasets and the investigation of microRNAs and the less known small interfering RNAs. However, the size and intricacy of current data requires a comprehensive set of tools, able to discriminate the patterns from the low-level, noise-like, variation; numerous and varied suggestions from the community represent an invaluable source of ideas for future tools, the ability of the community to contribute to this software is essential. We present a new version of the UEA sRNA Workbench, reconfigured to allow an easy insertion of new tools/workflows. In its released form, it comprises of a suite of tools in a user-friendly environment, with enhanced capabilities for a comprehensive processing of sRNA-seq data e.g. tools for an accurate prediction of sRNA loci (CoLIde) and miRNA loci (miRCat2), as well as workflows to guide the users through common steps such as quality checking of the input data, normalization of abundances or detection of differential expression represent the first step in sRNA-seq analyses. The UEA sRNA Workbench is available at: http://srna-workbench.cmp.uea.ac.uk The source code is available at: https://github.com/sRNAworkbenchuea/UEA_sRNA_Workbench. v.moulton@uea.ac.uk.

  12. Facilitating RNA structure prediction with microarrays.

    Kierzek, Elzbieta; Kierzek, Ryszard; Turner, Douglas H; Catrina, Irina E

    2006-01-17

    Determining RNA secondary structure is important for understanding structure-function relationships and identifying potential drug targets. This paper reports the use of microarrays with heptamer 2'-O-methyl oligoribonucleotides to probe the secondary structure of an RNA and thereby improve the prediction of that secondary structure. When experimental constraints from hybridization results are added to a free-energy minimization algorithm, the prediction of the secondary structure of Escherichia coli 5S rRNA improves from 27 to 92% of the known canonical base pairs. Optimization of buffer conditions for hybridization and application of 2'-O-methyl-2-thiouridine to enhance binding and improve discrimination between AU and GU pairs are also described. The results suggest that probing RNA with oligonucleotide microarrays can facilitate determination of secondary structure.

  13. RNA secondary structure prediction using soft computing.

    Ray, Shubhra Sankar; Pal, Sankar K

    2013-01-01

    Prediction of RNA structure is invaluable in creating new drugs and understanding genetic diseases. Several deterministic algorithms and soft computing-based techniques have been developed for more than a decade to determine the structure from a known RNA sequence. Soft computing gained importance with the need to get approximate solutions for RNA sequences by considering the issues related with kinetic effects, cotranscriptional folding, and estimation of certain energy parameters. A brief description of some of the soft computing-based techniques, developed for RNA secondary structure prediction, is presented along with their relevance. The basic concepts of RNA and its different structural elements like helix, bulge, hairpin loop, internal loop, and multiloop are described. These are followed by different methodologies, employing genetic algorithms, artificial neural networks, and fuzzy logic. The role of various metaheuristics, like simulated annealing, particle swarm optimization, ant colony optimization, and tabu search is also discussed. A relative comparison among different techniques, in predicting 12 known RNA secondary structures, is presented, as an example. Future challenging issues are then mentioned.

  14. IntaRNA 2.0: enhanced and customizable prediction of RNA-RNA interactions.

    Mann, Martin; Wright, Patrick R; Backofen, Rolf

    2017-07-03

    The IntaRNA algorithm enables fast and accurate prediction of RNA-RNA hybrids by incorporating seed constraints and interaction site accessibility. Here, we introduce IntaRNAv2, which enables enhanced parameterization as well as fully customizable control over the prediction modes and output formats. Based on up to date benchmark data, the enhanced predictive quality is shown and further improvements due to more restrictive seed constraints are highlighted. The extended web interface provides visualizations of the new minimal energy profiles for RNA-RNA interactions. These allow a detailed investigation of interaction alternatives and can reveal potential interaction site multiplicity. IntaRNAv2 is freely available (source and binary), and distributed via the conda package manager. Furthermore, it has been included into the Galaxy workflow framework and its already established web interface enables ad hoc usage. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

  15. Occupational-Specific Strength Predicts Astronaut-Related Task Performance in a Weighted Suit.

    Taylor, Andrew; Kotarsky, Christopher J; Bond, Colin W; Hackney, Kyle J

    2018-01-01

    Future space missions beyond low Earth orbit will require deconditioned astronauts to perform occupationally relevant tasks within a planetary spacesuit. The prediction of time-to-completion (TTC) of astronaut tasks will be critical for crew safety, autonomous operations, and mission success. This exploratory study determined if the addition of task-specific strength testing to current standard lower body testing would enhance the prediction of TTC in a 1-G test battery. Eight healthy participants completed NASA lower body strength tests, occupationally specific strength tests, and performed six task simulations (hand drilling, construction wrenching, incline walking, collecting weighted samples, and dragging an unresponsive crewmember to safety) in a 48-kg weighted suit. The TTC for each task was recorded and summed to obtain a total TTC for the test battery. Linear regression was used to predict total TTC with two models: 1) NASA lower body strength tests; and 2) NASA lower body strength tests + occupationally specific strength tests. Total TTC of the test battery ranged from 20.2-44.5 min. The lower body strength test alone accounted for 61% of the variability in total TTC. The addition of hand drilling and wrenching strength tests accounted for 99% of the variability in total TTC. Adding occupationally specific strength tests (hand drilling and wrenching) to standard lower body strength tests successfully predicted total TTC in a performance test battery within a weighted suit. Future research should couple these strength tests with higher fidelity task simulations to determine the utility and efficacy of task performance prediction.Taylor A, Kotarsky CJ, Bond CW, Hackney KJ. Occupational-specific strength predicts astronaut-related task performance in a weighted suit. Aerosp Med Hum Perform. 2018; 89(1):58-62.

  16. TargetRNA: a tool for predicting targets of small RNA action in bacteria

    Tjaden, Brian

    2008-01-01

    Many small RNA (sRNA) genes in bacteria act as posttranscriptional regulators of target messenger RNAs. Here, we present TargetRNA, a web tool for predicting mRNA targets of sRNA action in bacteria. TargetRNA takes as input a genomic sequence that may correspond to an sRNA gene. TargetRNA then uses a dynamic programming algorithm to search each annotated message in a specified genome for mRNAs that evince basepair-binding potential to the input sRNA sequence. Based on the calculated basepair-...

  17. Combinatorial microRNA target predictions

    Krek, Azra; Grün, Dominic; Poy, Matthew N.

    2005-01-01

    MicroRNAs are small noncoding RNAs that recognize and bind to partially complementary sites in the 3' untranslated regions of target genes in animals and, by unknown mechanisms, regulate protein production of the target transcript1, 2, 3. Different combinations of microRNAs are expressed...... in different cell types and may coordinately regulate cell-specific target genes. Here, we present PicTar, a computational method for identifying common targets of microRNAs. Statistical tests using genome-wide alignments of eight vertebrate genomes, PicTar's ability to specifically recover published micro......RNA targets, and experimental validation of seven predicted targets suggest that PicTar has an excellent success rate in predicting targets for single microRNAs and for combinations of microRNAs. We find that vertebrate microRNAs target, on average, roughly 200 transcripts each. Furthermore, our results...

  18. Wireless Wearable Multisensory Suite and Real-Time Prediction of Obstructive Sleep Apnea Episodes.

    Le, Trung Q; Cheng, Changqing; Sangasoongsong, Akkarapol; Wongdhamma, Woranat; Bukkapatnam, Satish T S

    2013-01-01

    Obstructive sleep apnea (OSA) is a common sleep disorder found in 24% of adult men and 9% of adult women. Although continuous positive airway pressure (CPAP) has emerged as a standard therapy for OSA, a majority of patients are not tolerant to this treatment, largely because of the uncomfortable nasal air delivery during their sleep. Recent advances in wireless communication and advanced ("bigdata") preditive analytics technologies offer radically new point-of-care treatment approaches for OSA episodes with unprecedented comfort and afforadability. We introduce a Dirichlet process-based mixture Gaussian process (DPMG) model to predict the onset of sleep apnea episodes based on analyzing complex cardiorespiratory signals gathered from a custom-designed wireless wearable multisensory suite. Extensive testing with signals from the multisensory suite as well as PhysioNet's OSA database suggests that the accuracy of offline OSA classification is 88%, and accuracy for predicting an OSA episode 1-min ahead is 83% and 3-min ahead is 77%. Such accurate prediction of an impending OSA episode can be used to adaptively adjust CPAP airflow (toward improving the patient's adherence) or the torso posture (e.g., minor chin adjustments to maintain steady levels of the airflow).

  19. The Earth System Prediction Suite: Toward a Coordinated U.S. Modeling Capability

    Theurich, Gerhard; DeLuca, C.; Campbell, T.; Liu, F.; Saint, K.; Vertenstein, M.; Chen, J.; Oehmke, R.; Doyle, J.; Whitcomb, T.; hide

    2016-01-01

    The Earth System Prediction Suite (ESPS) is a collection of flagship U.S. weather and climate models and model components that are being instrumented to conform to interoperability conventions, documented to follow metadata standards, and made available either under open source terms or to credentialed users.The ESPS represents a culmination of efforts to create a common Earth system model architecture, and the advent of increasingly coordinated model development activities in the U.S. ESPS component interfaces are based on the Earth System Modeling Framework (ESMF), community-developed software for building and coupling models, and the National Unified Operational Prediction Capability (NUOPC) Layer, a set of ESMF-based component templates and interoperability conventions. This shared infrastructure simplifies the process of model coupling by guaranteeing that components conform to a set of technical and semantic behaviors. The ESPS encourages distributed, multi-agency development of coupled modeling systems, controlled experimentation and testing, and exploration of novel model configurations, such as those motivated by research involving managed and interactive ensembles. ESPS codes include the Navy Global Environmental Model (NavGEM), HYbrid Coordinate Ocean Model (HYCOM), and Coupled Ocean Atmosphere Mesoscale Prediction System (COAMPS); the NOAA Environmental Modeling System (NEMS) and the Modular Ocean Model (MOM); the Community Earth System Model (CESM); and the NASA ModelE climate model and GEOS-5 atmospheric general circulation model.

  20. Evolutionary rate variation and RNA secondary structure prediction

    Knudsen, B.; Andersen, E.S.; Damgaard, C.

    2004-01-01

    Predicting RNA secondary structure using evolutionary history can be carried out by using an alignment of related RNA sequences with conserved structure. Accurately determining evolutionary substitution rates for base pairs and single stranded nucleotides is a concern for methods based on this type...... by applying rates derived from tRNA and rRNA to the prediction of the much more rapidly evolving 5'-region of HIV-1. We find that the HIV-1 prediction is in agreement with experimental data, even though the relative evolutionary rate between A and G is significantly increased, both in stem and loop regions...

  1. Common features of microRNA target prediction tools

    Sarah M. Peterson

    2014-02-01

    Full Text Available The human genome encodes for over 1800 microRNAs, which are short noncoding RNA molecules that function to regulate gene expression post-transcriptionally. Due to the potential for one microRNA to target multiple gene transcripts, microRNAs are recognized as a major mechanism to regulate gene expression and mRNA translation. Computational prediction of microRNA targets is a critical initial step in identifying microRNA:mRNA target interactions for experimental validation. The available tools for microRNA target prediction encompass a range of different computational approaches, from the modeling of physical interactions to the incorporation of machine learning. This review provides an overview of the major computational approaches to microRNA target prediction. Our discussion highlights three tools for their ease of use, reliance on relatively updated versions of miRBase, and range of capabilities, and these are DIANA-microT-CDS, miRanda-mirSVR, and TargetScan. In comparison across all microRNA target prediction tools, four main aspects of the microRNA:mRNA target interaction emerge as common features on which most target prediction is based: seed match, conservation, free energy, and site accessibility. This review explains these features and identifies how they are incorporated into currently available target prediction tools. MicroRNA target prediction is a dynamic field with increasing attention on development of new analysis tools. This review attempts to provide a comprehensive assessment of these tools in a manner that is accessible across disciplines. Understanding the basis of these prediction methodologies will aid in user selection of the appropriate tools and interpretation of the tool output.

  2. A comprehensive comparison of comparative RNA structure prediction approaches

    Gardner, P. P.; Giegerich, R.

    2004-01-01

    -finding and multiple-sequence-alignment algorithms. Results Here we evaluate a number of RNA folding algorithms using reliable RNA data-sets and compare their relative performance. Conclusions We conclude that comparative data can enhance structure prediction but structure-prediction-algorithms vary widely in terms......Background An increasing number of researchers have released novel RNA structure analysis and prediction algorithms for comparative approaches to structure prediction. Yet, independent benchmarking of these algorithms is rarely performed as is now common practice for protein-folding, gene...

  3. Ensemble-based prediction of RNA secondary structures.

    Aghaeepour, Nima; Hoos, Holger H

    2013-04-24

    Accurate structure prediction methods play an important role for the understanding of RNA function. Energy-based, pseudoknot-free secondary structure prediction is one of the most widely used and versatile approaches, and improved methods for this task have received much attention over the past five years. Despite the impressive progress that as been achieved in this area, existing evaluations of the prediction accuracy achieved by various algorithms do not provide a comprehensive, statistically sound assessment. Furthermore, while there is increasing evidence that no prediction algorithm consistently outperforms all others, no work has been done to exploit the complementary strengths of multiple approaches. In this work, we present two contributions to the area of RNA secondary structure prediction. Firstly, we use state-of-the-art, resampling-based statistical methods together with a previously published and increasingly widely used dataset of high-quality RNA structures to conduct a comprehensive evaluation of existing RNA secondary structure prediction procedures. The results from this evaluation clarify the performance relationship between ten well-known existing energy-based pseudoknot-free RNA secondary structure prediction methods and clearly demonstrate the progress that has been achieved in recent years. Secondly, we introduce AveRNA, a generic and powerful method for combining a set of existing secondary structure prediction procedures into an ensemble-based method that achieves significantly higher prediction accuracies than obtained from any of its component procedures. Our new, ensemble-based method, AveRNA, improves the state of the art for energy-based, pseudoknot-free RNA secondary structure prediction by exploiting the complementary strengths of multiple existing prediction procedures, as demonstrated using a state-of-the-art statistical resampling approach. In addition, AveRNA allows an intuitive and effective control of the trade-off between

  4. A quick reality check for microRNA target prediction.

    Kast, Juergen

    2011-04-01

    The regulation of protein abundance by microRNA (miRNA)-mediated repression of mRNA translation is a rapidly growing area of interest in biochemical research. In animal cells, the miRNA seed sequence does not perfectly match that of the mRNA it targets, resulting in a large number of possible miRNA targets and varied extents of repression. Several software tools are available for the prediction of miRNA targets, yet the overlap between them is limited. Jovanovic et al. have developed and applied a targeted, quantitative approach to validate predicted miRNA target proteins. Using a proteome database, they have set up and tested selected reaction monitoring assays for approximately 20% of more than 800 predicted let-7 targets, as well as control genes in Caenorhabditis elegans. Their results demonstrate that such assays can be developed quickly and with relative ease, and applied in a high-throughput setup to verify known and identify novel miRNA targets. They also show, however, that the choice of the biological system and material has a noticeable influence on the frequency, extent and direction of the observed changes. Nonetheless, selected reaction monitoring assays, such as those developed by Jovanovic et al., represent an attractive new tool in the study of miRNA function at the organism level.

  5. RNAstructure: software for RNA secondary structure prediction and analysis.

    Reuter, Jessica S; Mathews, David H

    2010-03-15

    To understand an RNA sequence's mechanism of action, the structure must be known. Furthermore, target RNA structure is an important consideration in the design of small interfering RNAs and antisense DNA oligonucleotides. RNA secondary structure prediction, using thermodynamics, can be used to develop hypotheses about the structure of an RNA sequence. RNAstructure is a software package for RNA secondary structure prediction and analysis. It uses thermodynamics and utilizes the most recent set of nearest neighbor parameters from the Turner group. It includes methods for secondary structure prediction (using several algorithms), prediction of base pair probabilities, bimolecular structure prediction, and prediction of a structure common to two sequences. This contribution describes new extensions to the package, including a library of C++ classes for incorporation into other programs, a user-friendly graphical user interface written in JAVA, and new Unix-style text interfaces. The original graphical user interface for Microsoft Windows is still maintained. The extensions to RNAstructure serve to make RNA secondary structure prediction user-friendly. The package is available for download from the Mathews lab homepage at http://rna.urmc.rochester.edu/RNAstructure.html.

  6. RNA folding: structure prediction, folding kinetics and ion electrostatics.

    Tan, Zhijie; Zhang, Wenbing; Shi, Yazhou; Wang, Fenghua

    2015-01-01

    Beyond the "traditional" functions such as gene storage, transport and protein synthesis, recent discoveries reveal that RNAs have important "new" biological functions including the RNA silence and gene regulation of riboswitch. Such functions of noncoding RNAs are strongly coupled to the RNA structures and proper structure change, which naturally leads to the RNA folding problem including structure prediction and folding kinetics. Due to the polyanionic nature of RNAs, RNA folding structure, stability and kinetics are strongly coupled to the ion condition of solution. The main focus of this chapter is to review the recent progress in the three major aspects in RNA folding problem: structure prediction, folding kinetics and ion electrostatics. This chapter will introduce both the recent experimental and theoretical progress, while emphasize the theoretical modelling on the three aspects in RNA folding.

  7. Free energy minimization to predict RNA secondary structures and computational RNA design.

    Churkin, Alexander; Weinbrand, Lina; Barash, Danny

    2015-01-01

    Determining the RNA secondary structure from sequence data by computational predictions is a long-standing problem. Its solution has been approached in two distinctive ways. If a multiple sequence alignment of a collection of homologous sequences is available, the comparative method uses phylogeny to determine conserved base pairs that are more likely to form as a result of billions of years of evolution than by chance. In the case of single sequences, recursive algorithms that compute free energy structures by using empirically derived energy parameters have been developed. This latter approach of RNA folding prediction by energy minimization is widely used to predict RNA secondary structure from sequence. For a significant number of RNA molecules, the secondary structure of the RNA molecule is indicative of its function and its computational prediction by minimizing its free energy is important for its functional analysis. A general method for free energy minimization to predict RNA secondary structures is dynamic programming, although other optimization methods have been developed as well along with empirically derived energy parameters. In this chapter, we introduce and illustrate by examples the approach of free energy minimization to predict RNA secondary structures.

  8. Airport Gate Activity Monitoring Tool Suite for Improved Turnaround Prediction, Phase I

    National Aeronautics and Space Administration — The objective of this research is to create a suite of tools for monitoring airport gate activities with the objective of improving aircraft turnaround. Airport ramp...

  9. A Method to Predict the Structure and Stability of RNA/RNA Complexes.

    Xu, Xiaojun; Chen, Shi-Jie

    2016-01-01

    RNA/RNA interactions are essential for genomic RNA dimerization and regulation of gene expression. Intermolecular loop-loop base pairing is a widespread and functionally important tertiary structure motif in RNA machinery. However, computational prediction of intermolecular loop-loop base pairing is challenged by the entropy and free energy calculation due to the conformational constraint and the intermolecular interactions. In this chapter, we describe a recently developed statistical mechanics-based method for the prediction of RNA/RNA complex structures and stabilities. The method is based on the virtual bond RNA folding model (Vfold). The main emphasis in the method is placed on the evaluation of the entropy and free energy for the loops, especially tertiary kissing loops. The method also uses recursive partition function calculations and two-step screening algorithm for large, complicated structures of RNA/RNA complexes. As case studies, we use the HIV-1 Mal dimer and the siRNA/HIV-1 mutant (T4) to illustrate the method.

  10. CompaRNA: a server for continuous benchmarking of automated methods for RNA secondary structure prediction

    Puton, Tomasz; Kozlowski, Lukasz P.; Rother, Kristian M.; Bujnicki, Janusz M.

    2013-01-01

    We present a continuous benchmarking approach for the assessment of RNA secondary structure prediction methods implemented in the CompaRNA web server. As of 3 October 2012, the performance of 28 single-sequence and 13 comparative methods has been evaluated on RNA sequences/structures released weekly by the Protein Data Bank. We also provide a static benchmark generated on RNA 2D structures derived from the RNAstrand database. Benchmarks on both data sets offer insight into the relative performance of RNA secondary structure prediction methods on RNAs of different size and with respect to different types of structure. According to our tests, on the average, the most accurate predictions obtained by a comparative approach are generated by CentroidAlifold, MXScarna, RNAalifold and TurboFold. On the average, the most accurate predictions obtained by single-sequence analyses are generated by CentroidFold, ContextFold and IPknot. The best comparative methods typically outperform the best single-sequence methods if an alignment of homologous RNA sequences is available. This article presents the results of our benchmarks as of 3 October 2012, whereas the rankings presented online are continuously updated. We will gladly include new prediction methods and new measures of accuracy in the new editions of CompaRNA benchmarks. PMID:23435231

  11. CompaRNA: a server for continuous benchmarking of automated methods for RNA secondary structure prediction.

    Puton, Tomasz; Kozlowski, Lukasz P; Rother, Kristian M; Bujnicki, Janusz M

    2013-04-01

    We present a continuous benchmarking approach for the assessment of RNA secondary structure prediction methods implemented in the CompaRNA web server. As of 3 October 2012, the performance of 28 single-sequence and 13 comparative methods has been evaluated on RNA sequences/structures released weekly by the Protein Data Bank. We also provide a static benchmark generated on RNA 2D structures derived from the RNAstrand database. Benchmarks on both data sets offer insight into the relative performance of RNA secondary structure prediction methods on RNAs of different size and with respect to different types of structure. According to our tests, on the average, the most accurate predictions obtained by a comparative approach are generated by CentroidAlifold, MXScarna, RNAalifold and TurboFold. On the average, the most accurate predictions obtained by single-sequence analyses are generated by CentroidFold, ContextFold and IPknot. The best comparative methods typically outperform the best single-sequence methods if an alignment of homologous RNA sequences is available. This article presents the results of our benchmarks as of 3 October 2012, whereas the rankings presented online are continuously updated. We will gladly include new prediction methods and new measures of accuracy in the new editions of CompaRNA benchmarks.

  12. Prediction of RNA Polymerase II recruitment, elongation and stalling from histone modification data

    Chen, Yun; Jørgensen, Mette; Kolde, Raivo

    2011-01-01

    of RNAPII stalling. CONCLUSIONS: In this study we introduce a general framework to accurately predict the level of RNAPII recruitment, elongation, stalling and mRNA expression from chromatin signals. The versatility of the method also makes it ideally suited to investigate other genomic data....... strategies are needed to progress from descriptive annotation of data to quantitative, predictive models. RESULTS: Here, we describe a computational framework which with high accuracy can predict the locations of core promoters, the amount of recruited RNAPII at the promoter, the amount of elongating RNAPII...... of these four marks are found to be necessary for recruitment of RNAPII but not sufficient for the elongation. We also show that the spatial distributions of histone marks are almost as predictive as the signal strength and that a set of histone marks immediately downstream of the TSS is highly predictive...

  13. Prediction of miRNA-mRNA associations in Alzheimer's disease mice using network topology.

    Noh, Haneul; Park, Charny; Park, Soojun; Lee, Young Seek; Cho, Soo Young; Seo, Hyemyung

    2014-08-03

    Little is known about the relationship between miRNA and mRNA expression in Alzheimer's disease (AD) at early- or late-symptomatic stages. Sequence-based target prediction algorithms and anti-correlation profiles have been applied to predict miRNA targets using omics data, but this approach often leads to false positive predictions. Here, we applied the joint profiling analysis of mRNA and miRNA expression levels to Tg6799 AD model mice at 4 and 8 months of age using a network topology-based method. We constructed gene regulatory networks and used the PageRank algorithm to predict significant interactions between miRNA and mRNA. In total, 8 cluster modules were predicted by the transcriptome data for co-expression networks of AD pathology. In total, 54 miRNAs were identified as being differentially expressed in AD. Among these, 50 significant miRNA-mRNA interactions were predicted by integrating sequence target prediction, expression analysis, and the PageRank algorithm. We identified a set of miRNA-mRNA interactions that were changed in the hippocampus of Tg6799 AD model mice. We determined the expression levels of several candidate genes and miRNA. For functional validation in primary cultured neurons from Tg6799 mice (MT) and littermate (LM) controls, the overexpression of ARRDC3 enhanced PPP1R3C expression. ARRDC3 overexpression showed the tendency to decrease the expression of miR139-5p and miR3470a in both LM and MT primary cells. Pathological environment created by Aβ treatment increased the gene expression of PPP1R3C and Sfpq but did not significantly alter the expression of miR139-5p or miR3470a. Aβ treatment increased the promoter activity of ARRDC3 gene in LM primary cells but not in MT primary cells. Our results demonstrate AD-specific changes in the miRNA regulatory system as well as the relationship between the expression levels of miRNAs and their targets in the hippocampus of Tg6799 mice. These data help further our understanding of the function

  14. RNA 3D modules in genome-wide predictions of RNA 2D structure

    Theis, Corinna; Zirbel, Craig L; Zu Siederdissen, Christian Höner

    2015-01-01

    . These modules can, for example, occur inside structural elements which in RNA 2D predictions appear as internal loops. Hence one question is if the use of such RNA 3D information can improve the prediction accuracy of RNA secondary structure at a genome-wide level. Here, we use RNAz in combination with 3D......Recent experimental and computational progress has revealed a large potential for RNA structure in the genome. This has been driven by computational strategies that exploit multiple genomes of related organisms to identify common sequences and secondary structures. However, these computational...... approaches have two main challenges: they are computationally expensive and they have a relatively high false discovery rate (FDR). Simultaneously, RNA 3D structure analysis has revealed modules composed of non-canonical base pairs which occur in non-homologous positions, apparently by independent evolution...

  15. Computational prediction of miRNA genes from small RNA sequencing data

    Wenjing eKang

    2015-01-01

    Full Text Available Next-generation sequencing now for the first time allows researchers to gauge the depth and variation of entire transcriptomes. However, now as rare transcripts can be detected that are present in cells at single copies, more advanced computational tools are needed to accurately annotate and profile them. miRNAs are 22 nucleotide small RNAs (sRNAs that post-transcriptionally reduce the output of protein coding genes. They have established roles in numerous biological processes, including cancers and other diseases. During miRNA biogenesis, the sRNAs are sequentially cleaved from precursor molecules that have a characteristic hairpin RNA structure. The vast majority of new miRNA genes that are discovered are mined from small RNA sequencing (sRNA-seq, which can detect more than a billion RNAs in a single run. However, given that many of the detected RNAs are degradation products from all types of transcripts, the accurate identification of miRNAs remain a non-trivial computational problem. Here we review the tools available to predict animal miRNAs from sRNA sequencing data. We present tools for generalist and specialist use cases, including prediction from massively pooled data or in species without reference genome. We also present wet-lab methods used to validate predicted miRNAs, and approaches to computationally benchmark prediction accuracy. For each tool, we reference validation experiments and benchmarking efforts. Last, we discuss the future of the field.

  16. HAMDA: Hybrid Approach for MiRNA-Disease Association prediction.

    Chen, Xing; Niu, Ya-Wei; Wang, Guang-Hui; Yan, Gui-Ying

    2017-12-01

    For decades, enormous experimental researches have collectively indicated that microRNA (miRNA) could play indispensable roles in many critical biological processes and thus also the pathogenesis of human complex diseases. Whereas the resource and time cost required in traditional biology experiments are expensive, more and more attentions have been paid to the development of effective and feasible computational methods for predicting potential associations between disease and miRNA. In this study, we developed a computational model of Hybrid Approach for MiRNA-Disease Association prediction (HAMDA), which involved the hybrid graph-based recommendation algorithm, to reveal novel miRNA-disease associations by integrating experimentally verified miRNA-disease associations, disease semantic similarity, miRNA functional similarity, and Gaussian interaction profile kernel similarity into a recommendation algorithm. HAMDA took not only network structure and information propagation but also node attribution into consideration, resulting in a satisfactory prediction performance. Specifically, HAMDA obtained AUCs of 0.9035 and 0.8395 in the frameworks of global and local leave-one-out cross validation, respectively. Meanwhile, HAMDA also achieved good performance with AUC of 0.8965 ± 0.0012 in 5-fold cross validation. Additionally, we conducted case studies about three important human cancers for performance evaluation of HAMDA. As a result, 90% (Lymphoma), 86% (Prostate Cancer) and 92% (Kidney Cancer) of top 50 predicted miRNAs were confirmed by recent experiment literature, which showed the reliable prediction ability of HAMDA. Copyright © 2017 Elsevier Inc. All rights reserved.

  17. IntaRNA 2.0: enhanced and customizable prediction of RNA–RNA interactions

    Mann, Martin; Wright, Patrick R.

    2017-01-01

    Abstract The IntaRNA algorithm enables fast and accurate prediction of RNA–RNA hybrids by incorporating seed constraints and interaction site accessibility. Here, we introduce IntaRNAv2, which enables enhanced parameterization as well as fully customizable control over the prediction modes and output formats. Based on up to date benchmark data, the enhanced predictive quality is shown and further improvements due to more restrictive seed constraints are highlighted. The extended web interface provides visualizations of the new minimal energy profiles for RNA–RNA interactions. These allow a detailed investigation of interaction alternatives and can reveal potential interaction site multiplicity. IntaRNAv2 is freely available (source and binary), and distributed via the conda package manager. Furthermore, it has been included into the Galaxy workflow framework and its already established web interface enables ad hoc usage. PMID:28472523

  18. Improved nucleic acid descriptors for siRNA efficacy prediction.

    Sciabola, Simone; Cao, Qing; Orozco, Modesto; Faustino, Ignacio; Stanton, Robert V

    2013-02-01

    Although considerable progress has been made recently in understanding how gene silencing is mediated by the RNAi pathway, the rational design of effective sequences is still a challenging task. In this article, we demonstrate that including three-dimensional descriptors improved the discrimination between active and inactive small interfering RNAs (siRNAs) in a statistical model. Five descriptor types were used: (i) nucleotide position along the siRNA sequence, (ii) nucleotide composition in terms of presence/absence of specific combinations of di- and trinucleotides, (iii) nucleotide interactions by means of a modified auto- and cross-covariance function, (iv) nucleotide thermodynamic stability derived by the nearest neighbor model representation and (v) nucleic acid structure flexibility. The duplex flexibility descriptors are derived from extended molecular dynamics simulations, which are able to describe the sequence-dependent elastic properties of RNA duplexes, even for non-standard oligonucleotides. The matrix of descriptors was analysed using three statistical packages in R (partial least squares, random forest, and support vector machine), and the most predictive model was implemented in a modeling tool we have made publicly available through SourceForge. Our implementation of new RNA descriptors coupled with appropriate statistical algorithms resulted in improved model performance for the selection of siRNA candidates when compared with publicly available siRNA prediction tools and previously published test sets. Additional validation studies based on in-house RNA interference projects confirmed the robustness of the scoring procedure in prospective studies.

  19. Literature-based condition-specific miRNA-mRNA target prediction.

    Minsik Oh

    Full Text Available miRNAs are small non-coding RNAs that regulate gene expression by binding to the 3'-UTR of genes. Many recent studies have reported that miRNAs play important biological roles by regulating specific mRNAs or genes. Many sequence-based target prediction algorithms have been developed to predict miRNA targets. However, these methods are not designed for condition-specific target predictions and produce many false positives; thus, expression-based target prediction algorithms have been developed for condition-specific target predictions. A typical strategy to utilize expression data is to leverage the negative control roles of miRNAs on genes. To control false positives, a stringent cutoff value is typically set, but in this case, these methods tend to reject many true target relationships, i.e., false negatives. To overcome these limitations, additional information should be utilized. The literature is probably the best resource that we can utilize. Recent literature mining systems compile millions of articles with experiments designed for specific biological questions, and the systems provide a function to search for specific information. To utilize the literature information, we used a literature mining system, BEST, that automatically extracts information from the literature in PubMed and that allows the user to perform searches of the literature with any English words. By integrating omics data analysis methods and BEST, we developed Context-MMIA, a miRNA-mRNA target prediction method that combines expression data analysis results and the literature information extracted based on the user-specified context. In the pathway enrichment analysis using genes included in the top 200 miRNA-targets, Context-MMIA outperformed the four existing target prediction methods that we tested. In another test on whether prediction methods can re-produce experimentally validated target relationships, Context-MMIA outperformed the four existing target prediction

  20. A comprehensive software suite for protein family construction and functional site prediction.

    David Renfrew Haft

    Full Text Available In functionally diverse protein families, conservation in short signature regions may outperform full-length sequence comparisons for identifying proteins that belong to a subgroup within which one specific aspect of their function is conserved. The SIMBAL workflow (Sites Inferred by Metabolic Background Assertion Labeling is a data-mining procedure for finding such signature regions. It begins by using clues from genomic context, such as co-occurrence or conserved gene neighborhoods, to build a useful training set from a large number of uncharacterized but mutually homologous proteins. When training set construction is successful, the YES partition is enriched in proteins that share function with the user's query sequence, while the NO partition is depleted. A selected query sequence is then mined for short signature regions whose closest matches overwhelmingly favor proteins from the YES partition. High-scoring signature regions typically contain key residues critical to functional specificity, so proteins with the highest sequence similarity across these regions tend to share the same function. The SIMBAL algorithm was described previously, but significant manual effort, expertise, and a supporting software infrastructure were required to prepare the requisite training sets. Here, we describe a new, distributable software suite that speeds up and simplifies the process for using SIMBAL, most notably by providing tools that automate training set construction. These tools have broad utility for comparative genomics, allowing for flexible collection of proteins or protein domains based on genomic context as well as homology, a capability that can greatly assist in protein family construction. Armed with this new software suite, SIMBAL can serve as a fast and powerful in silico alternative to direct experimentation for characterizing proteins and their functional interactions.

  1. Dinucleotide controlled null models for comparative RNA gene prediction

    Gesell Tanja

    2008-05-01

    Full Text Available Abstract Background Comparative prediction of RNA structures can be used to identify functional noncoding RNAs in genomic screens. It was shown recently by Babak et al. [BMC Bioinformatics. 8:33] that RNA gene prediction programs can be biased by the genomic dinucleotide content, in particular those programs using a thermodynamic folding model including stacking energies. As a consequence, there is need for dinucleotide-preserving control strategies to assess the significance of such predictions. While there have been randomization algorithms for single sequences for many years, the problem has remained challenging for multiple alignments and there is currently no algorithm available. Results We present a program called SISSIz that simulates multiple alignments of a given average dinucleotide content. Meeting additional requirements of an accurate null model, the randomized alignments are on average of the same sequence diversity and preserve local conservation and gap patterns. We make use of a phylogenetic substitution model that includes overlapping dependencies and site-specific rates. Using fast heuristics and a distance based approach, a tree is estimated under this model which is used to guide the simulations. The new algorithm is tested on vertebrate genomic alignments and the effect on RNA structure predictions is studied. In addition, we directly combined the new null model with the RNAalifold consensus folding algorithm giving a new variant of a thermodynamic structure based RNA gene finding program that is not biased by the dinucleotide content. Conclusion SISSIz implements an efficient algorithm to randomize multiple alignments preserving dinucleotide content. It can be used to get more accurate estimates of false positive rates of existing programs, to produce negative controls for the training of machine learning based programs, or as standalone RNA gene finding program. Other applications in comparative genomics that require

  2. Dinucleotide controlled null models for comparative RNA gene prediction.

    Gesell, Tanja; Washietl, Stefan

    2008-05-27

    Comparative prediction of RNA structures can be used to identify functional noncoding RNAs in genomic screens. It was shown recently by Babak et al. [BMC Bioinformatics. 8:33] that RNA gene prediction programs can be biased by the genomic dinucleotide content, in particular those programs using a thermodynamic folding model including stacking energies. As a consequence, there is need for dinucleotide-preserving control strategies to assess the significance of such predictions. While there have been randomization algorithms for single sequences for many years, the problem has remained challenging for multiple alignments and there is currently no algorithm available. We present a program called SISSIz that simulates multiple alignments of a given average dinucleotide content. Meeting additional requirements of an accurate null model, the randomized alignments are on average of the same sequence diversity and preserve local conservation and gap patterns. We make use of a phylogenetic substitution model that includes overlapping dependencies and site-specific rates. Using fast heuristics and a distance based approach, a tree is estimated under this model which is used to guide the simulations. The new algorithm is tested on vertebrate genomic alignments and the effect on RNA structure predictions is studied. In addition, we directly combined the new null model with the RNAalifold consensus folding algorithm giving a new variant of a thermodynamic structure based RNA gene finding program that is not biased by the dinucleotide content. SISSIz implements an efficient algorithm to randomize multiple alignments preserving dinucleotide content. It can be used to get more accurate estimates of false positive rates of existing programs, to produce negative controls for the training of machine learning based programs, or as standalone RNA gene finding program. Other applications in comparative genomics that require randomization of multiple alignments can be considered. SISSIz

  3. An online re-linearization scheme suited for Model Predictive and Linear Quadratic Control

    Henriksen, Lars Christian; Poulsen, Niels Kjølstad

    This technical note documents the equations for primal-dual interior-point quadratic programming problem solver used for MPC. The algorithm exploits the special structure of the MPC problem and is able to reduce the computational burden such that the computational burden scales with prediction...... horizon length in a linear way rather than cubic, which would be the case if the structure was not exploited. It is also shown how models used for design of model-based controllers, e.g. linear quadratic and model predictive, can be linearized both at equilibrium and non-equilibrium points, making...

  4. Prediction of RNA-Binding Proteins by Voting Systems

    C. R. Peng

    2011-01-01

    Full Text Available It is important to identify which proteins can interact with RNA for the purpose of protein annotation, since interactions between RNA and proteins influence the structure of the ribosome and play important roles in gene expression. This paper tries to identify proteins that can interact with RNA using voting systems. Firstly through Weka, 34 learning algorithms are chosen for investigation. Then simple majority voting system (SMVS is used for the prediction of RNA-binding proteins, achieving average ACC (overall prediction accuracy value of 79.72% and MCC (Matthew’s correlation coefficient value of 59.77% for the independent testing dataset. Then mRMR (minimum redundancy maximum relevance strategy is used, which is transferred into algorithm selection. In addition, the MCC value of each classifier is assigned to be the weight of the classifier’s vote. As a result, best average MCC values are attained when 22 algorithms are selected and integrated through weighted votes, which are 64.70% for the independent testing dataset, and ACC value is 82.04% at this moment.

  5. Development and evaluation of SBLINE, a suite of models for the prediction of pollution concentrations from vehicles in urban areas

    Namdeo, A.K.; Colls, J.J. [Environmental Science, University of Nottingham, Loughborough (United Kingdom)

    1996-09-06

    The assessment of air quality impacts from roadways is a major concern to urban planners, developers, health officials and engineers. This paper describes the development of a suite of models, called SBLINE, for prediction of pollution concentrations from vehicles in urban road networks. The first component of the suite is ROADFAC, an emission model for calculating emission rates for a road link with known vehicle fleet structure and operational details. ROADFAC can also calculate modal emission rates, caused by deceleration, idle, acceleration and cruise operational modes, by determining queue length and vehicle delay from traffic volume and signal phasing information. The other components of SBLINE are two dispersion models, called NOTLINE and CPB, for prediction of pollution concentrations contributed by different roadlinks in the network. These models use site geometry, meteorology, and traffic emissions calculated by ROADFAC to predict pollutant concentrations. The contribution from a given link is calculated by using NOTLINE if that link is situated in simple topography, or CPB is run if the link is inside a canyon or a cut-section. Finally, cumulative concentrations at any receptor location are calculated by adding the contributions from all roadlinks. SBLINE can be applied to any urban network of roads, with roadlinks located in either simple topography or street canyons. The program has been evaluated in one region of Leicester in the UK. The region represents a typical urban network of roads with some roads located in plain topography and some inside medium size canyons. Observed values of pollutant concentrations are compared with predictions made from detailed measurements of the vehicle population parameters, meteorology, and local street and building topography. Well-established statistical techniques have been used to show the potential of SBLINE for application to other road networks

  6. Distill: a suite of web servers for the prediction of one-, two- and three-dimensional structural features of proteins

    Walsh Ian

    2006-09-01

    Full Text Available Abstract Background We describe Distill, a suite of servers for the prediction of protein structural features: secondary structure; relative solvent accessibility; contact density; backbone structural motifs; residue contact maps at 6, 8 and 12 Angstrom; coarse protein topology. The servers are based on large-scale ensembles of recursive neural networks and trained on large, up-to-date, non-redundant subsets of the Protein Data Bank. Together with structural feature predictions, Distill includes a server for prediction of Cα traces for short proteins (up to 200 amino acids. Results The servers are state-of-the-art, with secondary structure predicted correctly for nearly 80% of residues (currently the top performance on EVA, 2-class solvent accessibility nearly 80% correct, and contact maps exceeding 50% precision on the top non-diagonal contacts. A preliminary implementation of the predictor of protein Cα traces featured among the top 20 Novel Fold predictors at the last CASP6 experiment as group Distill (ID 0348. The majority of the servers, including the Cα trace predictor, now take into account homology information from the PDB, when available, resulting in greatly improved reliability. Conclusion All predictions are freely available through a simple joint web interface and the results are returned by email. In a single submission the user can send protein sequences for a total of up to 32k residues to all or a selection of the servers. Distill is accessible at the address: http://distill.ucd.ie/distill/.

  7. Prediction of RNA secondary structure using generalized centroid estimators.

    Hamada, Michiaki; Kiryu, Hisanori; Sato, Kengo; Mituyama, Toutai; Asai, Kiyoshi

    2009-02-15

    Recent studies have shown that the methods for predicting secondary structures of RNAs on the basis of posterior decoding of the base-pairing probabilities has an advantage with respect to prediction accuracy over the conventionally utilized minimum free energy methods. However, there is room for improvement in the objective functions presented in previous studies, which are maximized in the posterior decoding with respect to the accuracy measures for secondary structures. We propose novel estimators which improve the accuracy of secondary structure prediction of RNAs. The proposed estimators maximize an objective function which is the weighted sum of the expected number of the true positives and that of the true negatives of the base pairs. The proposed estimators are also improved versions of the ones used in previous works, namely CONTRAfold for secondary structure prediction from a single RNA sequence and McCaskill-MEA for common secondary structure prediction from multiple alignments of RNA sequences. We clarify the relations between the proposed estimators and the estimators presented in previous works, and theoretically show that the previous estimators include additional unnecessary terms in the evaluation measures with respect to the accuracy. Furthermore, computational experiments confirm the theoretical analysis by indicating improvement in the empirical accuracy. The proposed estimators represent extensions of the centroid estimators proposed in Ding et al. and Carvalho and Lawrence, and are applicable to a wide variety of problems in bioinformatics. Supporting information and the CentroidFold software are available online at: http://www.ncrna.org/software/centroidfold/.

  8. Integrating chemical footprinting data into RNA secondary structure prediction.

    Kourosh Zarringhalam

    Full Text Available Chemical and enzymatic footprinting experiments, such as shape (selective 2'-hydroxyl acylation analyzed by primer extension, yield important information about RNA secondary structure. Indeed, since the [Formula: see text]-hydroxyl is reactive at flexible (loop regions, but unreactive at base-paired regions, shape yields quantitative data about which RNA nucleotides are base-paired. Recently, low error rates in secondary structure prediction have been reported for three RNAs of moderate size, by including base stacking pseudo-energy terms derived from shape data into the computation of minimum free energy secondary structure. Here, we describe a novel method, RNAsc (RNA soft constraints, which includes pseudo-energy terms for each nucleotide position, rather than only for base stacking positions. We prove that RNAsc is self-consistent, in the sense that the nucleotide-specific probabilities of being unpaired in the low energy Boltzmann ensemble always become more closely correlated with the input shape data after application of RNAsc. From this mathematical perspective, the secondary structure predicted by RNAsc should be 'correct', in as much as the shape data is 'correct'. We benchmark RNAsc against the previously mentioned method for eight RNAs, for which both shape data and native structures are known, to find the same accuracy in 7 out of 8 cases, and an improvement of 25% in one case. Furthermore, we present what appears to be the first direct comparison of shape data and in-line probing data, by comparing yeast asp-tRNA shape data from the literature with data from in-line probing experiments we have recently performed. With respect to several criteria, we find that shape data appear to be more robust than in-line probing data, at least in the case of asp-tRNA.

  9. Escherichia coli promoter sequences predict in vitro RNA polymerase selectivity.

    Mulligan, M E; Hawley, D K; Entriken, R; McClure, W R

    1984-01-11

    We describe a simple algorithm for computing a homology score for Escherichia coli promoters based on DNA sequence alone. The homology score was related to 31 values, measured in vitro, of RNA polymerase selectivity, which we define as the product KBk2, the apparent second order rate constant for open complex formation. We found that promoter strength could be predicted to within a factor of +/-4.1 in KBk2 over a range of 10(4) in the same parameter. The quantitative evaluation was linked to an automated (Apple II) procedure for searching and evaluating possible promoters in DNA sequence files.

  10. Escherichia coli promoter sequences predict in vitro RNA polymerase selectivity.

    Mulligan, M E; Hawley, D K; Entriken, R; McClure, W R

    1984-01-01

    We describe a simple algorithm for computing a homology score for Escherichia coli promoters based on DNA sequence alone. The homology score was related to 31 values, measured in vitro, of RNA polymerase selectivity, which we define as the product KBk2, the apparent second order rate constant for open complex formation. We found that promoter strength could be predicted to within a factor of +/-4.1 in KBk2 over a range of 10(4) in the same parameter. The quantitative evaluation was linked to ...

  11. piRNA analysis framework from small RNA-Seq data by a novel cluster prediction tool - PILFER.

    Ray, Rishav; Pandey, Priyanka

    2017-12-19

    With the increasing number of studies focusing on PIWI-interacting RNA (piRNAs), it is now pertinent to develop efficient tools dedicated towards piRNA analysis. We have developed a novel cluster prediction tool called PILFER (PIrna cLuster FindER), which can accurately predict piRNA clusters from small RNA sequencing data. PILFER is an open source, easy to use tool, and can be executed even on a personal computer with minimum resources. It uses a sliding-window mechanism by integrating the expression of the reads along with the spatial information to predict the piRNA clusters. We have additionally defined a piRNA analysis pipeline incorporating PILFER to detect and annotate piRNAs and their clusters from raw small RNA sequencing data and implemented it on publicly available data from healthy germline and somatic tissues. We compared PILFER with other existing piRNA cluster prediction tools and found it to be statistically more accurate and superior in many aspects such as the robustness of PILFER clusters is higher and memory efficiency is more. Overall, PILFER provides a fast and accurate solution to piRNA cluster prediction. Copyright © 2017 Elsevier Inc. All rights reserved.

  12. RNA Secondary Structure Prediction by Using Discrete Mathematics: An Interdisciplinary Research Experience for Undergraduate Students

    Ellington, Roni; Wachira, James; Nkwanta, Asamoah

    2010-01-01

    The focus of this Research Experience for Undergraduates (REU) project was on RNA secondary structure prediction by using a lattice walk approach. The lattice walk approach is a combinatorial and computational biology method used to enumerate possible secondary structures and predict RNA secondary structure from RNA sequences. The method uses…

  13. Comparison of efficacy, safety, and predictability of laser in situ keratomileusis using two laser suites

    Meidani A

    2016-08-01

    Full Text Available Alexandra Meidani,1–3 Chara Tzavara3 1Hypervision Laser Centre, 2Eye Day Clinic, 3Department of Hygiene, University of Athens Medical School, Centre for Health Services Research, Epidemiology and Medical Statistics, Athens, Greece Purpose: The main aim of this study was to compare the efficacy, safety, and predictability of femtosecond laser-assisted in situ keratomileusis performed by two different laser suites in the treatment of myopia for up to 6 months.Methods: In this two-site retrospective nonrandomized study, myopic eyes that underwent laser-assisted in situ keratomileusis using IntraLase FS 60 kHz formed group 1 and those using WaveLight FS200 femtosecond laser system formed group 2. Ablation was performed with Visx Star S4 IR and WaveLight EX500 Excimer lasers, respectively, in groups 1 and 2. Both groups were well matched for age, sex, and mean level of preoperative refractive spherical equivalent (MRSE. Uncorrected distance visual acuity, corrected distance visual acuity, and MRSE were evaluated preoperatively and at 1 week, 1 month, and 6 months after treatment.Results: Fifty-six eyes of 28 patients were included in the study. At 6-month follow-up postop, 78.6% of eyes in group 1 and 92.8% of eyes in group 2 achieved an uncorrected distance visual acuity of 20/20 or better (P=0.252. 35.7% and 50% in group 1 and group 2, respectively, gained one line (P=0.179. No eye lost lines of corrected distance visual acuity. Twenty-five eyes in group 1 (92.7% and 27 eyes in group 2 (96.3% had MRSE within ±0.5 D in the 6-month follow-up (P>0.999. The mean efficacy index at 6 months was similar in group 1 and group 2 (mean 1.10±0.12 [standard deviation] vs 1.10±0.1 (P=0.799. The mean safety index was similar in group 1 and group 2 (mean 1.10±0.10 [standard deviation] vs 1.10±0.09 (P=0.407.Conclusion: The outcomes were excellent between the two laser suites. There were no significant differences at 6-month follow-up postop between the two

  14. CentroidFold: a web server for RNA secondary structure prediction

    Sato, Kengo; Hamada, Michiaki; Asai, Kiyoshi; Mituyama, Toutai

    2009-01-01

    The CentroidFold web server (http://www.ncrna.org/centroidfold/) is a web application for RNA secondary structure prediction powered by one of the most accurate prediction engine. The server accepts two kinds of sequence data: a single RNA sequence and a multiple alignment of RNA sequences. It responses with a prediction result shown as a popular base-pair notation and a graph representation. PDF version of the graph representation is also available. For a multiple alignment sequence, the ser...

  15. DeepMirTar: a deep-learning approach for predicting human miRNA targets.

    Wen, Ming; Cong, Peisheng; Zhang, Zhimin; Lu, Hongmei; Li, Tonghua

    2018-06-01

    MicroRNAs (miRNAs) are small noncoding RNAs that function in RNA silencing and post-transcriptional regulation of gene expression by targeting messenger RNAs (mRNAs). Because the underlying mechanisms associated with miRNA binding to mRNA are not fully understood, a major challenge of miRNA studies involves the identification of miRNA-target sites on mRNA. In silico prediction of miRNA-target sites can expedite costly and time-consuming experimental work by providing the most promising miRNA-target-site candidates. In this study, we reported the design and implementation of DeepMirTar, a deep-learning-based approach for accurately predicting human miRNA targets at the site level. The predicted miRNA-target sites are those having canonical or non-canonical seed, and features, including high-level expert-designed, low-level expert-designed, and raw-data-level, were used to represent the miRNA-target site. Comparison with other state-of-the-art machine-learning methods and existing miRNA-target-prediction tools indicated that DeepMirTar improved overall predictive performance. DeepMirTar is freely available at https://github.com/Bjoux2/DeepMirTar_SdA. lith@tongji.edu.cn, hongmeilu@csu.edu.cn. Supplementary data are available at Bioinformatics online.

  16. SimRNA: a coarse-grained method for RNA folding simulations and 3D structure prediction.

    Boniecki, Michal J; Lach, Grzegorz; Dawson, Wayne K; Tomala, Konrad; Lukasz, Pawel; Soltysinski, Tomasz; Rother, Kristian M; Bujnicki, Janusz M

    2016-04-20

    RNA molecules play fundamental roles in cellular processes. Their function and interactions with other biomolecules are dependent on the ability to form complex three-dimensional (3D) structures. However, experimental determination of RNA 3D structures is laborious and challenging, and therefore, the majority of known RNAs remain structurally uncharacterized. Here, we present SimRNA: a new method for computational RNA 3D structure prediction, which uses a coarse-grained representation, relies on the Monte Carlo method for sampling the conformational space, and employs a statistical potential to approximate the energy and identify conformations that correspond to biologically relevant structures. SimRNA can fold RNA molecules using only sequence information, and, on established test sequences, it recapitulates secondary structure with high accuracy, including correct prediction of pseudoknots. For modeling of complex 3D structures, it can use additional restraints, derived from experimental or computational analyses, including information about secondary structure and/or long-range contacts. SimRNA also can be used to analyze conformational landscapes and identify potential alternative structures. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

  17. RNA secondary structure prediction with pseudoknots: Contribution of algorithm versus energy model.

    Jabbari, Hosna; Wark, Ian; Montemagno, Carlo

    2018-01-01

    RNA is a biopolymer with various applications inside the cell and in biotechnology. Structure of an RNA molecule mainly determines its function and is essential to guide nanostructure design. Since experimental structure determination is time-consuming and expensive, accurate computational prediction of RNA structure is of great importance. Prediction of RNA secondary structure is relatively simpler than its tertiary structure and provides information about its tertiary structure, therefore, RNA secondary structure prediction has received attention in the past decades. Numerous methods with different folding approaches have been developed for RNA secondary structure prediction. While methods for prediction of RNA pseudoknot-free structure (structures with no crossing base pairs) have greatly improved in terms of their accuracy, methods for prediction of RNA pseudoknotted secondary structure (structures with crossing base pairs) still have room for improvement. A long-standing question for improving the prediction accuracy of RNA pseudoknotted secondary structure is whether to focus on the prediction algorithm or the underlying energy model, as there is a trade-off on computational cost of the prediction algorithm versus the generality of the method. The aim of this work is to argue when comparing different methods for RNA pseudoknotted structure prediction, the combination of algorithm and energy model should be considered and a method should not be considered superior or inferior to others if they do not use the same scoring model. We demonstrate that while the folding approach is important in structure prediction, it is not the only important factor in prediction accuracy of a given method as the underlying energy model is also as of great value. Therefore we encourage researchers to pay particular attention in comparing methods with different energy models.

  18. Accurate microRNA target prediction correlates with protein repression levels

    Simossis Victor A

    2009-09-01

    Full Text Available Abstract Background MicroRNAs are small endogenously expressed non-coding RNA molecules that regulate target gene expression through translation repression or messenger RNA degradation. MicroRNA regulation is performed through pairing of the microRNA to sites in the messenger RNA of protein coding genes. Since experimental identification of miRNA target genes poses difficulties, computational microRNA target prediction is one of the key means in deciphering the role of microRNAs in development and disease. Results DIANA-microT 3.0 is an algorithm for microRNA target prediction which is based on several parameters calculated individually for each microRNA and combines conserved and non-conserved microRNA recognition elements into a final prediction score, which correlates with protein production fold change. Specifically, for each predicted interaction the program reports a signal to noise ratio and a precision score which can be used as an indication of the false positive rate of the prediction. Conclusion Recently, several computational target prediction programs were benchmarked based on a set of microRNA target genes identified by the pSILAC method. In this assessment DIANA-microT 3.0 was found to achieve the highest precision among the most widely used microRNA target prediction programs reaching approximately 66%. The DIANA-microT 3.0 prediction results are available online in a user friendly web server at http://www.microrna.gr/microT

  19. Genome-scale characterization of RNA tertiary structures and their functional impact by RNA solvent accessibility prediction.

    Yang, Yuedong; Li, Xiaomei; Zhao, Huiying; Zhan, Jian; Wang, Jihua; Zhou, Yaoqi

    2017-01-01

    As most RNA structures are elusive to structure determination, obtaining solvent accessible surface areas (ASAs) of nucleotides in an RNA structure is an important first step to characterize potential functional sites and core structural regions. Here, we developed RNAsnap, the first machine-learning method trained on protein-bound RNA structures for solvent accessibility prediction. Built on sequence profiles from multiple sequence alignment (RNAsnap-prof), the method provided robust prediction in fivefold cross-validation and an independent test (Pearson correlation coefficients, r, between predicted and actual ASA values are 0.66 and 0.63, respectively). Application of the method to 6178 mRNAs revealed its positive correlation to mRNA accessibility by dimethyl sulphate (DMS) experimentally measured in vivo (r = 0.37) but not in vitro (r = 0.07), despite the lack of training on mRNAs and the fact that DMS accessibility is only an approximation to solvent accessibility. We further found strong association across coding and noncoding regions between predicted solvent accessibility of the mutation site of a single nucleotide variant (SNV) and the frequency of that variant in the population for 2.2 million SNVs obtained in the 1000 Genomes Project. Moreover, mapping solvent accessibility of RNAs to the human genome indicated that introns, 5' cap of 5' and 3' cap of 3' untranslated regions, are more solvent accessible, consistent with their respective functional roles. These results support conformational selections as the mechanism for the formation of RNA-protein complexes and highlight the utility of genome-scale characterization of RNA tertiary structures by RNAsnap. The server and its stand-alone downloadable version are available at http://sparks-lab.org. © 2016 Yang et al.; Published by Cold Spring Harbor Laboratory Press for the RNA Society.

  20. Predicting protein-binding RNA nucleotides with consideration of binding partners.

    Tuvshinjargal, Narankhuu; Lee, Wook; Park, Byungkyu; Han, Kyungsook

    2015-06-01

    In recent years several computational methods have been developed to predict RNA-binding sites in protein. Most of these methods do not consider interacting partners of a protein, so they predict the same RNA-binding sites for a given protein sequence even if the protein binds to different RNAs. Unlike the problem of predicting RNA-binding sites in protein, the problem of predicting protein-binding sites in RNA has received little attention mainly because it is much more difficult and shows a lower accuracy on average. In our previous study, we developed a method that predicts protein-binding nucleotides from an RNA sequence. In an effort to improve the prediction accuracy and usefulness of the previous method, we developed a new method that uses both RNA and protein sequence data. In this study, we identified effective features of RNA and protein molecules and developed a new support vector machine (SVM) model to predict protein-binding nucleotides from RNA and protein sequence data. The new model that used both protein and RNA sequence data achieved a sensitivity of 86.5%, a specificity of 86.2%, a positive predictive value (PPV) of 72.6%, a negative predictive value (NPV) of 93.8% and Matthews correlation coefficient (MCC) of 0.69 in a 10-fold cross validation; it achieved a sensitivity of 58.8%, a specificity of 87.4%, a PPV of 65.1%, a NPV of 84.2% and MCC of 0.48 in independent testing. For comparative purpose, we built another prediction model that used RNA sequence data alone and ran it on the same dataset. In a 10 fold-cross validation it achieved a sensitivity of 85.7%, a specificity of 80.5%, a PPV of 67.7%, a NPV of 92.2% and MCC of 0.63; in independent testing it achieved a sensitivity of 67.7%, a specificity of 78.8%, a PPV of 57.6%, a NPV of 85.2% and MCC of 0.45. In both cross-validations and independent testing, the new model that used both RNA and protein sequences showed a better performance than the model that used RNA sequence data alone in

  1. A semi-supervised learning approach for RNA secondary structure prediction.

    Yonemoto, Haruka; Asai, Kiyoshi; Hamada, Michiaki

    2015-08-01

    RNA secondary structure prediction is a key technology in RNA bioinformatics. Most algorithms for RNA secondary structure prediction use probabilistic models, in which the model parameters are trained with reliable RNA secondary structures. Because of the difficulty of determining RNA secondary structures by experimental procedures, such as NMR or X-ray crystal structural analyses, there are still many RNA sequences that could be useful for training whose secondary structures have not been experimentally determined. In this paper, we introduce a novel semi-supervised learning approach for training parameters in a probabilistic model of RNA secondary structures in which we employ not only RNA sequences with annotated secondary structures but also ones with unknown secondary structures. Our model is based on a hybrid of generative (stochastic context-free grammars) and discriminative models (conditional random fields) that has been successfully applied to natural language processing. Computational experiments indicate that the accuracy of secondary structure prediction is improved by incorporating RNA sequences with unknown secondary structures into training. To our knowledge, this is the first study of a semi-supervised learning approach for RNA secondary structure prediction. This technique will be useful when the number of reliable structures is limited. Copyright © 2015 Elsevier Ltd. All rights reserved.

  2. Tumor RNA disruption predicts survival benefit from breast cancer chemotherapy.

    Parissenti, Amadeo M; Guo, Baoqing; Pritzker, Laura B; Pritzker, Kenneth P H; Wang, Xiaohui; Zhu, Mu; Shepherd, Lois E; Trudeau, Maureen E

    2015-08-01

    In a prior substudy of the CAN-NCIC-MA.22 clinical trial (ClinicalTrials.gov identifier NCT00066443), we observed that neoadjuvant chemotherapy reduced tumor RNA integrity in breast cancer patients, a phenomenon we term "RNA disruption." The purpose of the current study was to assess in the full patient cohort the relationship between mid-treatment tumor RNA disruption and both pCR post-treatment and, subsequently, disease-free survival (DFS) up to 108 months post-treatment. To meet these objectives, we developed the RNA disruption assay (RDA) to quantify RNA disruption and stratify it into 3 response zones of clinical importance. Zone 1 is a level of RNA disruption inadequate for pathologic complete response (pCR); Zone 2 is an intermediate level, while Zone 3 has high RNA disruption. The same RNA disruption cut points developed for pCR response were then utilized for DFS. Tumor RDA identified >fourfold more chemotherapy non-responders than did clinical response by calipers. pCR responders were clustered in RDA Zone 3, irrespective of tumor subtype. DFS was about 2-fold greater for patients with tumors in Zone 3 compared to Zone 1 patients. Kaplan-Meier survival curves corroborated these findings that high tumor RNA disruption was associated with increased DFS. DFS values for patients in zone 3 that did not achieve a pCR were similar to that of pCR recipients across tumor subtypes, including patients with hormone receptor positive tumors that seldom achieve a pCR. RDA appears superior to pCR as a chemotherapy response biomarker, supporting the prospect of its use in response-guided chemotherapy.

  3. DIANA-microT web server: elucidating microRNA functions through target prediction.

    Maragkakis, M; Reczko, M; Simossis, V A; Alexiou, P; Papadopoulos, G L; Dalamagas, T; Giannopoulos, G; Goumas, G; Koukis, E; Kourtis, K; Vergoulis, T; Koziris, N; Sellis, T; Tsanakas, P; Hatzigeorgiou, A G

    2009-07-01

    Computational microRNA (miRNA) target prediction is one of the key means for deciphering the role of miRNAs in development and disease. Here, we present the DIANA-microT web server as the user interface to the DIANA-microT 3.0 miRNA target prediction algorithm. The web server provides extensive information for predicted miRNA:target gene interactions with a user-friendly interface, providing extensive connectivity to online biological resources. Target gene and miRNA functions may be elucidated through automated bibliographic searches and functional information is accessible through Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. The web server offers links to nomenclature, sequence and protein databases, and users are facilitated by being able to search for targeted genes using different nomenclatures or functional features, such as the genes possible involvement in biological pathways. The target prediction algorithm supports parameters calculated individually for each miRNA:target gene interaction and provides a signal-to-noise ratio and a precision score that helps in the evaluation of the significance of the predicted results. Using a set of miRNA targets recently identified through the pSILAC method, the performance of several computational target prediction programs was assessed. DIANA-microT 3.0 achieved there with 66% the highest ratio of correctly predicted targets over all predicted targets. The DIANA-microT web server is freely available at www.microrna.gr/microT.

  4. A Comparative Taxonomy of Parallel Algorithms for RNA Secondary Structure Prediction

    Al-Khatib, Ra’ed M.; Abdullah, Rosni; Rashid, Nur’Aini Abdul

    2010-01-01

    RNA molecules have been discovered playing crucial roles in numerous biological and medical procedures and processes. RNA structures determination have become a major problem in the biology context. Recently, computer scientists have empowered the biologists with RNA secondary structures that ease an understanding of the RNA functions and roles. Detecting RNA secondary structure is an NP-hard problem, especially in pseudoknotted RNA structures. The detection process is also time-consuming; as a result, an alternative approach such as using parallel architectures is a desirable option. The main goal in this paper is to do an intensive investigation of parallel methods used in the literature to solve the demanding issues, related to the RNA secondary structure prediction methods. Then, we introduce a new taxonomy for the parallel RNA folding methods. Based on this proposed taxonomy, a systematic and scientific comparison is performed among these existing methods. PMID:20458364

  5. Evolving stochastic context-free grammars for RNA secondary structure prediction

    Anderson, James WJ; Tataru, Paula Cristina; Stains, Joe

    2012-01-01

    Background Stochastic Context-Free Grammars (SCFGs) were applied successfully to RNA secondary structure prediction in the early 90s, and used in combination with comparative methods in the late 90s. The set of SCFGs potentially useful for RNA secondary structure prediction is very large, but a few...... to structure prediction as has been previously suggested. Results These search techniques were applied to predict RNA secondary structure on a maximal data set and revealed new and interesting grammars, though none are dramatically better than classic grammars. In general, results showed that many grammars...... with quite different structure could have very similar predictive ability. Many ambiguous grammars were found which were at least as effective as the best current unambiguous grammars. Conclusions Overall the method of evolving SCFGs for RNA secondary structure prediction proved effective in finding many...

  6. TAPIR, a web server for the prediction of plant microRNA targets, including target mimics.

    Bonnet, Eric; He, Ying; Billiau, Kenny; Van de Peer, Yves

    2010-06-15

    We present a new web server called TAPIR, designed for the prediction of plant microRNA targets. The server offers the possibility to search for plant miRNA targets using a fast and a precise algorithm. The precise option is much slower but guarantees to find less perfectly paired miRNA-target duplexes. Furthermore, the precise option allows the prediction of target mimics, which are characterized by a miRNA-target duplex having a large loop, making them undetectable by traditional tools. The TAPIR web server can be accessed at: http://bioinformatics.psb.ugent.be/webtools/tapir. Supplementary data are available at Bioinformatics online.

  7. Comparison of RNA-seq and microarray-based models for clinical endpoint prediction.

    Zhang, Wenqian; Yu, Ying; Hertwig, Falk; Thierry-Mieg, Jean; Zhang, Wenwei; Thierry-Mieg, Danielle; Wang, Jian; Furlanello, Cesare; Devanarayan, Viswanath; Cheng, Jie; Deng, Youping; Hero, Barbara; Hong, Huixiao; Jia, Meiwen; Li, Li; Lin, Simon M; Nikolsky, Yuri; Oberthuer, André; Qing, Tao; Su, Zhenqiang; Volland, Ruth; Wang, Charles; Wang, May D; Ai, Junmei; Albanese, Davide; Asgharzadeh, Shahab; Avigad, Smadar; Bao, Wenjun; Bessarabova, Marina; Brilliant, Murray H; Brors, Benedikt; Chierici, Marco; Chu, Tzu-Ming; Zhang, Jibin; Grundy, Richard G; He, Min Max; Hebbring, Scott; Kaufman, Howard L; Lababidi, Samir; Lancashire, Lee J; Li, Yan; Lu, Xin X; Luo, Heng; Ma, Xiwen; Ning, Baitang; Noguera, Rosa; Peifer, Martin; Phan, John H; Roels, Frederik; Rosswog, Carolina; Shao, Susan; Shen, Jie; Theissen, Jessica; Tonini, Gian Paolo; Vandesompele, Jo; Wu, Po-Yen; Xiao, Wenzhong; Xu, Joshua; Xu, Weihong; Xuan, Jiekun; Yang, Yong; Ye, Zhan; Dong, Zirui; Zhang, Ke K; Yin, Ye; Zhao, Chen; Zheng, Yuanting; Wolfinger, Russell D; Shi, Tieliu; Malkas, Linda H; Berthold, Frank; Wang, Jun; Tong, Weida; Shi, Leming; Peng, Zhiyu; Fischer, Matthias

    2015-06-25

    Gene expression profiling is being widely applied in cancer research to identify biomarkers for clinical endpoint prediction. Since RNA-seq provides a powerful tool for transcriptome-based applications beyond the limitations of microarrays, we sought to systematically evaluate the performance of RNA-seq-based and microarray-based classifiers in this MAQC-III/SEQC study for clinical endpoint prediction using neuroblastoma as a model. We generate gene expression profiles from 498 primary neuroblastomas using both RNA-seq and 44 k microarrays. Characterization of the neuroblastoma transcriptome by RNA-seq reveals that more than 48,000 genes and 200,000 transcripts are being expressed in this malignancy. We also find that RNA-seq provides much more detailed information on specific transcript expression patterns in clinico-genetic neuroblastoma subgroups than microarrays. To systematically compare the power of RNA-seq and microarray-based models in predicting clinical endpoints, we divide the cohort randomly into training and validation sets and develop 360 predictive models on six clinical endpoints of varying predictability. Evaluation of factors potentially affecting model performances reveals that prediction accuracies are most strongly influenced by the nature of the clinical endpoint, whereas technological platforms (RNA-seq vs. microarrays), RNA-seq data analysis pipelines, and feature levels (gene vs. transcript vs. exon-junction level) do not significantly affect performances of the models. We demonstrate that RNA-seq outperforms microarrays in determining the transcriptomic characteristics of cancer, while RNA-seq and microarray-based models perform similarly in clinical endpoint prediction. Our findings may be valuable to guide future studies on the development of gene expression-based predictive models and their implementation in clinical practice.

  8. Prediction and Dissection of Protein-RNA Interactions by Molecular Descriptors.

    Liu, Zhi-Ping; Chen, Luonan

    2016-01-01

    Protein-RNA interactions play crucial roles in numerous biological processes. However, detecting the interactions and binding sites between protein and RNA by traditional experiments is still time consuming and labor costing. Thus, it is of importance to develop bioinformatics methods for predicting protein-RNA interactions and binding sites. Accurate prediction of protein-RNA interactions and recognitions will highly benefit to decipher the interaction mechanisms between protein and RNA, as well as to improve the RNA-related protein engineering and drug design. In this work, we summarize the current bioinformatics strategies of predicting protein-RNA interactions and dissecting protein-RNA interaction mechanisms from local structure binding motifs. In particular, we focus on the feature-based machine learning methods, in which the molecular descriptors of protein and RNA are extracted and integrated as feature vectors of representing the interaction events and recognition residues. In addition, the available methods are classified and compared comprehensively. The molecular descriptors are expected to elucidate the binding mechanisms of protein-RNA interaction and reveal the functional implications from structural complementary perspective.

  9. TBI server: a web server for predicting ion effects in RNA folding.

    Zhu, Yuhong; He, Zhaojian; Chen, Shi-Jie

    2015-01-01

    Metal ions play a critical role in the stabilization of RNA structures. Therefore, accurate prediction of the ion effects in RNA folding can have a far-reaching impact on our understanding of RNA structure and function. Multivalent ions, especially Mg²⁺, are essential for RNA tertiary structure formation. These ions can possibly become strongly correlated in the close vicinity of RNA surface. Most of the currently available software packages, which have widespread success in predicting ion effects in biomolecular systems, however, do not explicitly account for the ion correlation effect. Therefore, it is important to develop a software package/web server for the prediction of ion electrostatics in RNA folding by including ion correlation effects. The TBI web server http://rna.physics.missouri.edu/tbi_index.html provides predictions for the total electrostatic free energy, the different free energy components, and the mean number and the most probable distributions of the bound ions. A novel feature of the TBI server is its ability to account for ion correlation and ion distribution fluctuation effects. By accounting for the ion correlation and fluctuation effects, the TBI server is a unique online tool for computing ion-mediated electrostatic properties for given RNA structures. The results can provide important data for in-depth analysis for ion effects in RNA folding including the ion-dependence of folding stability, ion uptake in the folding process, and the interplay between the different energetic components.

  10. TBI server: a web server for predicting ion effects in RNA folding.

    Yuhong Zhu

    Full Text Available Metal ions play a critical role in the stabilization of RNA structures. Therefore, accurate prediction of the ion effects in RNA folding can have a far-reaching impact on our understanding of RNA structure and function. Multivalent ions, especially Mg²⁺, are essential for RNA tertiary structure formation. These ions can possibly become strongly correlated in the close vicinity of RNA surface. Most of the currently available software packages, which have widespread success in predicting ion effects in biomolecular systems, however, do not explicitly account for the ion correlation effect. Therefore, it is important to develop a software package/web server for the prediction of ion electrostatics in RNA folding by including ion correlation effects.The TBI web server http://rna.physics.missouri.edu/tbi_index.html provides predictions for the total electrostatic free energy, the different free energy components, and the mean number and the most probable distributions of the bound ions. A novel feature of the TBI server is its ability to account for ion correlation and ion distribution fluctuation effects.By accounting for the ion correlation and fluctuation effects, the TBI server is a unique online tool for computing ion-mediated electrostatic properties for given RNA structures. The results can provide important data for in-depth analysis for ion effects in RNA folding including the ion-dependence of folding stability, ion uptake in the folding process, and the interplay between the different energetic components.

  11. Advancing viral RNA structure prediction: measuring the thermodynamics of pyrimidine-rich internal loops.

    Phan, Andy; Mailey, Katherine; Saeki, Jessica; Gu, Xiaobo; Schroeder, Susan J

    2017-05-01

    Accurate thermodynamic parameters improve RNA structure predictions and thus accelerate understanding of RNA function and the identification of RNA drug binding sites. Many viral RNA structures, such as internal ribosome entry sites, have internal loops and bulges that are potential drug target sites. Current models used to predict internal loops are biased toward small, symmetric purine loops, and thus poorly predict asymmetric, pyrimidine-rich loops with >6 nucleotides (nt) that occur frequently in viral RNA. This article presents new thermodynamic data for 40 pyrimidine loops, many of which can form UU or protonated CC base pairs. Uracil and protonated cytosine base pairs stabilize asymmetric internal loops. Accurate prediction rules are presented that account for all thermodynamic measurements of RNA asymmetric internal loops. New loop initiation terms for loops with >6 nt are presented that do not follow previous assumptions that increasing asymmetry destabilizes loops. Since the last 2004 update, 126 new loops with asymmetry or sizes greater than 2 × 2 have been measured. These new measurements significantly deepen and diversify the thermodynamic database for RNA. These results will help better predict internal loops that are larger, pyrimidine-rich, and occur within viral structures such as internal ribosome entry sites. © 2017 Phan et al.; Published by Cold Spring Harbor Laboratory Press for the RNA Society.

  12. Vfold: a web server for RNA structure and folding thermodynamics prediction.

    Xu, Xiaojun; Zhao, Peinan; Chen, Shi-Jie

    2014-01-01

    The ever increasing discovery of non-coding RNAs leads to unprecedented demand for the accurate modeling of RNA folding, including the predictions of two-dimensional (base pair) and three-dimensional all-atom structures and folding stabilities. Accurate modeling of RNA structure and stability has far-reaching impact on our understanding of RNA functions in human health and our ability to design RNA-based therapeutic strategies. The Vfold server offers a web interface to predict (a) RNA two-dimensional structure from the nucleotide sequence, (b) three-dimensional structure from the two-dimensional structure and the sequence, and (c) folding thermodynamics (heat capacity melting curve) from the sequence. To predict the two-dimensional structure (base pairs), the server generates an ensemble of structures, including loop structures with the different intra-loop mismatches, and evaluates the free energies using the experimental parameters for the base stacks and the loop entropy parameters given by a coarse-grained RNA folding model (the Vfold model) for the loops. To predict the three-dimensional structure, the server assembles the motif scaffolds using structure templates extracted from the known PDB structures and refines the structure using all-atom energy minimization. The Vfold-based web server provides a user friendly tool for the prediction of RNA structure and stability. The web server and the source codes are freely accessible for public use at "http://rna.physics.missouri.edu".

  13. MiRNA expression patterns predict survival in glioblastoma

    Niyazi, Maximilian; Belka, Claus; Zehentmayr, Franz; Niemöller, Olivier M; Eigenbrod, Sabina; Kretzschmar, Hans; Osthoff, Klaus-Schulze; Tonn, Jörg-Christian; Atkinson, Mike; Mörtl, Simone

    2011-01-01

    In order to define new prognostic subgroups in patients with glioblastoma a miRNA screen (> 1000 miRNAs) from paraffin tissues followed by a bio-mathematical analysis was performed. 35 glioblastoma patients treated between 7/2005 - 8/2008 at a single institution with surgery and postoperative radio(chemo)therapy were included in this retrospective analysis. For microarray analysis the febit biochip 'Geniom ® Biochip MPEA homo-sapiens' was used. Total RNA was isolated from FFPE tissue sections and 1100 different miRNAs were analyzed. It was possible to define a distinct miRNA expression pattern allowing for a separation of distinct prognostic subgroups. The defined miRNA pattern was significantly associated with early death versus long-term survival (split at 450 days) (p = 0.01). The pattern and the prognostic power were both independent of the MGMT status. At present, this is the first dataset defining a prognostic role of miRNA expression patterns in patients with glioblastoma. Having defined such a pattern, a prospective validation of this observation is required

  14. Feature-Based and String-Based Models for Predicting RNA-Protein Interaction

    Donald Adjeroh

    2018-03-01

    Full Text Available In this work, we study two approaches for the problem of RNA-Protein Interaction (RPI. In the first approach, we use a feature-based technique by combining extracted features from both sequences and secondary structures. The feature-based approach enhanced the prediction accuracy as it included much more available information about the RNA-protein pairs. In the second approach, we apply search algorithms and data structures to extract effective string patterns for prediction of RPI, using both sequence information (protein and RNA sequences, and structure information (protein and RNA secondary structures. This led to different string-based models for predicting interacting RNA-protein pairs. We show results that demonstrate the effectiveness of the proposed approaches, including comparative results against leading state-of-the-art methods.

  15. Statistical properties of thermodynamically predicted RNA secondary structures in viral genomes

    Spanò, M.; Lillo, F.; Miccichè, S.; Mantegna, R. N.

    2008-10-01

    By performing a comprehensive study on 1832 segments of 1212 complete genomes of viruses, we show that in viral genomes the hairpin structures of thermodynamically predicted RNA secondary structures are more abundant than expected under a simple random null hypothesis. The detected hairpin structures of RNA secondary structures are present both in coding and in noncoding regions for the four groups of viruses categorized as dsDNA, dsRNA, ssDNA and ssRNA. For all groups, hairpin structures of RNA secondary structures are detected more frequently than expected for a random null hypothesis in noncoding rather than in coding regions. However, potential RNA secondary structures are also present in coding regions of dsDNA group. In fact, we detect evolutionary conserved RNA secondary structures in conserved coding and noncoding regions of a large set of complete genomes of dsDNA herpesviruses.

  16. CRISPRTarget: bioinformatic prediction and analysis of crRNA targets

    Biswas, A.; Gagnon, J.N.; Brouns, S.J.J.; Fineran, P.C.; Brown, C.M.

    2013-01-01

    The bacterial and archaeal CRISPR/Cas adaptive immune system targets specific protospacer nucleotide sequences in invading organisms. This requires base pairing between processed CRISPR RNA and the target protospacer. For type I and II CRISPR/Cas systems, protospacer adjacent motifs (PAM) are

  17. LDAP: a web server for lncRNA-disease association prediction.

    Lan, Wei; Li, Min; Zhao, Kaijie; Liu, Jin; Wu, Fang-Xiang; Pan, Yi; Wang, Jianxin

    2017-02-01

    Increasing evidences have demonstrated that long noncoding RNAs (lncRNAs) play important roles in many human diseases. Therefore, predicting novel lncRNA-disease associations would contribute to dissect the complex mechanisms of disease pathogenesis. Some computational methods have been developed to infer lncRNA-disease associations. However, most of these methods infer lncRNA-disease associations only based on single data resource. In this paper, we propose a new computational method to predict lncRNA-disease associations by integrating multiple biological data resources. Then, we implement this method as a web server for lncRNA-disease association prediction (LDAP). The input of the LDAP server is the lncRNA sequence. The LDAP predicts potential lncRNA-disease associations by using a bagging SVM classifier based on lncRNA similarity and disease similarity. The web server is available at http://bioinformatics.csu.edu.cn/ldap jxwang@mail.csu.edu.cn. Supplementary data are available at Bioinformatics online.

  18. MCTBI: a web server for predicting metal ion effects in RNA structures.

    Sun, Li-Zhen; Zhang, Jing-Xiang; Chen, Shi-Jie

    2017-08-01

    Metal ions play critical roles in RNA structure and function. However, web servers and software packages for predicting ion effects in RNA structures are notably scarce. Furthermore, the existing web servers and software packages mainly neglect ion correlation and fluctuation effects, which are potentially important for RNAs. We here report a new web server, the MCTBI server (http://rna.physics.missouri.edu/MCTBI), for the prediction of ion effects for RNA structures. This server is based on the recently developed MCTBI, a model that can account for ion correlation and fluctuation effects for nucleic acid structures and can provide improved predictions for the effects of metal ions, especially for multivalent ions such as Mg 2+ effects, as shown by extensive theory-experiment test results. The MCTBI web server predicts metal ion binding fractions, the most probable bound ion distribution, the electrostatic free energy of the system, and the free energy components. The results provide mechanistic insights into the role of metal ions in RNA structure formation and folding stability, which is important for understanding RNA functions and the rational design of RNA structures. © 2017 Sun et al.; Published by Cold Spring Harbor Laboratory Press for the RNA Society.

  19. Use of tiling array data and RNA secondary structure predictions to identify noncoding RNA genes

    Weile, Christian; Gardner, Paul P; Hedegaard, Mads M

    2007-01-01

    neuroblastoma cell line SK-N-AS. Using this strategy, we identify thousands of human candidate RNA genes. To further verify the expression of these genes, we focused on candidate genes that had a stable hairpin structures or a high level of covariance. Using northern blotting, we verify the expression of 2 out...

  20. Circular RNA Signature Predicts Gemcitabine Resistance of Pancreatic Ductal Adenocarcinoma

    Feng Shao

    2018-06-01

    Full Text Available Gemcitabine resistance is currently the main problem of chemotherapy for advanced pancreatic cancer patients. The resistance is thought to be caused by altered drug metabolism or reduced apoptosis of cancer cells. However, the underlying mechanism of Gemcitabine resistance in pancreatic cancer remains unclear. In this study, we established Gemcitabine resistant PANC-1 (PANC-1-GR cell lines and compared the circular RNAs (circRNAs profiles between PANC-1 cells and PANC-1-GR cells by RNA sequencing. Differentially expressed circRNAs were demonstrated using scatter plot and cluster heatmap analysis. Gene ontology and pathway analysis were performed to systemically map the genes which are functionally associated to those differentially expressed circRNAs identified from our data. The expression of the differentially expressed circRNAs picked up by RNAseq in PANC-1-GR cells was further validated by qRT-PCR and two circRNAs were eventually identified as the most distinct targets. Consistently, by analyzing plasma samples form pancreatic ductal adenocarcinoma (PDAC patients, the two circRNAs showed more significant expression in the Gemcitabine non-responsive patients than the responsive ones. In addition, we found that silencing of the two circRNAs could restore the sensitivity of PANC-1-GR cells to Gemcitabine treatment, while over-expression of them could increase the resistance of normal PANC-1 and MIA PACA-2 cells, suggesting that they might serve as drug targets for Gemcitabine resistance. Furthermore, the miRNA interaction networks were also explored based on the correlation analysis of the target microRNAs of these two circRNAs. In conclusion, we successfully established new PANC-1-GR cells, systemically characterized the circRNA and miRNA profiles, and identified two circRNAs as novel biomarkers and potential therapeutic targets for Gemcitabine non-responsive PDAC patients.

  1. RNA secondary structure prediction by using discrete mathematics: an interdisciplinary research experience for undergraduate students.

    Ellington, Roni; Wachira, James; Nkwanta, Asamoah

    2010-01-01

    The focus of this Research Experience for Undergraduates (REU) project was on RNA secondary structure prediction by using a lattice walk approach. The lattice walk approach is a combinatorial and computational biology method used to enumerate possible secondary structures and predict RNA secondary structure from RNA sequences. The method uses discrete mathematical techniques and identifies specified base pairs as parameters. The goal of the REU was to introduce upper-level undergraduate students to the principles and challenges of interdisciplinary research in molecular biology and discrete mathematics. At the beginning of the project, students from the biology and mathematics departments of a mid-sized university received instruction on the role of secondary structure in the function of eukaryotic RNAs and RNA viruses, RNA related to combinatorics, and the National Center for Biotechnology Information resources. The student research projects focused on RNA secondary structure prediction on a regulatory region of the yellow fever virus RNA genome and on an untranslated region of an mRNA of a gene associated with the neurological disorder epilepsy. At the end of the project, the REU students gave poster and oral presentations, and they submitted written final project reports to the program director. The outcome of the REU was that the students gained transferable knowledge and skills in bioinformatics and an awareness of the applications of discrete mathematics to biological research problems.

  2. RNA Secondary Structure Prediction by Using Discrete Mathematics: An Interdisciplinary Research Experience for Undergraduate Students

    Ellington, Roni; Wachira, James

    2010-01-01

    The focus of this Research Experience for Undergraduates (REU) project was on RNA secondary structure prediction by using a lattice walk approach. The lattice walk approach is a combinatorial and computational biology method used to enumerate possible secondary structures and predict RNA secondary structure from RNA sequences. The method uses discrete mathematical techniques and identifies specified base pairs as parameters. The goal of the REU was to introduce upper-level undergraduate students to the principles and challenges of interdisciplinary research in molecular biology and discrete mathematics. At the beginning of the project, students from the biology and mathematics departments of a mid-sized university received instruction on the role of secondary structure in the function of eukaryotic RNAs and RNA viruses, RNA related to combinatorics, and the National Center for Biotechnology Information resources. The student research projects focused on RNA secondary structure prediction on a regulatory region of the yellow fever virus RNA genome and on an untranslated region of an mRNA of a gene associated with the neurological disorder epilepsy. At the end of the project, the REU students gave poster and oral presentations, and they submitted written final project reports to the program director. The outcome of the REU was that the students gained transferable knowledge and skills in bioinformatics and an awareness of the applications of discrete mathematics to biological research problems. PMID:20810968

  3. RNA.

    Darnell, James E., Jr.

    1985-01-01

    Ribonucleic acid (RNA) converts genetic information into protein and usually must be processed to serve its function. RNA types, chemical structure, protein synthesis, translation, manufacture, and processing are discussed. Concludes that the first genes might have been spliced RNA and that humans might be closer than bacteria to primitive…

  4. Sparse RNA folding revisited: space-efficient minimum free energy structure prediction.

    Will, Sebastian; Jabbari, Hosna

    2016-01-01

    RNA secondary structure prediction by energy minimization is the central computational tool for the analysis of structural non-coding RNAs and their interactions. Sparsification has been successfully applied to improve the time efficiency of various structure prediction algorithms while guaranteeing the same result; however, for many such folding problems, space efficiency is of even greater concern, particularly for long RNA sequences. So far, space-efficient sparsified RNA folding with fold reconstruction was solved only for simple base-pair-based pseudo-energy models. Here, we revisit the problem of space-efficient free energy minimization. Whereas the space-efficient minimization of the free energy has been sketched before, the reconstruction of the optimum structure has not even been discussed. We show that this reconstruction is not possible in trivial extension of the method for simple energy models. Then, we present the time- and space-efficient sparsified free energy minimization algorithm SparseMFEFold that guarantees MFE structure prediction. In particular, this novel algorithm provides efficient fold reconstruction based on dynamically garbage-collected trace arrows. The complexity of our algorithm depends on two parameters, the number of candidates Z and the number of trace arrows T; both are bounded by [Formula: see text], but are typically much smaller. The time complexity of RNA folding is reduced from [Formula: see text] to [Formula: see text]; the space complexity, from [Formula: see text] to [Formula: see text]. Our empirical results show more than 80 % space savings over RNAfold [Vienna RNA package] on the long RNAs from the RNA STRAND database (≥2500 bases). The presented technique is intentionally generalizable to complex prediction algorithms; due to their high space demands, algorithms like pseudoknot prediction and RNA-RNA-interaction prediction are expected to profit even stronger than "standard" MFE folding. SparseMFEFold is free

  5. A Meta-Path-Based Prediction Method for Human miRNA-Target Association

    Jiawei Luo

    2016-01-01

    Full Text Available MicroRNAs (miRNAs are short noncoding RNAs that play important roles in regulating gene expressing, and the perturbed miRNAs are often associated with development and tumorigenesis as they have effects on their target mRNA. Predicting potential miRNA-target associations from multiple types of genomic data is a considerable problem in the bioinformatics research. However, most of the existing methods did not fully use the experimentally validated miRNA-mRNA interactions. Here, we developed RMLM and RMLMSe to predict the relationship between miRNAs and their targets. RMLM and RMLMSe are global approaches as they can reconstruct the missing associations for all the miRNA-target simultaneously and RMLMSe demonstrates that the integration of sequence information can improve the performance of RMLM. In RMLM, we use RM measure to evaluate different relatedness between miRNA and its target based on different meta-paths; logistic regression and MLE method are employed to estimate the weight of different meta-paths. In RMLMSe, sequence information is utilized to improve the performance of RMLM. Here, we carry on fivefold cross validation and pathway enrichment analysis to prove the performance of our methods. The fivefold experiments show that our methods have higher AUC scores compared with other methods and the integration of sequence information can improve the performance of miRNA-target association prediction.

  6. Improved Model for Predicting the Free Energy Contribution of Dinucleotide Bulges to RNA Duplex Stability.

    Tomcho, Jeremy C; Tillman, Magdalena R; Znosko, Brent M

    2015-09-01

    Predicting the secondary structure of RNA is an intermediate in predicting RNA three-dimensional structure. Commonly, determining RNA secondary structure from sequence uses free energy minimization and nearest neighbor parameters. Current algorithms utilize a sequence-independent model to predict free energy contributions of dinucleotide bulges. To determine if a sequence-dependent model would be more accurate, short RNA duplexes containing dinucleotide bulges with different sequences and nearest neighbor combinations were optically melted to derive thermodynamic parameters. These data suggested energy contributions of dinucleotide bulges were sequence-dependent, and a sequence-dependent model was derived. This model assigns free energy penalties based on the identity of nucleotides in the bulge (3.06 kcal/mol for two purines, 2.93 kcal/mol for two pyrimidines, 2.71 kcal/mol for 5'-purine-pyrimidine-3', and 2.41 kcal/mol for 5'-pyrimidine-purine-3'). The predictive model also includes a 0.45 kcal/mol penalty for an A-U pair adjacent to the bulge and a -0.28 kcal/mol bonus for a G-U pair adjacent to the bulge. The new sequence-dependent model results in predicted values within, on average, 0.17 kcal/mol of experimental values, a significant improvement over the sequence-independent model. This model and new experimental values can be incorporated into algorithms that predict RNA stability and secondary structure from sequence.

  7. Hierarchical folding of multiple sequence alignments for the prediction of structures and RNA-RNA interactions

    Seemann, Ernst Stefan; Richter, Andreas S.; Gorodkin, Jan

    2010-01-01

    of that used for individual multiple alignments. Results: We derived a rather extensive algorithm. One of the advantages of our approach (in contrast to other RNARNA interaction prediction methods) is the application of covariance detection and prediction of pseudoknots between intra- and inter-molecular base...... pairs. As a proof of concept, we show an example and discuss the strengths and weaknesses of the approach....

  8. Plant MicroRNA Prediction by Supervised Machine Learning Using C5.0 Decision Trees.

    Williams, Philip H; Eyles, Rod; Weiller, Georg

    2012-01-01

    MicroRNAs (miRNAs) are nonprotein coding RNAs between 20 and 22 nucleotides long that attenuate protein production. Different types of sequence data are being investigated for novel miRNAs, including genomic and transcriptomic sequences. A variety of machine learning methods have successfully predicted miRNA precursors, mature miRNAs, and other nonprotein coding sequences. MirTools, mirDeep2, and miRanalyzer require "read count" to be included with the input sequences, which restricts their use to deep-sequencing data. Our aim was to train a predictor using a cross-section of different species to accurately predict miRNAs outside the training set. We wanted a system that did not require read-count for prediction and could therefore be applied to short sequences extracted from genomic, EST, or RNA-seq sources. A miRNA-predictive decision-tree model has been developed by supervised machine learning. It only requires that the corresponding genome or transcriptome is available within a sequence window that includes the precursor candidate so that the required sequence features can be collected. Some of the most critical features for training the predictor are the miRNA:miRNA(∗) duplex energy and the number of mismatches in the duplex. We present a cross-species plant miRNA predictor with 84.08% sensitivity and 98.53% specificity based on rigorous testing by leave-one-out validation.

  9. Computational prediction and experimental validation of Ciona intestinalis microRNA genes

    Pasquinelli Amy E

    2007-11-01

    Full Text Available Abstract Background This study reports the first collection of validated microRNA genes in the sea squirt, Ciona intestinalis. MicroRNAs are processed from hairpin precursors to ~22 nucleotide RNAs that base pair to target mRNAs and inhibit expression. As a member of the subphylum Urochordata (Tunicata whose larval form has a notochord, the sea squirt is situated at the emergence of vertebrates, and therefore may provide information about the evolution of molecular regulators of early development. Results In this study, computational methods were used to predict 14 microRNA gene families in Ciona intestinalis. The microRNA prediction algorithm utilizes configurable microRNA sequence conservation and stem-loop specificity parameters, grouping by miRNA family, and phylogenetic conservation to the related species, Ciona savignyi. The expression for 8, out of 9 attempted, of the putative microRNAs in the adult tissue of Ciona intestinalis was validated by Northern blot analyses. Additionally, a target prediction algorithm was implemented, which identified a high confidence list of 240 potential target genes. Over half of the predicted targets can be grouped into the gene ontology categories of metabolism, transport, regulation of transcription, and cell signaling. Conclusion The computational techniques implemented in this study can be applied to other organisms and serve to increase the understanding of the origins of non-coding RNAs, embryological and cellular developmental pathways, and the mechanisms for microRNA-controlled gene regulatory networks.

  10. Systematic Prediction of the Impacts of Mutations in MicroRNA Seed Sequences

    Bhattacharya Anindya

    2017-05-01

    Full Text Available MicroRNAs are a class of small non-coding RNAs that are involved in many important biological processes and the dysfunction of microRNA has been associated with many diseases. The seed region of a microRNA is of crucial importance to its target recognition. Mutations in microRNA seed regions may disrupt the binding of microRNAs to their original target genes and make them bind to new target genes. Here we use a knowledge-based computational method to systematically predict the functional effects of all the possible single nucleotide mutations in human microRNA seed regions. The result provides a comprehensive reference for the functional assessment of the impacts of possible natural and artificial single nucleotide mutations in microRNA seed regions.

  11. Supervised learning classification models for prediction of plant virus encoded RNA silencing suppressors.

    Zeenia Jagga

    Full Text Available Viral encoded RNA silencing suppressor proteins interfere with the host RNA silencing machinery, facilitating viral infection by evading host immunity. In plant hosts, the viral proteins have several basic science implications and biotechnology applications. However in silico identification of these proteins is limited by their high sequence diversity. In this study we developed supervised learning based classification models for plant viral RNA silencing suppressor proteins in plant viruses. We developed four classifiers based on supervised learning algorithms: J48, Random Forest, LibSVM and Naïve Bayes algorithms, with enriched model learning by correlation based feature selection. Structural and physicochemical features calculated for experimentally verified primary protein sequences were used to train the classifiers. The training features include amino acid composition; auto correlation coefficients; composition, transition, and distribution of various physicochemical properties; and pseudo amino acid composition. Performance analysis of predictive models based on 10 fold cross-validation and independent data testing revealed that the Random Forest based model was the best and achieved 86.11% overall accuracy and 86.22% balanced accuracy with a remarkably high area under the Receivers Operating Characteristic curve of 0.95 to predict viral RNA silencing suppressor proteins. The prediction models for plant viral RNA silencing suppressors can potentially aid identification of novel viral RNA silencing suppressors, which will provide valuable insights into the mechanism of RNA silencing and could be further explored as potential targets for designing novel antiviral therapeutics. Also, the key subset of identified optimal features may help in determining compositional patterns in the viral proteins which are important determinants for RNA silencing suppressor activities. The best prediction model developed in the study is available as a

  12. DNApi: A De Novo Adapter Prediction Algorithm for Small RNA Sequencing Data.

    Tsuji, Junko; Weng, Zhiping

    2016-01-01

    With the rapid accumulation of publicly available small RNA sequencing datasets, third-party meta-analysis across many datasets is becoming increasingly powerful. Although removing the 3´ adapter is an essential step for small RNA sequencing analysis, the adapter sequence information is not always available in the metadata. The information can be also erroneous even when it is available. In this study, we developed DNApi, a lightweight Python software package that predicts the 3´ adapter sequence de novo and provides the user with cleansed small RNA sequences ready for down stream analysis. Tested on 539 publicly available small RNA libraries accompanied with 3´ adapter sequences in their metadata, DNApi shows near-perfect accuracy (98.5%) with fast runtime (~2.85 seconds per library) and efficient memory usage (~43 MB on average). In addition to 3´ adapter prediction, it is also important to classify whether the input small RNA libraries were already processed, i.e. the 3´ adapters were removed. DNApi perfectly judged that given another batch of datasets, 192 publicly available processed libraries were "ready-to-map" small RNA sequence. DNApi is compatible with Python 2 and 3, and is available at https://github.com/jnktsj/DNApi. The 731 small RNA libraries used for DNApi evaluation were from human tissues and were carefully and manually collected. This study also provides readers with the curated datasets that can be integrated into their studies.

  13. 3dRPC: a web server for 3D RNA-protein structure prediction.

    Huang, Yangyu; Li, Haotian; Xiao, Yi

    2018-04-01

    RNA-protein interactions occur in many biological processes. To understand the mechanism of these interactions one needs to know three-dimensional (3D) structures of RNA-protein complexes. 3dRPC is an algorithm for prediction of 3D RNA-protein complex structures and consists of a docking algorithm RPDOCK and a scoring function 3dRPC-Score. RPDOCK is used to sample possible complex conformations of an RNA and a protein by calculating the geometric and electrostatic complementarities and stacking interactions at the RNA-protein interface according to the features of atom packing of the interface. 3dRPC-Score is a knowledge-based potential that uses the conformations of nucleotide-amino-acid pairs as statistical variables and that is used to choose the near-native complex-conformations obtained from the docking method above. Recently, we built a web server for 3dRPC. The users can easily use 3dRPC without installing it locally. RNA and protein structures in PDB (Protein Data Bank) format are the only needed input files. It can also incorporate the information of interface residues or residue-pairs obtained from experiments or theoretical predictions to improve the prediction. The address of 3dRPC web server is http://biophy.hust.edu.cn/3dRPC. yxiao@hust.edu.cn.

  14. Ranking of microRNA target prediction scores by Pareto front analysis.

    Sahoo, Sudhakar; Albrecht, Andreas A

    2010-12-01

    Over the past ten years, a variety of microRNA target prediction methods has been developed, and many of the methods are constantly improved and adapted to recent insights into miRNA-mRNA interactions. In a typical scenario, different methods return different rankings of putative targets, even if the ranking is reduced to selected mRNAs that are related to a specific disease or cell type. For the experimental validation it is then difficult to decide in which order to process the predicted miRNA-mRNA bindings, since each validation is a laborious task and therefore only a limited number of mRNAs can be analysed. We propose a new ranking scheme that combines ranked predictions from several methods and - unlike standard thresholding methods - utilises the concept of Pareto fronts as defined in multi-objective optimisation. In the present study, we attempt a proof of concept by applying the new ranking scheme to hsa-miR-21, hsa-miR-125b, and hsa-miR-373 and prediction scores supplied by PITA and RNAhybrid. The scores are interpreted as a two-objective optimisation problem, and the elements of the Pareto front are ranked by the STarMir score with a subsequent re-calculation of the Pareto front after removal of the top-ranked mRNA from the basic set of prediction scores. The method is evaluated on validated targets of the three miRNA, and the ranking is compared to scores from DIANA-microT and TargetScan. We observed that the new ranking method performs well and consistent, and the first validated targets are elements of Pareto fronts at a relatively early stage of the recurrent procedure, which encourages further research towards a higher-dimensional analysis of Pareto fronts. Copyright © 2010 Elsevier Ltd. All rights reserved.

  15. miRNAFold: a web server for fast miRNA precursor prediction in genomes.

    Tav, Christophe; Tempel, Sébastien; Poligny, Laurent; Tahi, Fariza

    2016-07-08

    Computational methods are required for prediction of non-coding RNAs (ncRNAs), which are involved in many biological processes, especially at post-transcriptional level. Among these ncRNAs, miRNAs have been largely studied and biologists need efficient and fast tools for their identification. In particular, ab initio methods are usually required when predicting novel miRNAs. Here we present a web server dedicated for miRNA precursors identification at a large scale in genomes. It is based on an algorithm called miRNAFold that allows predicting miRNA hairpin structures quickly with high sensitivity. miRNAFold is implemented as a web server with an intuitive and user-friendly interface, as well as a standalone version. The web server is freely available at: http://EvryRNA.ibisc.univ-evry.fr/miRNAFold. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

  16. Plant MicroRNA Prediction by Supervised Machine Learning Using C5.0 Decision Trees

    Philip H. Williams

    2012-01-01

    Full Text Available MicroRNAs (miRNAs are nonprotein coding RNAs between 20 and 22 nucleotides long that attenuate protein production. Different types of sequence data are being investigated for novel miRNAs, including genomic and transcriptomic sequences. A variety of machine learning methods have successfully predicted miRNA precursors, mature miRNAs, and other nonprotein coding sequences. MirTools, mirDeep2, and miRanalyzer require “read count” to be included with the input sequences, which restricts their use to deep-sequencing data. Our aim was to train a predictor using a cross-section of different species to accurately predict miRNAs outside the training set. We wanted a system that did not require read-count for prediction and could therefore be applied to short sequences extracted from genomic, EST, or RNA-seq sources. A miRNA-predictive decision-tree model has been developed by supervised machine learning. It only requires that the corresponding genome or transcriptome is available within a sequence window that includes the precursor candidate so that the required sequence features can be collected. Some of the most critical features for training the predictor are the miRNA:miRNA∗ duplex energy and the number of mismatches in the duplex. We present a cross-species plant miRNA predictor with 84.08% sensitivity and 98.53% specificity based on rigorous testing by leave-one-out validation.

  17. Predicting RNA hyper-editing with a novel tool when unambiguous alignment is impossible.

    McKerrow, Wilson H; Savva, Yiannis A; Rezaei, Ali; Reenan, Robert A; Lawrence, Charles E

    2017-07-10

    Repetitive elements are now known to have relevant cellular functions, including self-complementary sequences that form double stranded (ds) RNA. There are numerous pathways that determine the fate of endogenous dsRNA, and misregulation of endogenous dsRNA is a driver of autoimmune disease, particularly in the brain. Unfortunately, the alignment of high-throughput, short-read sequences to repeat elements poses a dilemma: Such sequences may align equally well to multiple genomic locations. In order to differentiate repeat elements, current alignment methods depend on sequence variation in the reference genome. Reads are discarded when no such variations are present. However, RNA hyper-editing, a possible fate for dsRNA, introduces enough variation to distinguish between repeats that are otherwise identical. To take advantage of this variation, we developed a new algorithm, RepProfile, that simultaneously aligns reads and predicts novel variations. RepProfile accurately aligns hyper-edited reads that other methods discard. In particular we predict hyper-editing of Drosophila melanogaster repeat elements in vivo at levels previously described only in vitro, and provide validation by Sanger sequencing sixty-two individual cloned sequences. We find that hyper-editing is concentrated in genes involved in cell-cell communication at the synapse, including some that are associated with neurodegeneration. We also find that hyper-editing tends to occur in short runs. Previous studies of RNA hyper-editing discarded ambiguously aligned reads, ignoring hyper-editing in long, perfect dsRNA - the perfect substrate for hyper-editing. We provide a method that simulation and Sanger validation show accurately predicts such RNA editing, yielding a superior picture of hyper-editing.

  18. A predictable suite of helminth parasites in the long-billed dowitcher, Limnodromus scolopaceus, from the Chihuahua desert in Texas and Mexico.

    Canaris, Albert G; Ortiz, Rafael; Canaris, Gay J

    2010-12-01

    Eighty-eight long-billed dowitchers, Limnodromus scolopaceus, were examined for helminth parasites, 62 from Texas and 26 from Mexico. In total, 3,558 helminth parasites were obtained from this host, 2,273 from Texas birds and 1,285 from birds from Mexico. The component communities consisted of 22 species of helminths in Texas, and 19 in Mexico. Of a total of 26 helminth species recorded from the 2 localities, 15 were common to both, 7 found only in Texas, and 4 only in Mexico. Fifty-nine of 62 Texas birds and 25 of 26 birds from Mexico were infected. The most prevalent helminth for Texas was the cestode Shipleya inermis. The cestode Aploparaksis retroversa was the most abundant, accounting for 37% of the total abundance, and was second highest in prevalence. Five species of cestodes, A. retroversa, Aploparaksis diagonalis, Aploparaksis occidentalis, Aploparaksis rissae, and Shipleya inermis accounted for 79% of total abundance. In the sample from Mexico, S. inermis was also highest in prevalence, followed by the nematode Hystrichis tricolor. The cestode A. retroversa was highest in abundance at 50% of the total, and was third highest in prevalence. Mean species richness, diversity, and evenness were similar among the component communities of Texas and Mexico. A predictable suite of aploparaksid cestodes, together with the cestode S. inermis, constituted 79%, and 61%, of total abundance for the component communities of Texas and Mexico, respectively, and were present in all component communities for locality, season, and year. The cestodes, A. retroversa and S. inermis, were the dominant species in all component communities. Differences among component communities and low similarities for all other comparisons were largely caused by less predictable suites of helminth species. A checklist of helminth parasites reported for long-billed dowitchers is included.

  19. Bi-objective integer programming for RNA secondary structure prediction with pseudoknots.

    Legendre, Audrey; Angel, Eric; Tahi, Fariza

    2018-01-15

    RNA structure prediction is an important field in bioinformatics, and numerous methods and tools have been proposed. Pseudoknots are specific motifs of RNA secondary structures that are difficult to predict. Almost all existing methods are based on a single model and return one solution, often missing the real structure. An alternative approach would be to combine different models and return a (small) set of solutions, maximizing its quality and diversity in order to increase the probability that it contains the real structure. We propose here an original method for predicting RNA secondary structures with pseudoknots, based on integer programming. We developed a generic bi-objective integer programming algorithm allowing to return optimal and sub-optimal solutions optimizing simultaneously two models. This algorithm was then applied to the combination of two known models of RNA secondary structure prediction, namely MEA and MFE. The resulting tool, called BiokoP, is compared with the other methods in the literature. The results show that the best solution (structure with the highest F 1 -score) is, in most cases, given by BiokoP. Moreover, the results of BiokoP are homogeneous, regardless of the pseudoknot type or the presence or not of pseudoknots. Indeed, the F 1 -scores are always higher than 70% for any number of solutions returned. The results obtained by BiokoP show that combining the MEA and the MFE models, as well as returning several optimal and several sub-optimal solutions, allow to improve the prediction of secondary structures. One perspective of our work is to combine better mono-criterion models, in particular to combine a model based on the comparative approach with the MEA and the MFE models. This leads to develop in the future a new multi-objective algorithm to combine more than two models. BiokoP is available on the EvryRNA platform: https://EvryRNA.ibisc.univ-evry.fr .

  20. Analysis of electric moments of RNA-binding proteins: implications for mechanism and prediction

    Sarai Akinori

    2011-02-01

    Full Text Available Abstract Background Protein-RNA interactions play important role in many biological processes such as gene regulation, replication, protein synthesis and virus assembly. Although many structures of various types of protein-RNA complexes have been determined, the mechanism of protein-RNA recognition remains elusive. We have earlier shown that the simplest electrostatic properties viz. charge, dipole and quadrupole moments, calculated from backbone atomic coordinates of proteins are biased relative to other proteins, and these quantities can be used to identify DNA-binding proteins. Closely related, RNA-binding proteins are investigated in this study. In particular, discrimination between various types of RNA-binding proteins, evolutionary conservation of these bulk electrostatic features and effect of conformational changes by complex formation are investigated. Basic binding mechanism of a putative RNA-binding protein (HI1333 from Haemophilus influenza is suggested as a potential application of this study. Results We found that similar to DNA-binding proteins (DBPs, RNA-binding proteins (RBPs also show significantly higher values of electric moments. However, higher moments in RBPs are found to strongly depend on their functional class: proteins binding to ribosomal RNA (rRNA constitute the only class with all three of the properties (charge, dipole and quadrupole moments being higher than control proteins. Neural networks were trained using leave-one-out cross-validation to predict RBPs from control data as well as pair-wise classification capacity between proteins binding to various RNA types. RBPs and control proteins reached up to 78% accuracy measured by the area under the ROC curve. Proteins binding to rRNA are found to be best distinguished (AUC = 79%. Changes in dipole and quadrupole moments between unbound and bound structures were small and these properties are found to be robust under complex formation. Conclusions Bulk electric

  1. Know Your Enemy: Successful Bioinformatic Approaches to Predict Functional RNA Structures in Viral RNAs

    Lim, Chun Shen; Brown, Chris M.

    2018-01-01

    Structured RNA elements may control virus replication, transcription and translation, and their distinct features are being exploited by novel antiviral strategies. Viral RNA elements continue to be discovered using combinations of experimental and computational analyses. However, the wealth of sequence data, notably from deep viral RNA sequencing, viromes, and metagenomes, necessitates computational approaches being used as an essential discovery tool. In this review, we describe practical approaches being used to discover functional RNA elements in viral genomes. In addition to success stories in new and emerging viruses, these approaches have revealed some surprising new features of well-studied viruses e.g., human immunodeficiency virus, hepatitis C virus, influenza, and dengue viruses. Some notable discoveries were facilitated by new comparative analyses of diverse viral genome alignments. Importantly, comparative approaches for finding RNA elements embedded in coding and non-coding regions differ. With the exponential growth of computer power we have progressed from stem-loop prediction on single sequences to cutting edge 3D prediction, and from command line to user friendly web interfaces. Despite these advances, many powerful, user friendly prediction tools and resources are underutilized by the virology community. PMID:29354101

  2. Predicting gene regulatory networks of soybean nodulation from RNA-Seq transcriptome data.

    Zhu, Mingzhu; Dahmen, Jeremy L; Stacey, Gary; Cheng, Jianlin

    2013-09-22

    High-throughput RNA sequencing (RNA-Seq) is a revolutionary technique to study the transcriptome of a cell under various conditions at a systems level. Despite the wide application of RNA-Seq techniques to generate experimental data in the last few years, few computational methods are available to analyze this huge amount of transcription data. The computational methods for constructing gene regulatory networks from RNA-Seq expression data of hundreds or even thousands of genes are particularly lacking and urgently needed. We developed an automated bioinformatics method to predict gene regulatory networks from the quantitative expression values of differentially expressed genes based on RNA-Seq transcriptome data of a cell in different stages and conditions, integrating transcriptional, genomic and gene function data. We applied the method to the RNA-Seq transcriptome data generated for soybean root hair cells in three different development stages of nodulation after rhizobium infection. The method predicted a soybean nodulation-related gene regulatory network consisting of 10 regulatory modules common for all three stages, and 24, 49 and 70 modules separately for the first, second and third stage, each containing both a group of co-expressed genes and several transcription factors collaboratively controlling their expression under different conditions. 8 of 10 common regulatory modules were validated by at least two kinds of validations, such as independent DNA binding motif analysis, gene function enrichment test, and previous experimental data in the literature. We developed a computational method to reliably reconstruct gene regulatory networks from RNA-Seq transcriptome data. The method can generate valuable hypotheses for interpreting biological data and designing biological experiments such as ChIP-Seq, RNA interference, and yeast two hybrid experiments.

  3. CircRNA-0004904, CircRNA-0001855, and PAPP-A: Potential Novel Biomarkers for the Prediction of Preeclampsia

    Min Jiang

    2018-05-01

    Full Text Available Background/Aims: Circular RNAs (circRNAs are transcribed prevalently in the genome; however, their potential roles in multiple cardiovascular diseases, particularly preeclampsia (PE, are not yet well understood. This study investigated the expression profiles of circRNAs and explored circRNA-mediated pregnancy-associated plasma protein A (PAPP-A expression as a potential biomarker for PE before 20 weeks of pregnancy. Methods: A nested case-control two-phase screening/validation study was performed in pregnant women before 20 weeks of gestation (before clinical diagnosis at Guangzhou Women and Children’s Medical Center from 2012 to 2015. In the screening phase, circRNA expression profiles of blood cells were assessed using a human circRNA microarray, which was designed to detect simultaneously 5396 circRNAs, in 5 patients with PE and 5 age- and gestational week-matched controls. In the validation phase, 18 circRNAs in blood cells predicted by bioinformatics tools were validated by quantitative reverse transcription PCR in a cohort of 60 patients (PE and age-, gestational week-, and sample storage time-matched controls. Then, we examined the involvement of circRNAs in PE-related pathways via interactions with miRNAs by multiple bioinformatics approaches. Bioinformatics analysis predicted that hsa_circ_0004904 and hsa_circ_0001855 miRNA sponges directly target PAPP-A. PAPP-A was verified in the serum of the same cohort of patients using an enzyme-linked immunosorbent assay. Finally, we combined PAPP-A with circRNAs to create a novel preclinical diagnostic model for PE with logistic regression and evaluated the efficiency of this model with receiver operating curve analysis. Results: Volcano plot analysis using various parameters showed that circRNAs were differentially expressed among both groups (P < 0.01, fold change > 2. In the screening phase, we found that 2178 circRNAs were differentially expressed between the control and PE groups, in

  4. Bioinformatical approaches to RNA structure prediction & Sequencing of an ancient human genome

    Lindgreen, Stinus

    Stinus Lindgreen has been working in two different fields during his Ph.D. The first part has been focused on computational approaches to predict the structure of non-coding RNA molecules at the base pairing level. This has resulted in the analysis of various measures of the base pairing potentia...

  5. GTfold: Enabling parallel RNA secondary structure prediction on multi-core desktops

    Swenson, M Shel; Anderson, Joshua; Ash, Andrew

    2012-01-01

    achieved significant improvements in runtime, but their implementations were not portable from niche high-performance computers or easily accessible to most RNA researchers. With the increasing prevalence of multi-core desktop machines, a new parallel prediction program is needed to take full advantage...

  6. Correlation of microRNA levels during hypoxia with predicted target mRNAs through genome-wide microarray analysis

    Page Grier P

    2009-03-01

    Full Text Available Abstract Background Low levels of oxygen in tissues, seen in situations such as chronic lung disease, necrotic tumors, and high altitude exposures, initiate a signaling pathway that results in active transcription of genes possessing a hypoxia response element (HRE. The aim of this study was to investigate whether a change in miRNA expression following hypoxia could account for changes in the cellular transcriptome based on currently available miRNA target prediction tools. Methods To identify changes induced by hypoxia, we conducted mRNA- and miRNA-array-based experiments in HT29 cells, and performed comparative analysis of the resulting data sets based on multiple target prediction algorithms. To date, few studies have investigated an environmental perturbation for effects on genome-wide miRNA levels, or their consequent influence on mRNA output. Results Comparison of miRNAs with predicted mRNA targets indicated a lower level of concordance than expected. We did, however, find preliminary evidence of combinatorial regulation of mRNA expression by miRNA. Conclusion Target prediction programs and expression profiling techniques do not yet adequately represent the complexity of miRNA-mediated gene repression, and new methods may be required to better elucidate these pathways. Our data suggest the physiologic impact of miRNAs on cellular transcription results from a multifaceted network of miRNA and mRNA relationships, working together in an interconnected system and in context of hundreds of RNA species. The methods described here for comparative analysis of cellular miRNA and mRNA will be useful for understanding genome wide regulatory responsiveness and refining miRNA predictive algorithms.

  7. GIMDA: Graphlet interaction-based MiRNA-disease association prediction.

    Chen, Xing; Guan, Na-Na; Li, Jian-Qiang; Yan, Gui-Ying

    2018-03-01

    MicroRNAs (miRNAs) have been confirmed to be closely related to various human complex diseases by many experimental studies. It is necessary and valuable to develop powerful and effective computational models to predict potential associations between miRNAs and diseases. In this work, we presented a prediction model of Graphlet Interaction for MiRNA-Disease Association prediction (GIMDA) by integrating the disease semantic similarity, miRNA functional similarity, Gaussian interaction profile kernel similarity and the experimentally confirmed miRNA-disease associations. The related score of a miRNA to a disease was calculated by measuring the graphlet interactions between two miRNAs or two diseases. The novelty of GIMDA lies in that we used graphlet interaction to analyse the complex relationships between two nodes in a graph. The AUCs of GIMDA in global and local leave-one-out cross-validation (LOOCV) turned out to be 0.9006 and 0.8455, respectively. The average result of five-fold cross-validation reached to 0.8927 ± 0.0012. In case study for colon neoplasms, kidney neoplasms and prostate neoplasms based on the database of HMDD V2.0, 45, 45, 41 of the top 50 potential miRNAs predicted by GIMDA were validated by dbDEMC and miR2Disease. Additionally, in the case study of new diseases without any known associated miRNAs and the case study of predicting potential miRNA-disease associations using HMDD V1.0, there were also high percentages of top 50 miRNAs verified by the experimental literatures. © 2017 The Authors. Journal of Cellular and Molecular Medicine published by John Wiley & Sons Ltd and Foundation for Cellular and Molecular Medicine.

  8. Combining Results from Distinct MicroRNA Target Prediction Tools Enhances the Performance of Analyses

    Arthur C. Oliveira

    2017-05-01

    Full Text Available Target prediction is generally the first step toward recognition of bona fide microRNA (miRNA-target interactions in living cells. Several target prediction tools are now available, which use distinct criteria and stringency to provide the best set of candidate targets for a single miRNA or a subset of miRNAs. However, there are many false-negative predictions, and consensus about the optimum strategy to select and use the output information provided by the target prediction tools is lacking. We compared the performance of four tools cited in literature—TargetScan (TS, miRanda-mirSVR (MR, Pita, and RNA22 (R22, and we determined the most effective approach for analyzing target prediction data (individual, union, or intersection. For this purpose, we calculated the sensitivity, specificity, precision, and correlation of these approaches using 10 miRNAs (miR-1-3p, miR-17-5p, miR-21-5p, miR-24-3p, miR-29a-3p, miR-34a-5p, miR-124-3p, miR-125b-5p, miR-145-5p, and miR-155-5p and 1,400 genes (700 validated and 700 non-validated as targets of these miRNAs. The four tools provided a subset of high-quality predictions and returned few false-positive predictions; however, they could not identify several known true targets. We demonstrate that union of TS/MR and TS/MR/R22 enhanced the quality of in silico prediction analysis of miRNA targets. We conclude that the union rather than the intersection of the aforementioned tools is the best strategy for maximizing performance while minimizing the loss of time and resources in subsequent in vivo and in vitro experiments for functional validation of miRNA-target interactions.

  9. StructRNAfinder: an automated pipeline and web server for RNA families prediction.

    Arias-Carrasco, Raúl; Vásquez-Morán, Yessenia; Nakaya, Helder I; Maracaja-Coutinho, Vinicius

    2018-02-17

    The function of many noncoding RNAs (ncRNAs) depend upon their secondary structures. Over the last decades, several methodologies have been developed to predict such structures or to use them to functionally annotate RNAs into RNA families. However, to fully perform this analysis, researchers should utilize multiple tools, which require the constant parsing and processing of several intermediate files. This makes the large-scale prediction and annotation of RNAs a daunting task even to researchers with good computational or bioinformatics skills. We present an automated pipeline named StructRNAfinder that predicts and annotates RNA families in transcript or genome sequences. This single tool not only displays the sequence/structural consensus alignments for each RNA family, according to Rfam database but also provides a taxonomic overview for each assigned functional RNA. Moreover, we implemented a user-friendly web service that allows researchers to upload their own nucleotide sequences in order to perform the whole analysis. Finally, we provided a stand-alone version of StructRNAfinder to be used in large-scale projects. The tool was developed under GNU General Public License (GPLv3) and is freely available at http://structrnafinder.integrativebioinformatics.me . The main advantage of StructRNAfinder relies on the large-scale processing and integrating the data obtained by each tool and database employed along the workflow, of which several files are generated and displayed in user-friendly reports, useful for downstream analyses and data exploration.

  10. An integrated computational validation approach for potential novel miRNA prediction

    Pooja Viswam

    2017-12-01

    Full Text Available MicroRNAs (miRNAs are short, non-coding RNAs between 17bp-24bp length that regulate gene expression by targeting mRNA molecules. The regulatory functions of miRNAs are known to be majorly associated with disease phenotypes such as cancer, cell signaling, cell division, growth and other metabolisms. Novel miRNAs are defined as sequences which does not have any similarity with the existing known sequences and void of any experimental evidences. In recent decades, the advent of next-generation sequencing allows us to capture the small RNA molecules form the cells and developing methods to estimate their expression levels. Several computational algorithms are available to predict the novel miRNAs from the deep sequencing data. In this work, we integrated three novel miRNA prediction programs miRDeep, miRanalyzer and miRPRo to compare and validate their prediction efficiency. The dicer cleavage sites, alignment density, seed conservation, minimum free energy, AU-GC percentage, secondary loop scores, false discovery rates and confidence scores will be considered for comparison and evaluation. Efficiency to identify isomiRs and base pair mismatches in a strand specific manner will also be considered for the computational validation. Further, the criteria and parameters for the identification of the best possible novel miRNA with minimal false positive rates were deduced.

  11. A Circulating microRNA Signature Predicts Age-Based Development of Lymphoma.

    Afshin Beheshti

    Full Text Available Extensive epidemiological data have demonstrated an exponential rise in the incidence of non-Hodgkin lymphoma (NHL that is associated with increasing age. The molecular etiology of this remains largely unknown, which impacts the effectiveness of treatment for patients. We proposed that age-dependent circulating microRNA (miRNA signatures in the host influence diffuse large B cell lymphoma (DLBCL development. Our objective was to examine tumor development in an age-based DLBCL system using an inventive systems biology approach. We harnessed a novel murine model of spontaneous DLBCL initiation (Smurf2-deficient at two age groups: 3 and 15 months old. All Smurf2-deficient mice develop visible DLBCL tumor starting at 15 months of age. Total miRNA was isolated from serum, bone marrow and spleen and were collected for all age groups for Smurf2-deficient mice and age-matched wild-type C57BL/6 mice. Using systems biology techniques, we identified a list of 10 circulating miRNAs being regulated in both the spleen and bone marrow that were present in DLBCL forming mice starting at 3 months of age that were not present in the control mice. Furthermore, this miRNA signature was found to occur circulating in the blood and it strongly impacted JUN and MYC oncogenic signaling. In addition, quantification of the miRNA signature was performed via Droplet Digital PCR technology. It was discovered that a key miRNA signature circulates throughout a host prior to the formation of a tumor starting at 3 months old, which becomes further modulated by age and yielded calculation of a 'carcinogenic risk score'. This novel age-based circulating miRNA signature may potentially be leveraged as a DLBCL risk profile at a young age to predict future lymphoma development or disease progression as well as for potential innovative miRNA-based targeted therapeutic strategies in lymphoma.

  12. Evaluation of the suitability of free-energy minimization using nearest-neighbor energy parameters for RNA secondary structure prediction

    Cobaugh Christian W

    2004-08-01

    Full Text Available Abstract Background A detailed understanding of an RNA's correct secondary and tertiary structure is crucial to understanding its function and mechanism in the cell. Free energy minimization with energy parameters based on the nearest-neighbor model and comparative analysis are the primary methods for predicting an RNA's secondary structure from its sequence. Version 3.1 of Mfold has been available since 1999. This version contains an expanded sequence dependence of energy parameters and the ability to incorporate coaxial stacking into free energy calculations. We test Mfold 3.1 by performing the largest and most phylogenetically diverse comparison of rRNA and tRNA structures predicted by comparative analysis and Mfold, and we use the results of our tests on 16S and 23S rRNA sequences to assess the improvement between Mfold 2.3 and Mfold 3.1. Results The average prediction accuracy for a 16S or 23S rRNA sequence with Mfold 3.1 is 41%, while the prediction accuracies for the majority of 16S and 23S rRNA structures tested are between 20% and 60%, with some having less than 20% prediction accuracy. The average prediction accuracy was 71% for 5S rRNA and 69% for tRNA. The majority of the 5S rRNA and tRNA sequences have prediction accuracies greater than 60%. The prediction accuracy of 16S rRNA base-pairs decreases exponentially as the number of nucleotides intervening between the 5' and 3' halves of the base-pair increases. Conclusion Our analysis indicates that the current set of nearest-neighbor energy parameters in conjunction with the Mfold folding algorithm are unable to consistently and reliably predict an RNA's correct secondary structure. For 16S or 23S rRNA structure prediction, Mfold 3.1 offers little improvement over Mfold 2.3. However, the nearest-neighbor energy parameters do work well for shorter RNA sequences such as tRNA or 5S rRNA, or for larger rRNAs when the contact distance between the base-pairs is less than 100 nucleotides.

  13. Base pair probability estimates improve the prediction accuracy of RNA non-canonical base pairs.

    Michael F Sloma

    2017-11-01

    Full Text Available Prediction of RNA tertiary structure from sequence is an important problem, but generating accurate structure models for even short sequences remains difficult. Predictions of RNA tertiary structure tend to be least accurate in loop regions, where non-canonical pairs are important for determining the details of structure. Non-canonical pairs can be predicted using a knowledge-based model of structure that scores nucleotide cyclic motifs, or NCMs. In this work, a partition function algorithm is introduced that allows the estimation of base pairing probabilities for both canonical and non-canonical interactions. Pairs that are predicted to be probable are more likely to be found in the true structure than pairs of lower probability. Pair probability estimates can be further improved by predicting the structure conserved across multiple homologous sequences using the TurboFold algorithm. These pairing probabilities, used in concert with prior knowledge of the canonical secondary structure, allow accurate inference of non-canonical pairs, an important step towards accurate prediction of the full tertiary structure. Software to predict non-canonical base pairs and pairing probabilities is now provided as part of the RNAstructure software package.

  14. Base pair probability estimates improve the prediction accuracy of RNA non-canonical base pairs.

    Sloma, Michael F; Mathews, David H

    2017-11-01

    Prediction of RNA tertiary structure from sequence is an important problem, but generating accurate structure models for even short sequences remains difficult. Predictions of RNA tertiary structure tend to be least accurate in loop regions, where non-canonical pairs are important for determining the details of structure. Non-canonical pairs can be predicted using a knowledge-based model of structure that scores nucleotide cyclic motifs, or NCMs. In this work, a partition function algorithm is introduced that allows the estimation of base pairing probabilities for both canonical and non-canonical interactions. Pairs that are predicted to be probable are more likely to be found in the true structure than pairs of lower probability. Pair probability estimates can be further improved by predicting the structure conserved across multiple homologous sequences using the TurboFold algorithm. These pairing probabilities, used in concert with prior knowledge of the canonical secondary structure, allow accurate inference of non-canonical pairs, an important step towards accurate prediction of the full tertiary structure. Software to predict non-canonical base pairs and pairing probabilities is now provided as part of the RNAstructure software package.

  15. Accuracy of taxonomy prediction for 16S rRNA and fungal ITS sequences

    Robert C. Edgar

    2018-04-01

    Full Text Available Prediction of taxonomy for marker gene sequences such as 16S ribosomal RNA (rRNA is a fundamental task in microbiology. Most experimentally observed sequences are diverged from reference sequences of authoritatively named organisms, creating a challenge for prediction methods. I assessed the accuracy of several algorithms using cross-validation by identity, a new benchmark strategy which explicitly models the variation in distances between query sequences and the closest entry in a reference database. When the accuracy of genus predictions was averaged over a representative range of identities with the reference database (100%, 99%, 97%, 95% and 90%, all tested methods had ≤50% accuracy on the currently-popular V4 region of 16S rRNA. Accuracy was found to fall rapidly with identity; for example, better methods were found to have V4 genus prediction accuracy of ∼100% at 100% identity but ∼50% at 97% identity. The relationship between identity and taxonomy was quantified as the probability that a rank is the lowest shared by a pair of sequences with a given pair-wise identity. With the V4 region, 95% identity was found to be a twilight zone where taxonomy is highly ambiguous because the probabilities that the lowest shared rank between pairs of sequences is genus, family, order or class are approximately equal.

  16. Peripheral blood cell microRNA quantification during the first trimester predicts preeclampsia: Proof of concept.

    Edward E Winger

    Full Text Available We investigated the capacity of microRNAs isolated from peripheral blood buffy coat collected late during the first trimester to predict preeclampsia.The cohort study comprised 48 pregnant women with the following pregnancy outcomes: 8 preeclampsia and 40 with normal delivery outcomes. Quantitative rtPCR was performed on a panel of 30 microRNAs from buffy coat samples drawn at a mean of 12.7±0.5 weeks gestation. MicroRNA Risk Scores were calculated and AUC-ROC calculations derived.The AUC-ROC for preeclampsia risk was 0.91 (p<0.0001. When women with normal delivery and high-risk background (those with SLE/APS, chronic hypertension and/or Type 2 Diabetes were compared to women who developed preeclampsia but with a normal risk background (without these mentioned risk factors, preeclampsia was still predicted with an AUC-ROC of 0.92 (p<0.0001.MicroRNA quantification of peripheral immune cell microRNA provides sensitive and specific prediction of preeclampsia in the first trimester of pregnant women. With this study, we extend the range during which disorders of the placental bed may be predicted from early to the end of the first trimester. This study confirms that buffy coat may be used as a sample preparation.

  17. Matrix factorization-based data fusion for the prediction of lncRNA-disease associations.

    Fu, Guangyuan; Wang, Jun; Domeniconi, Carlotta; Yu, Guoxian

    2018-05-01

    Long non-coding RNAs (lncRNAs) play crucial roles in complex disease diagnosis, prognosis, prevention and treatment, but only a small portion of lncRNA-disease associations have been experimentally verified. Various computational models have been proposed to identify lncRNA-disease associations by integrating heterogeneous data sources. However, existing models generally ignore the intrinsic structure of data sources or treat them as equally relevant, while they may not be. To accurately identify lncRNA-disease associations, we propose a Matrix Factorization based LncRNA-Disease Association prediction model (MFLDA in short). MFLDA decomposes data matrices of heterogeneous data sources into low-rank matrices via matrix tri-factorization to explore and exploit their intrinsic and shared structure. MFLDA can select and integrate the data sources by assigning different weights to them. An iterative solution is further introduced to simultaneously optimize the weights and low-rank matrices. Next, MFLDA uses the optimized low-rank matrices to reconstruct the lncRNA-disease association matrix and thus to identify potential associations. In 5-fold cross validation experiments to identify verified lncRNA-disease associations, MFLDA achieves an area under the receiver operating characteristic curve (AUC) of 0.7408, at least 3% higher than those given by state-of-the-art data fusion based computational models. An empirical study on identifying masked lncRNA-disease associations again shows that MFLDA can identify potential associations more accurately than competing models. A case study on identifying lncRNAs associated with breast, lung and stomach cancers show that 38 out of 45 (84%) associations predicted by MFLDA are supported by recent biomedical literature and further proves the capability of MFLDA in identifying novel lncRNA-disease associations. MFLDA is a general data fusion framework, and as such it can be adopted to predict associations between other biological

  18. Prediction of RNA secondary structures: from theory to models and real molecules

    Schuster, Peter

    2006-01-01

    RNA secondary structures are derived from RNA sequences, which are strings built form the natural four letter nucleotide alphabet, {AUGC}. These coarse-grained structures, in turn, are tantamount to constrained strings over a three letter alphabet. Hence, the secondary structures are discrete objects and the number of sequences always exceeds the number of structures. The sequences built from two letter alphabets form perfect structures when the nucleotides can form a base pair, as is the case with {GC} or {AU}, but the relation between the sequences and structures differs strongly from the four letter alphabet. A comprehensive theory of RNA structure is presented, which is based on the concepts of sequence space and shape space, being a space of structures. It sets the stage for modelling processes in ensembles of RNA molecules like evolutionary optimization or kinetic folding as dynamical phenomena guided by mappings between the two spaces. The number of minimum free energy (mfe) structures is always smaller than the number of sequences, even for two letter alphabets. Folding of RNA molecules into mfe energy structures constitutes a non-invertible mapping from sequence space onto shape space. The preimage of a structure in sequence space is defined as its neutral network. Similarly the set of suboptimal structures is the preimage of a sequence in shape space. This set represents the conformation space of a given sequence. The evolutionary optimization of structures in populations is a process taking place in sequence space, whereas kinetic folding occurs in molecular ensembles that optimize free energy in conformation space. Efficient folding algorithms based on dynamic programming are available for the prediction of secondary structures for given sequences. The inverse problem, the computation of sequences for predefined structures, is an important tool for the design of RNA molecules with tailored properties. Simultaneous folding or cofolding of two or more RNA

  19. TargetSpy: a supervised machine learning approach for microRNA target prediction.

    Sturm, Martin; Hackenberg, Michael; Langenberger, David; Frishman, Dmitrij

    2010-05-28

    Virtually all currently available microRNA target site prediction algorithms require the presence of a (conserved) seed match to the 5' end of the microRNA. Recently however, it has been shown that this requirement might be too stringent, leading to a substantial number of missed target sites. We developed TargetSpy, a novel computational approach for predicting target sites regardless of the presence of a seed match. It is based on machine learning and automatic feature selection using a wide spectrum of compositional, structural, and base pairing features covering current biological knowledge. Our model does not rely on evolutionary conservation, which allows the detection of species-specific interactions and makes TargetSpy suitable for analyzing unconserved genomic sequences.In order to allow for an unbiased comparison of TargetSpy to other methods, we classified all algorithms into three groups: I) no seed match requirement, II) seed match requirement, and III) conserved seed match requirement. TargetSpy predictions for classes II and III are generated by appropriate postfiltering. On a human dataset revealing fold-change in protein production for five selected microRNAs our method shows superior performance in all classes. In Drosophila melanogaster not only our class II and III predictions are on par with other algorithms, but notably the class I (no-seed) predictions are just marginally less accurate. We estimate that TargetSpy predicts between 26 and 112 functional target sites without a seed match per microRNA that are missed by all other currently available algorithms. Only a few algorithms can predict target sites without demanding a seed match and TargetSpy demonstrates a substantial improvement in prediction accuracy in that class. Furthermore, when conservation and the presence of a seed match are required, the performance is comparable with state-of-the-art algorithms. TargetSpy was trained on mouse and performs well in human and drosophila

  20. TargetSpy: a supervised machine learning approach for microRNA target prediction

    Langenberger David

    2010-05-01

    Full Text Available Abstract Background Virtually all currently available microRNA target site prediction algorithms require the presence of a (conserved seed match to the 5' end of the microRNA. Recently however, it has been shown that this requirement might be too stringent, leading to a substantial number of missed target sites. Results We developed TargetSpy, a novel computational approach for predicting target sites regardless of the presence of a seed match. It is based on machine learning and automatic feature selection using a wide spectrum of compositional, structural, and base pairing features covering current biological knowledge. Our model does not rely on evolutionary conservation, which allows the detection of species-specific interactions and makes TargetSpy suitable for analyzing unconserved genomic sequences. In order to allow for an unbiased comparison of TargetSpy to other methods, we classified all algorithms into three groups: I no seed match requirement, II seed match requirement, and III conserved seed match requirement. TargetSpy predictions for classes II and III are generated by appropriate postfiltering. On a human dataset revealing fold-change in protein production for five selected microRNAs our method shows superior performance in all classes. In Drosophila melanogaster not only our class II and III predictions are on par with other algorithms, but notably the class I (no-seed predictions are just marginally less accurate. We estimate that TargetSpy predicts between 26 and 112 functional target sites without a seed match per microRNA that are missed by all other currently available algorithms. Conclusion Only a few algorithms can predict target sites without demanding a seed match and TargetSpy demonstrates a substantial improvement in prediction accuracy in that class. Furthermore, when conservation and the presence of a seed match are required, the performance is comparable with state-of-the-art algorithms. TargetSpy was trained on

  1. HomoTarget: a new algorithm for prediction of microRNA targets in Homo sapiens.

    Ahmadi, Hamed; Ahmadi, Ali; Azimzadeh-Jamalkandi, Sadegh; Shoorehdeli, Mahdi Aliyari; Salehzadeh-Yazdi, Ali; Bidkhori, Gholamreza; Masoudi-Nejad, Ali

    2013-02-01

    MiRNAs play an essential role in the networks of gene regulation by inhibiting the translation of target mRNAs. Several computational approaches have been proposed for the prediction of miRNA target-genes. Reports reveal a large fraction of under-predicted or falsely predicted target genes. Thus, there is an imperative need to develop a computational method by which the target mRNAs of existing miRNAs can be correctly identified. In this study, combined pattern recognition neural network (PRNN) and principle component analysis (PCA) architecture has been proposed in order to model the complicated relationship between miRNAs and their target mRNAs in humans. The results of several types of intelligent classifiers and our proposed model were compared, showing that our algorithm outperformed them with higher sensitivity and specificity. Using the recent release of the mirBase database to find potential targets of miRNAs, this model incorporated twelve structural, thermodynamic and positional features of miRNA:mRNA binding sites to select target candidates. Copyright © 2012 Elsevier Inc. All rights reserved.

  2. Predicting Consensus Structures for RNA Alignments Via Pseudo-Energy Minimization

    Junilda Spirollari

    2009-01-01

    Full Text Available Thermodynamic processes with free energy parameters are often used in algorithms that solve the free energy minimization problem to predict secondary structures of single RNA sequences. While results from these algorithms are promising, an observation is that single sequence-based methods have moderate accuracy and more information is needed to improve on RNA secondary structure prediction, such as covariance scores obtained from multiple sequence alignments. We present in this paper a new approach to predicting the consensus secondary structure of a set of aligned RNA sequences via pseudo-energy minimization. Our tool, called RSpredict, takes into account sequence covariation and employs effective heuristics for accuracy improvement. RSpredict accepts, as input data, a multiple sequence alignment in FASTA or ClustalW format and outputs the consensus secondary structure of the input sequences in both the Vienna style Dot Bracket format and the Connectivity Table format. Our method was compared with some widely used tools including KNetFold, Pfold and RNAalifold. A comprehensive test on different datasets including Rfam sequence alignments and a multiple sequence alignment obtained from our study on the Drosophila X chromosome reveals that RSpredict is competitive with the existing tools on the tested datasets. RSpredict is freely available online as a web server and also as a jar file for download at http:// datalab.njit.edu/biology/RSpredict.

  3. Homology Modeling and Analysis of Structure Predictions of the Bovine Rhinitis B Virus RNA Dependent RNA Polymerase (RdRp

    Devendra K. Rai

    2012-07-01

    Full Text Available Bovine Rhinitis B Virus (BRBV is a picornavirus responsible for mild respiratory infection of cattle. It is probably the least characterized among the aphthoviruses. BRBV is the closest relative known to Foot and Mouth Disease virus (FMDV with a ~43% identical polyprotein sequence and as much as 67% identical sequence for the RNA dependent RNA polymerase (RdRp, which is also known as 3D polymerase (3Dpol. In the present study we carried out phylogenetic analysis, structure based sequence alignment and prediction of three-dimensional structure of BRBV 3Dpol using a combination of different computational tools. Model structures of BRBV 3Dpol were verified for their stereochemical quality and accuracy. The BRBV 3Dpol structure predicted by SWISS-MODEL exhibited highest scores in terms of stereochemical quality and accuracy, which were in the range of 2Å resolution crystal structures. The active site, nucleic acid binding site and overall structure were observed to be in agreement with the crystal structure of unliganded as well as template/primer (T/P, nucleotide tri-phosphate (NTP and pyrophosphate (PPi bound FMDV 3Dpol (PDB, 1U09 and 2E9Z. The closest proximity of BRBV and FMDV 3Dpol as compared to human rhinovirus type 16 (HRV-16 and rabbit hemorrhagic disease virus (RHDV 3Dpols is also substantiated by phylogeny analysis and root-mean square deviation (RMSD between C-α traces of the polymerase structures. The absence of positively charged α-helix at C terminal, significant differences in non-covalent interactions especially salt bridges and CH-pi interactions around T/P channel of BRBV 3Dpol compared to FMDV 3Dpol, indicate that despite a very high homology to FMDV 3Dpol, BRBV 3Dpol may adopt a different mechanism for handling its substrates and adapting to physiological requirements. Our findings will be valuable in the

  4. Genome wide predictions of miRNA regulation by transcription factors.

    Ruffalo, Matthew; Bar-Joseph, Ziv

    2016-09-01

    Reconstructing regulatory networks from expression and interaction data is a major goal of systems biology. While much work has focused on trying to experimentally and computationally determine the set of transcription-factors (TFs) and microRNAs (miRNAs) that regulate genes in these networks, relatively little work has focused on inferring the regulation of miRNAs by TFs. Such regulation can play an important role in several biological processes including development and disease. The main challenge for predicting such interactions is the very small positive training set currently available. Another challenge is the fact that a large fraction of miRNAs are encoded within genes making it hard to determine the specific way in which they are regulated. To enable genome wide predictions of TF-miRNA interactions, we extended semi-supervised machine-learning approaches to integrate a large set of different types of data including sequence, expression, ChIP-seq and epigenetic data. As we show, the methods we develop achieve good performance on both a labeled test set, and when analyzing general co-expression networks. We next analyze mRNA and miRNA cancer expression data, demonstrating the advantage of using the predicted set of interactions for identifying more coherent and relevant modules, genes, and miRNAs. The complete set of predictions is available on the supporting website and can be used by any method that combines miRNAs, genes, and TFs. Code and full set of predictions are available from the supporting website: http://cs.cmu.edu/~mruffalo/tf-mirna/ zivbj@cs.cmu.edu Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  5. MicroRNA classifier and nomogram for metastasis prediction in colon cancer.

    Goossens-Beumer, Inès J; Derr, Remco S; Buermans, Henk P J; Goeman, Jelle J; Böhringer, Stefan; Morreau, Hans; Nitsche, Ulrich; Janssen, Klaus-Peter; van de Velde, Cornelis J H; Kuppen, Peter J K

    2015-01-01

    Colon cancer prognosis and treatment are currently based on a classification system still showing large heterogeneity in clinical outcome, especially in TNM stages II and III. Prognostic biomarkers for metastasis risk are warranted as development of distant recurrent disease mainly accounts for the high lethality rates of colon cancer. miRNAs have been proposed as potential biomarkers for cancer. Furthermore, a verified standard for normalization of the amount of input material in PCR-based relative quantification of miRNA expression is lacking. A selection of frozen tumor specimens from two independent patient cohorts with TNM stage II-III microsatellite stable primary adenocarcinomas was used for laser capture microdissection. Next-generation sequencing was performed on small RNAs isolated from colorectal tumors from the Dutch cohort (N = 50). Differential expression analysis, comparing in metastasized and nonmetastasized tumors, identified prognostic miRNAs. Validation was performed on colon tumors from the German cohort (N = 43) using quantitative PCR (qPCR). miR25-3p and miR339-5p were identified and validated as independent prognostic markers and used to construct a multivariate nomogram for metastasis risk prediction. The nomogram showed good probability prediction in validation. In addition, we recommend combination of miR16-5p and miR26a-5p as standard for normalization in qPCR of colon cancer tissue-derived miRNA expression. In this international study, we identified and validated a miRNA classifier in primary cancers, and propose a nomogram capable of predicting metastasis risk in microsatellite stable TNM stage II-III colon cancer. In conjunction with TNM staging, by means of a nomogram, this miRNA classifier may allow for personalized treatment decisions based on individual tumor characteristics. ©2014 American Association for Cancer Research.

  6. Fine-grained parallelism accelerating for RNA secondary structure prediction with pseudoknots based on FPGA.

    Xia, Fei; Jin, Guoqing

    2014-06-01

    PKNOTS is a most famous benchmark program and has been widely used to predict RNA secondary structure including pseudoknots. It adopts the standard four-dimensional (4D) dynamic programming (DP) method and is the basis of many variants and improved algorithms. Unfortunately, the O(N(6)) computing requirements and complicated data dependency greatly limits the usefulness of PKNOTS package with the explosion in gene database size. In this paper, we present a fine-grained parallel PKNOTS package and prototype system for accelerating RNA folding application based on FPGA chip. We adopted a series of storage optimization strategies to resolve the "Memory Wall" problem. We aggressively exploit parallel computing strategies to improve computational efficiency. We also propose several methods that collectively reduce the storage requirements for FPGA on-chip memory. To the best of our knowledge, our design is the first FPGA implementation for accelerating 4D DP problem for RNA folding application including pseudoknots. The experimental results show a factor of more than 50x average speedup over the PKNOTS-1.08 software running on a PC platform with Intel Core2 Q9400 Quad CPU for input RNA sequences. However, the power consumption of our FPGA accelerator is only about 50% of the general-purpose micro-processors.

  7. Computational tools for genome-wide miRNA prediction and study

    Malas, T.B.; Ravasi, Timothy

    2012-01-01

    MicroRNAs (miRNAs) are single-stranded non-coding RNA susually of 22 nucleotidesin length that play an important post-transcriptional regulation role in many organisms. MicroRNAs bind a seed sequence to the 3-untranslated region (UTR) region of the target messenger RNA (mRNA), inducing degradation or inhibition of translation and resulting in a reduction in the protein level. This regulatory mechanism is central to many biological processes and perturbation could lead to diseases such as cancer. Given the biological importance, of miRNAs, there is a great need to identify and study their targets and functions. However, miRNAs are very difficult to clone in the lab and this has hindered the identification of novel miRNAs. Next-generation sequencing coupled with new computational tools has recently evolved to help researchers efficiently identify large numbers of novel miRNAs. In this review, we describe recent miRNA prediction tools and discuss their priorities, advantages and disadvantages. Malas and Ravasi.

  8. Computational tools for genome-wide miRNA prediction and study

    Malas, T.B.

    2012-11-02

    MicroRNAs (miRNAs) are single-stranded non-coding RNA susually of 22 nucleotidesin length that play an important post-transcriptional regulation role in many organisms. MicroRNAs bind a seed sequence to the 3-untranslated region (UTR) region of the target messenger RNA (mRNA), inducing degradation or inhibition of translation and resulting in a reduction in the protein level. This regulatory mechanism is central to many biological processes and perturbation could lead to diseases such as cancer. Given the biological importance, of miRNAs, there is a great need to identify and study their targets and functions. However, miRNAs are very difficult to clone in the lab and this has hindered the identification of novel miRNAs. Next-generation sequencing coupled with new computational tools has recently evolved to help researchers efficiently identify large numbers of novel miRNAs. In this review, we describe recent miRNA prediction tools and discuss their priorities, advantages and disadvantages. Malas and Ravasi.

  9. Predicting microRNA-disease associations using label propagation based on linear neighborhood similarity.

    Li, Guanghui; Luo, Jiawei; Xiao, Qiu; Liang, Cheng; Ding, Pingjian

    2018-05-12

    Interactions between microRNAs (miRNAs) and diseases can yield important information for uncovering novel prognostic markers. Since experimental determination of disease-miRNA associations is time-consuming and costly, attention has been given to designing efficient and robust computational techniques for identifying undiscovered interactions. In this study, we present a label propagation model with linear neighborhood similarity, called LPLNS, to predict unobserved miRNA-disease associations. Additionally, a preprocessing step is performed to derive new interaction likelihood profiles that will contribute to the prediction since new miRNAs and diseases lack known associations. Our results demonstrate that the LPLNS model based on the known disease-miRNA associations could achieve impressive performance with an AUC of 0.9034. Furthermore, we observed that the LPLNS model based on new interaction likelihood profiles could improve the performance to an AUC of 0.9127. This was better than other comparable methods. In addition, case studies also demonstrated our method's outstanding performance for inferring undiscovered interactions between miRNAs and diseases, especially for novel diseases. Copyright © 2018. Published by Elsevier Inc.

  10. MirZ: an integrated microRNA expression atlas and target prediction resource.

    Hausser, Jean; Berninger, Philipp; Rodak, Christoph; Jantscher, Yvonne; Wirth, Stefan; Zavolan, Mihaela

    2009-07-01

    MicroRNAs (miRNAs) are short RNAs that act as guides for the degradation and translational repression of protein-coding mRNAs. A large body of work showed that miRNAs are involved in the regulation of a broad range of biological functions, from development to cardiac and immune system function, to metabolism, to cancer. For most of the over 500 miRNAs that are encoded in the human genome the functions still remain to be uncovered. Identifying miRNAs whose expression changes between cell types or between normal and pathological conditions is an important step towards characterizing their function as is the prediction of mRNAs that could be targeted by these miRNAs. To provide the community the possibility of exploring interactively miRNA expression patterns and the candidate targets of miRNAs in an integrated environment, we developed the MirZ web server, which is accessible at www.mirz.unibas.ch. The server provides experimental and computational biologists with statistical analysis and data mining tools operating on up-to-date databases of sequencing-based miRNA expression profiles and of predicted miRNA target sites in species ranging from Caenorhabditis elegans to Homo sapiens.

  11. lncRNATargets: A platform for lncRNA target prediction based on nucleic acid thermodynamics.

    Hu, Ruifeng; Sun, Xiaobo

    2016-08-01

    Many studies have supported that long noncoding RNAs (lncRNAs) perform various functions in various critical biological processes. Advanced experimental and computational technologies allow access to more information on lncRNAs. Determining the functions and action mechanisms of these RNAs on a large scale is urgently needed. We provided lncRNATargets, which is a web-based platform for lncRNA target prediction based on nucleic acid thermodynamics. The nearest-neighbor (NN) model was used to calculate binging-free energy. The main principle of NN model for nucleic acid assumes that identity and orientation of neighbor base pairs determine stability of a given base pair. lncRNATargets features the following options: setting of a specific temperature that allow use not only for human but also for other animals or plants; processing all lncRNAs in high throughput without RNA size limitation that is superior to any other existing tool; and web-based, user-friendly interface, and colored result displays that allow easy access for nonskilled computer operators and provide better understanding of results. This technique could provide accurate calculation on the binding-free energy of lncRNA-target dimers to predict if these structures are well targeted together. lncRNATargets provides high accuracy calculations, and this user-friendly program is available for free at http://www.herbbol.org:8001/lrt/ .

  12. Identification of potential prognostic microRNA biomarkers for predicting survival in patients with hepatocellular carcinoma

    Liao X

    2018-04-01

    Full Text Available Xiwen Liao,1 Guangzhi Zhu,1 Rui Huang,2 Chengkun Yang,1 Xiangkun Wang,1 Ketuan Huang,1 Tingdong Yu,1 Chuangye Han,1 Hao Su,1 Tao Peng1 1Department of Hepatobiliary Surgery, The First Affiliated Hospital of Guangxi Medical University, Nanning, People’s Republic of China; 2Department of Hematology, The First Affiliated Hospital of Guangxi Medical University, Nanning, People’s Republic of China Background: The aim of the present study was to identify potential prognostic microRNA (miRNA biomarkers for hepatocellular carcinoma (HCC prognosis prediction based on a dataset from The Cancer Genome Atlas (TCGA. Materials and methods: A miRNA sequencing dataset and corresponding clinical parameters of HCC were obtained from TCGA. Genome-wide univariate Cox regression analysis was used to screen prognostic differentially expressed miRNAs (DEMs, and multivariable Cox regression analysis was used for prognostic signature construction. Comprehensive survival analysis was performed to evaluate the prognostic value of the prognostic signature. Results: Five miRNAs were regarded as prognostic DEMs and used for prognostic signature construction. The five-DEM prognostic signature performed well in prognosis prediction (adjusted P < 0.0001, adjusted hazard ratio = 2.249, 95% confidence interval =1.491–3.394, and time-dependent receiver–operating characteristic (ROC analysis showed an area under the curve (AUC of 0.765, 0.745, 0.725, and 0.687 for 1-, 2-, 3-, and 5-year HCC overall survival (OS prediction, respectively. Comprehensive survival analysis of the prognostic signature suggests that the risk score model could serve as an independent factor of HCC and perform better in prognosis prediction than other traditional clinical indicators. Functional assessment of the target genes of hsa-mir-139 and hsa-mir-5003 indicates that they were significantly enriched in multiple biological processes and pathways, including cell proliferation and cell migration

  13. Predictive biophysical modeling and understanding of the dynamics of mRNA translation and its evolution

    Zur, Hadas; Tuller, Tamir

    2016-01-01

    mRNA translation is the fundamental process of decoding the information encoded in mRNA molecules by the ribosome for the synthesis of proteins. The centrality of this process in various biomedical disciplines such as cell biology, evolution and biotechnology, encouraged the development of dozens of mathematical and computational models of translation in recent years. These models aimed at capturing various biophysical aspects of the process. The objective of this review is to survey these models, focusing on those based and/or validated on real large-scale genomic data. We consider aspects such as the complexity of the models, the biophysical aspects they regard and the predictions they may provide. Furthermore, we survey the central systems biology discoveries reported on their basis. This review demonstrates the fundamental advantages of employing computational biophysical translation models in general, and discusses the relative advantages of the different approaches and the challenges in the field. PMID:27591251

  14. Integration of RNA-Seq and RPPA data for survival time prediction in cancer patients.

    Isik, Zerrin; Ercan, Muserref Ece

    2017-10-01

    Integration of several types of patient data in a computational framework can accelerate the identification of more reliable biomarkers, especially for prognostic purposes. This study aims to identify biomarkers that can successfully predict the potential survival time of a cancer patient by integrating the transcriptomic (RNA-Seq), proteomic (RPPA), and protein-protein interaction (PPI) data. The proposed method -RPBioNet- employs a random walk-based algorithm that works on a PPI network to identify a limited number of protein biomarkers. Later, the method uses gene expression measurements of the selected biomarkers to train a classifier for the survival time prediction of patients. RPBioNet was applied to classify kidney renal clear cell carcinoma (KIRC), glioblastoma multiforme (GBM), and lung squamous cell carcinoma (LUSC) patients based on their survival time classes (long- or short-term). The RPBioNet method correctly identified the survival time classes of patients with between 66% and 78% average accuracy for three data sets. RPBioNet operates with only 20 to 50 biomarkers and can achieve on average 6% higher accuracy compared to the closest alternative method, which uses only RNA-Seq data in the biomarker selection. Further analysis of the most predictive biomarkers highlighted genes that are common for both cancer types, as they may be driver proteins responsible for cancer progression. The novelty of this study is the integration of a PPI network with mRNA and protein expression data to identify more accurate prognostic biomarkers that can be used for clinical purposes in the future. Copyright © 2017 Elsevier Ltd. All rights reserved.

  15. CID-miRNA: A web server for prediction of novel miRNA precursors in human genome

    Tyagi, Sonika; Vaz, Candida; Gupta, Vipin; Bhatia, Rohit; Maheshwari, Sachin; Srinivasan, Ashwin; Bhattacharya, Alok

    2008-01-01

    microRNAs (miRNA) are a class of non-protein coding functional RNAs that are thought to regulate expression of target genes by direct interaction with mRNAs. miRNAs have been identified through both experimental and computational methods in a variety of eukaryotic organisms. Though these approaches have been partially successful, there is a need to develop more tools for detection of these RNAs as they are also thought to be present in abundance in many genomes. In this report we describe a tool and a web server, named CID-miRNA, for identification of miRNA precursors in a given DNA sequence, utilising secondary structure-based filtering systems and an algorithm based on stochastic context free grammar trained on human miRNAs. CID-miRNA analyses a given sequence using a web interface, for presence of putative miRNA precursors and the generated output lists all the potential regions that can form miRNA-like structures. It can also scan large genomic sequences for the presence of potential miRNA precursors in its stand-alone form. The web server can be accessed at (http://mirna.jnu.ac.in/cidmirna/)

  16. A fast and robust iterative algorithm for prediction of RNA pseudoknotted secondary structures

    2014-01-01

    Background Improving accuracy and efficiency of computational methods that predict pseudoknotted RNA secondary structures is an ongoing challenge. Existing methods based on free energy minimization tend to be very slow and are limited in the types of pseudoknots that they can predict. Incorporating known structural information can improve prediction accuracy; however, there are not many methods for prediction of pseudoknotted structures that can incorporate structural information as input. There is even less understanding of the relative robustness of these methods with respect to partial information. Results We present a new method, Iterative HFold, for pseudoknotted RNA secondary structure prediction. Iterative HFold takes as input a pseudoknot-free structure, and produces a possibly pseudoknotted structure whose energy is at least as low as that of any (density-2) pseudoknotted structure containing the input structure. Iterative HFold leverages strengths of earlier methods, namely the fast running time of HFold, a method that is based on the hierarchical folding hypothesis, and the energy parameters of HotKnots V2.0. Our experimental evaluation on a large data set shows that Iterative HFold is robust with respect to partial information, with average accuracy on pseudoknotted structures steadily increasing from roughly 54% to 79% as the user provides up to 40% of the input structure. Iterative HFold is much faster than HotKnots V2.0, while having comparable accuracy. Iterative HFold also has significantly better accuracy than IPknot on our HK-PK and IP-pk168 data sets. Conclusions Iterative HFold is a robust method for prediction of pseudoknotted RNA secondary structures, whose accuracy with more than 5% information about true pseudoknot-free structures is better than that of IPknot, and with about 35% information about true pseudoknot-free structures compares well with that of HotKnots V2.0 while being significantly faster. Iterative HFold and all data used in

  17. Analysis of energy-based algorithms for RNA secondary structure prediction

    Hajiaghayi Monir

    2012-02-01

    Full Text Available Abstract Background RNA molecules play critical roles in the cells of organisms, including roles in gene regulation, catalysis, and synthesis of proteins. Since RNA function depends in large part on its folded structures, much effort has been invested in developing accurate methods for prediction of RNA secondary structure from the base sequence. Minimum free energy (MFE predictions are widely used, based on nearest neighbor thermodynamic parameters of Mathews, Turner et al. or those of Andronescu et al. Some recently proposed alternatives that leverage partition function calculations find the structure with maximum expected accuracy (MEA or pseudo-expected accuracy (pseudo-MEA methods. Advances in prediction methods are typically benchmarked using sensitivity, positive predictive value and their harmonic mean, namely F-measure, on datasets of known reference structures. Since such benchmarks document progress in improving accuracy of computational prediction methods, it is important to understand how measures of accuracy vary as a function of the reference datasets and whether advances in algorithms or thermodynamic parameters yield statistically significant improvements. Our work advances such understanding for the MFE and (pseudo-MEA-based methods, with respect to the latest datasets and energy parameters. Results We present three main findings. First, using the bootstrap percentile method, we show that the average F-measure accuracy of the MFE and (pseudo-MEA-based algorithms, as measured on our largest datasets with over 2000 RNAs from diverse families, is a reliable estimate (within a 2% range with high confidence of the accuracy of a population of RNA molecules represented by this set. However, average accuracy on smaller classes of RNAs such as a class of 89 Group I introns used previously in benchmarking algorithm accuracy is not reliable enough to draw meaningful conclusions about the relative merits of the MFE and MEA-based algorithms

  18. Instant Spring Tool Suite

    Chiang, Geoff

    2013-01-01

    Filled with practical, step-by-step instructions and clear explanations for the most important and useful tasks. A tutorial guide that walks you through how to use the features of Spring Tool Suite using well defined sections for the different parts of Spring.Instant Spring Tool Suite is for novice to intermediate Java developers looking to get a head-start in enterprise application development using Spring Tool Suite and the Spring framework. If you are looking for a guide for effective application development using Spring Tool Suite, then this book is for you.

  19. Clinical values of AFP, GPC3 mRNA in peripheral blood for prediction of hepatocellular carcinoma recurrence following OLT: AFP, GPC3 mRNA for prediction of HCC.

    Wang, Yuliang; Shen, Zhongyang; Zhu, Zhijun; Han, Ruifa; Huai, Mingsheng

    2011-03-01

    Hepatocellular carcinoma (HCC) is one of the most common malignancies worldwide. Annually, about 200,000 patients died of HCC in China. Liver transplantation (LT) holds great theoretical appeal in treating HCC. However, the high recurrence rate after transplantation is the most important limiting factor for long-term survival. To assess the value of alpha-fetoprotein (AFP) messenger RNA (mRNA), Glypican-3 (GPC3) mRNA-expressing cells in the peripheral blood (PB) for prediction of HCC recurrence following orthotopic liver transplantation (OLT). 29 patients with HCC who underwent OLT with a minimum clinical follow-up of 12 months were included in this retrospective study. We detected AFP mRNA, GPC3 mRNA-expressing cells in the PB by TaqMan real-time reverse transcriptase-polymerase chain reaction (RT-PCR), pre-, intra- and post-operatively. The early recurrence of patients was evaluated. 8 (28%), 15 (52%), and 9 (31%) patients had AFP mRNA detected pre-, intra-, and post-operatively, respectively. With 12 months of follow-up, HCC recurred in 7 (24%) patients. Univariate analysis revealed that positive pre- and post-operative AFP mRNA, TNM stage as well as vascular invasion were significant predictors for the HCC recurrence. Multivariate analysis revealed that being positive for AFP mRNA pre-operatively remained a significant risk factor for HCC recurrence after OLT. GPC3 mRNA was expressed in all PB samples. There was no significant difference in the expression levels of GPC3 mRNA between the HCC and control groups. There were no significant differences in GPC3 mRNA expression values between those patients with and without tumor recurrence. The pre-operative detection of circulating AFP mRNA-expressing cells could be a useful predictor for HCC recurrence following OLT. GPC3 mRNA-expressing cells in PB seem to have no diagnostic value.

  20. Spliceman2: a computational web server that predicts defects in pre-mRNA splicing.

    Cygan, Kamil Jan; Sanford, Clayton Hendrick; Fairbrother, William Guy

    2017-09-15

    Most pre-mRNA transcripts in eukaryotic cells must undergo splicing to remove introns and join exons, and splicing elements present a large mutational target for disease-causing mutations. Splicing elements are strongly position dependent with respect to the transcript annotations. In 2012, we presented Spliceman, an online tool that used positional dependence to predict how likely distant mutations around annotated splice sites were to disrupt splicing. Here, we present an improved version of the previous tool that will be more useful for predicting the likelihood of splicing mutations. We have added industry-standard input options (i.e. Spliceman now accepts variant call format files), which allow much larger inputs than previously available. The tool also can visualize the locations-within exons and introns-of sequence variants to be analyzed and the predicted effects on splicing of the pre-mRNA transcript. In addition, Spliceman2 integrates with RNAcompete motif libraries to provide a prediction of which trans -acting factors binding sites are disrupted/created and links out to the UCSC genome browser. In summary, the new features in Spliceman2 will allow scientists and physicians to better understand the effects of single nucleotide variations on splicing. Freely available on the web at http://fairbrother.biomed.brown.edu/spliceman2 . Website implemented in PHP framework-Laravel 5, PostgreSQL, Apache, and Perl, with all major browsers supported. william_fairbrother@brown.edu. Supplementary data are available at Bioinformatics online. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

  1. Validation suite for MCNP

    Mosteller, Russell D.

    2002-01-01

    Two validation suites, one for criticality and another for radiation shielding, have been defined and tested for the MCNP Monte Carlo code. All of the cases in the validation suites are based on experiments so that calculated and measured results can be compared in a meaningful way. The cases in the validation suites are described, and results from those cases are discussed. For several years, the distribution package for the MCNP Monte Carlo code1 has included an installation test suite to verify that MCNP has been installed correctly. However, the cases in that suite have been constructed primarily to test options within the code and to execute quickly. Consequently, they do not produce well-converged answers, and many of them are physically unrealistic. To remedy these deficiencies, sets of validation suites are being defined and tested for specific types of applications. All of the cases in the validation suites are based on benchmark experiments. Consequently, the results from the measurements are reliable and quantifiable, and calculated results can be compared with them in a meaningful way. Currently, validation suites exist for criticality and radiation-shielding applications.

  2. Pharmacy settles suit.

    1998-10-02

    A suit was filed by an HIV-positive man against a pharmacy that inadvertently disclosed his HIV status to his ex-wife and children. His ex-wife tried to use the information in a custody battle for their two children. The suit against the pharmacy was settled, but the terms of the settlement remain confidential.

  3. lncRNA Gene Signatures for Prediction of Breast Cancer Intrinsic Subtypes and Prognosis

    Silu Zhang

    2018-01-01

    Full Text Available Background: Breast cancer is intrinsically heterogeneous and is commonly classified into four main subtypes associated with distinct biological features and clinical outcomes. However, currently available data resources and methods are limited in identifying molecular subtyping on protein-coding genes, and little is known about the roles of long non-coding RNAs (lncRNAs, which occupies 98% of the whole genome. lncRNAs may also play important roles in subgrouping cancer patients and are associated with clinical phenotypes. Methods: The purpose of this project was to identify lncRNA gene signatures that are associated with breast cancer subtypes and clinical outcomes. We identified lncRNA gene signatures from The Cancer Genome Atlas (TCGA RNAseq data that are associated with breast cancer subtypes by an optimized 1-Norm SVM feature selection algorithm. We evaluated the prognostic performance of these gene signatures with a semi-supervised principal component (superPC method. Results: Although lncRNAs can independently predict breast cancer subtypes with satisfactory accuracy, a combined gene signature including both coding and non-coding genes will give the best clinically relevant prediction performance. We highlighted eight potential biomarkers (three from coding genes and five from non-coding genes that are significantly associated with survival outcomes. Conclusion: Our proposed methods are a novel means of identifying subtype-specific coding and non-coding potential biomarkers that are both clinically relevant and biologically significant.

  4. Prediction of hydrogen and carbon chemical shifts from RNA using database mining and support vector regression

    Brown, Joshua D.; Summers, Michael F. [University of Maryland Baltimore County, Howard Hughes Medical Institute (United States); Johnson, Bruce A., E-mail: bruce.johnson@asrc.cuny.edu [University of Maryland Baltimore County, Department of Chemistry and Biochemistry (United States)

    2015-09-15

    The Biological Magnetic Resonance Data Bank (BMRB) contains NMR chemical shift depositions for over 200 RNAs and RNA-containing complexes. We have analyzed the {sup 1}H NMR and {sup 13}C chemical shifts reported for non-exchangeable protons of 187 of these RNAs. Software was developed that downloads BMRB datasets and corresponding PDB structure files, and then generates residue-specific attributes based on the calculated secondary structure. Attributes represent properties present in each sequential stretch of five adjacent residues and include variables such as nucleotide type, base-pair presence and type, and tetraloop types. Attributes and {sup 1}H and {sup 13}C NMR chemical shifts of the central nucleotide are then used as input to train a predictive model using support vector regression. These models can then be used to predict shifts for new sequences. The new software tools, available as stand-alone scripts or integrated into the NMR visualization and analysis program NMRViewJ, should facilitate NMR assignment and/or validation of RNA {sup 1}H and {sup 13}C chemical shifts. In addition, our findings enabled the re-calibration a ring-current shift model using published NMR chemical shifts and high-resolution X-ray structural data as guides.

  5. The predictive value of microRNA-126 in relation to first line treatment with capecitabine and oxaliplatin in patients with metastatic colorectal cancer

    Hansen, Torben Frøstrup; Sørensen, Flemming Brandt; Lindebjerg, Jan

    2012-01-01

    MicroRNA-126 is the only microRNA (miRNA) known to be endothelial cell-specific influencing angiogenesis in several ways. The aim of the present study was to analyse the possible predictive value of miRNA-126 in relation to first line capecitabine and oxaliplatin (XELOX) in patients with metastatic...

  6. Analysis and prediction of translation rate based on sequence and functional features of the mRNA.

    Tao Huang

    Full Text Available Protein concentrations depend not only on the mRNA level, but also on the translation rate and the degradation rate. Prediction of mRNA's translation rate would provide valuable information for in-depth understanding of the translation mechanism and dynamic proteome. In this study, we developed a new computational model to predict the translation rate, featured by (1 integrating various sequence-derived and functional features, (2 applying the maximum relevance & minimum redundancy method and incremental feature selection to select features to optimize the prediction model, and (3 being able to predict the translation rate of RNA into high or low translation rate category. The prediction accuracies under rich and starvation condition were 68.8% and 70.0%, respectively, evaluated by jackknife cross-validation. It was found that the following features were correlated with translation rate: codon usage frequency, some gene ontology enrichment scores, number of RNA binding proteins known to bind its mRNA product, coding sequence length, protein abundance and 5'UTR free energy. These findings might provide useful information for understanding the mechanisms of translation and dynamic proteome. Our translation rate prediction model might become a high throughput tool for annotating the translation rate of mRNAs in large-scale.

  7. MKRMDA: multiple kernel learning-based Kronecker regularized least squares for MiRNA-disease association prediction.

    Chen, Xing; Niu, Ya-Wei; Wang, Guang-Hui; Yan, Gui-Ying

    2017-12-12

    Recently, as the research of microRNA (miRNA) continues, there are plenty of experimental evidences indicating that miRNA could be associated with various human complex diseases development and progression. Hence, it is necessary and urgent to pay more attentions to the relevant study of predicting diseases associated miRNAs, which may be helpful for effective prevention, diagnosis and treatment of human diseases. Especially, constructing computational methods to predict potential miRNA-disease associations is worthy of more studies because of the feasibility and effectivity. In this work, we developed a novel computational model of multiple kernels learning-based Kronecker regularized least squares for MiRNA-disease association prediction (MKRMDA), which could reveal potential miRNA-disease associations by automatically optimizing the combination of multiple kernels for disease and miRNA. MKRMDA obtained AUCs of 0.9040 and 0.8446 in global and local leave-one-out cross validation, respectively. Meanwhile, MKRMDA achieved average AUCs of 0.8894 ± 0.0015 in fivefold cross validation. Furthermore, we conducted three different kinds of case studies on some important human cancers for further performance evaluation. In the case studies of colonic cancer, esophageal cancer and lymphoma based on known miRNA-disease associations in HMDDv2.0 database, 76, 94 and 88% of the corresponding top 50 predicted miRNAs were confirmed by experimental reports, respectively. In another two kinds of case studies for new diseases without any known associated miRNAs and diseases only with known associations in HMDDv1.0 database, the verified ratios of two different cancers were 88 and 94%, respectively. All the results mentioned above adequately showed the reliable prediction ability of MKRMDA. We anticipated that MKRMDA could serve to facilitate further developments in the field and the follow-up investigations by biomedical researchers.

  8. MicroRNA prediction using a fixed-order Markov model based on the secondary structure pattern.

    Wei Shen

    Full Text Available Predicting miRNAs is an arduous task, due to the diversity of the precursors and complexity of enzyme processes. Although several prediction approaches have reached impressive performances, few of them could achieve a full-function recognition of mature miRNA directly from the candidate hairpins across species. Therefore, researchers continue to seek a more powerful model close to biological recognition to miRNA structure. In this report, we describe a novel miRNA prediction algorithm, known as FOMmiR, using a fixed-order Markov model based on the secondary structural pattern. For a training dataset containing 809 human pre-miRNAs and 6441 human pseudo-miRNA hairpins, the model's parameters were defined and evaluated. The results showed that FOMmiR reached 91% accuracy on the human dataset through 5-fold cross-validation. Moreover, for the independent test datasets, the FOMmiR presented an outstanding prediction in human and other species including vertebrates, Drosophila, worms and viruses, even plants, in contrast to the well-known algorithms and models. Especially, the FOMmiR was not only able to distinguish the miRNA precursors from the hairpins, but also locate the position and strand of the mature miRNA. Therefore, this study provides a new generation of miRNA prediction algorithm, which successfully realizes a full-function recognition of the mature miRNAs directly from the hairpin sequences. And it presents a new understanding of the biological recognition based on the strongest signal's location detected by FOMmiR, which might be closely associated with the enzyme cleavage mechanism during the miRNA maturation.

  9. Predicting microRNA precursors with a generalized Gaussian components based density estimation algorithm

    Wu Chi-Yeh

    2010-01-01

    Full Text Available Abstract Background MicroRNAs (miRNAs are short non-coding RNA molecules, which play an important role in post-transcriptional regulation of gene expression. There have been many efforts to discover miRNA precursors (pre-miRNAs over the years. Recently, ab initio approaches have attracted more attention because they do not depend on homology information and provide broader applications than comparative approaches. Kernel based classifiers such as support vector machine (SVM are extensively adopted in these ab initio approaches due to the prediction performance they achieved. On the other hand, logic based classifiers such as decision tree, of which the constructed model is interpretable, have attracted less attention. Results This article reports the design of a predictor of pre-miRNAs with a novel kernel based classifier named the generalized Gaussian density estimator (G2DE based classifier. The G2DE is a kernel based algorithm designed to provide interpretability by utilizing a few but representative kernels for constructing the classification model. The performance of the proposed predictor has been evaluated with 692 human pre-miRNAs and has been compared with two kernel based and two logic based classifiers. The experimental results show that the proposed predictor is capable of achieving prediction performance comparable to those delivered by the prevailing kernel based classification algorithms, while providing the user with an overall picture of the distribution of the data set. Conclusion Software predictors that identify pre-miRNAs in genomic sequences have been exploited by biologists to facilitate molecular biology research in recent years. The G2DE employed in this study can deliver prediction accuracy comparable with the state-of-the-art kernel based machine learning algorithms. Furthermore, biologists can obtain valuable insights about the different characteristics of the sequences of pre-miRNAs with the models generated by the G

  10. The predictive and prognostic potential of plasma telomerase reverse transcriptase (TERT) RNA in rectal cancer patients

    Rampazzo, Enrica; Del Bianco, Paola; Bertorelle, Roberta; Boso, Caterina; Perin, Alessandro; Spiro, Giovanna; Bergamo, Francesca; Belluco, Claudio; Buonadonna, Angela; Palazzari, Elisa; Leonardi, Sara; De Paoli, Antonino; Pucciarelli, Salvatore; De Rossi, Anita

    2018-01-01

    Background: Preoperative chemoradiotherapy (CRT) followed by surgery is the standard care for locally advanced rectal cancer, but tumour response to CRT and disease outcome are variable. The current study aimed to investigate the effectiveness of plasma telomerase reverse transcriptase (TERT) levels in predicting tumour response and clinical outcome. Methods: 176 rectal cancer patients were included. Plasma samples were collected at baseline (before CRT=T0), 2 weeks after CRT was initiated (T1), post-CRT and before surgery (T2), and 4–8 months after surgery (T3) time points. Plasma TERT mRNA levels and total cell-free RNA were determined using real-time PCR. Results: Plasma levels of TERT were significantly lower at T2 (P<0.0001) in responders than in non-responders. Post-CRT TERT levels and the differences between pre- and post-CRT TERT levels independently predicted tumour response, and the prediction model had an area under curve of 0.80 (95% confidence interval (CI) 0.73–0.87). Multiple analysis demonstrated that patients with detectable TERT levels at T2 and T3 time points had a risk of disease progression 2.13 (95% CI 1.10–4.11)-fold and 4.55 (95% CI 1.48–13.95)-fold higher, respectively, than those with undetectable plasma TERT levels. Conclusions: Plasma TERT levels are independent markers of tumour response and are prognostic of disease progression in rectal cancer patients who undergo neoadjuvant therapy. PMID:29449673

  11. Improving model predictions for RNA interference activities that use support vector machine regression by combining and filtering features

    Peek Andrew S

    2007-06-01

    Full Text Available Abstract Background RNA interference (RNAi is a naturally occurring phenomenon that results in the suppression of a target RNA sequence utilizing a variety of possible methods and pathways. To dissect the factors that result in effective siRNA sequences a regression kernel Support Vector Machine (SVM approach was used to quantitatively model RNA interference activities. Results Eight overall feature mapping methods were compared in their abilities to build SVM regression models that predict published siRNA activities. The primary factors in predictive SVM models are position specific nucleotide compositions. The secondary factors are position independent sequence motifs (N-grams and guide strand to passenger strand sequence thermodynamics. Finally, the factors that are least contributory but are still predictive of efficacy are measures of intramolecular guide strand secondary structure and target strand secondary structure. Of these, the site of the 5' most base of the guide strand is the most informative. Conclusion The capacity of specific feature mapping methods and their ability to build predictive models of RNAi activity suggests a relative biological importance of these features. Some feature mapping methods are more informative in building predictive models and overall t-test filtering provides a method to remove some noisy features or make comparisons among datasets. Together, these features can yield predictive SVM regression models with increased predictive accuracy between predicted and observed activities both within datasets by cross validation, and between independently collected RNAi activity datasets. Feature filtering to remove features should be approached carefully in that it is possible to reduce feature set size without substantially reducing predictive models, but the features retained in the candidate models become increasingly distinct. Software to perform feature prediction and SVM training and testing on nucleic acid

  12. Predicting human miRNA target genes using a novel evolutionary methodology

    Aigli, Korfiati; Kleftogiannis, Dimitrios A.; Konstantinos, Theofilatos; Spiros, Likothanassis; Athanasios, Tsakalidis; Seferina, Mavroudi

    2012-01-01

    The discovery of miRNAs had great impacts on traditional biology. Typically, miRNAs have the potential to bind to the 3'untraslated region (UTR) of their mRNA target genes for cleavage or translational repression. The experimental identification of their targets has many drawbacks including cost, time and low specificity and these are the reasons why many computational approaches have been developed so far. However, existing computational approaches do not include any advanced feature selection technique and they are facing problems concerning their classification performance and their interpretability. In the present paper, we propose a novel hybrid methodology which combines genetic algorithms and support vector machines in order to locate the optimal feature subset while achieving high classification performance. The proposed methodology was compared with two of the most promising existing methodologies in the problem of predicting human miRNA targets. Our approach outperforms existing methodologies in terms of classification performances while selecting a much smaller feature subset. © 2012 Springer-Verlag.

  13. Predicting human miRNA target genes using a novel evolutionary methodology

    Aigli, Korfiati

    2012-01-01

    The discovery of miRNAs had great impacts on traditional biology. Typically, miRNAs have the potential to bind to the 3\\'untraslated region (UTR) of their mRNA target genes for cleavage or translational repression. The experimental identification of their targets has many drawbacks including cost, time and low specificity and these are the reasons why many computational approaches have been developed so far. However, existing computational approaches do not include any advanced feature selection technique and they are facing problems concerning their classification performance and their interpretability. In the present paper, we propose a novel hybrid methodology which combines genetic algorithms and support vector machines in order to locate the optimal feature subset while achieving high classification performance. The proposed methodology was compared with two of the most promising existing methodologies in the problem of predicting human miRNA targets. Our approach outperforms existing methodologies in terms of classification performances while selecting a much smaller feature subset. © 2012 Springer-Verlag.

  14. G-cimp status prediction of glioblastoma samples using mRNA expression data.

    Mehmet Baysan

    Full Text Available Glioblastoma Multiforme (GBM is a tumor with high mortality and no known cure. The dramatic molecular and clinical heterogeneity seen in this tumor has led to attempts to define genetically similar subgroups of GBM with the hope of developing tumor specific therapies targeted to the unique biology within each of these subgroups. Recently, a subset of relatively favorable prognosis GBMs has been identified. These glioma CpG island methylator phenotype, or G-CIMP tumors, have distinct genomic copy number aberrations, DNA methylation patterns, and (mRNA expression profiles compared to other GBMs. While the standard method for identifying G-CIMP tumors is based on genome-wide DNA methylation data, such data is often not available compared to the more widely available gene expression data. In this study, we have developed and evaluated a method to predict the G-CIMP status of GBM samples based solely on gene expression data.

  15. G-cimp status prediction of glioblastoma samples using mRNA expression data.

    Baysan, Mehmet; Bozdag, Serdar; Cam, Margaret C; Kotliarova, Svetlana; Ahn, Susie; Walling, Jennifer; Killian, Jonathan K; Stevenson, Holly; Meltzer, Paul; Fine, Howard A

    2012-01-01

    Glioblastoma Multiforme (GBM) is a tumor with high mortality and no known cure. The dramatic molecular and clinical heterogeneity seen in this tumor has led to attempts to define genetically similar subgroups of GBM with the hope of developing tumor specific therapies targeted to the unique biology within each of these subgroups. Recently, a subset of relatively favorable prognosis GBMs has been identified. These glioma CpG island methylator phenotype, or G-CIMP tumors, have distinct genomic copy number aberrations, DNA methylation patterns, and (mRNA) expression profiles compared to other GBMs. While the standard method for identifying G-CIMP tumors is based on genome-wide DNA methylation data, such data is often not available compared to the more widely available gene expression data. In this study, we have developed and evaluated a method to predict the G-CIMP status of GBM samples based solely on gene expression data.

  16. SRMDAP: SimRank and Density-Based Clustering Recommender Model for miRNA-Disease Association Prediction

    Xiaoying Li

    2018-01-01

    Full Text Available Aberrant expression of microRNAs (miRNAs can be applied for the diagnosis, prognosis, and treatment of human diseases. Identifying the relationship between miRNA and human disease is important to further investigate the pathogenesis of human diseases. However, experimental identification of the associations between diseases and miRNAs is time-consuming and expensive. Computational methods are efficient approaches to determine the potential associations between diseases and miRNAs. This paper presents a new computational method based on the SimRank and density-based clustering recommender model for miRNA-disease associations prediction (SRMDAP. The AUC of 0.8838 based on leave-one-out cross-validation and case studies suggested the excellent performance of the SRMDAP in predicting miRNA-disease associations. SRMDAP could also predict diseases without any related miRNAs and miRNAs without any related diseases.

  17. Atomic-accuracy prediction of protein loop structures through an RNA-inspired Ansatz.

    Rhiju Das

    Full Text Available Consistently predicting biopolymer structure at atomic resolution from sequence alone remains a difficult problem, even for small sub-segments of large proteins. Such loop prediction challenges, which arise frequently in comparative modeling and protein design, can become intractable as loop lengths exceed 10 residues and if surrounding side-chain conformations are erased. Current approaches, such as the protein local optimization protocol or kinematic inversion closure (KIC Monte Carlo, involve stages that coarse-grain proteins, simplifying modeling but precluding a systematic search of all-atom configurations. This article introduces an alternative modeling strategy based on a 'stepwise ansatz', recently developed for RNA modeling, which posits that any realistic all-atom molecular conformation can be built up by residue-by-residue stepwise enumeration. When harnessed to a dynamic-programming-like recursion in the Rosetta framework, the resulting stepwise assembly (SWA protocol enables enumerative sampling of a 12 residue loop at a significant but achievable cost of thousands of CPU-hours. In a previously established benchmark, SWA recovers crystallographic conformations with sub-Angstrom accuracy for 19 of 20 loops, compared to 14 of 20 by KIC modeling with a comparable expenditure of computational power. Furthermore, SWA gives high accuracy results on an additional set of 15 loops highlighted in the biological literature for their irregularity or unusual length. Successes include cis-Pro touch turns, loops that pass through tunnels of other side-chains, and loops of lengths up to 24 residues. Remaining problem cases are traced to inaccuracies in the Rosetta all-atom energy function. In five additional blind tests, SWA achieves sub-Angstrom accuracy models, including the first such success in a protein/RNA binding interface, the YbxF/kink-turn interaction in the fourth 'RNA-puzzle' competition. These results establish all-atom enumeration as

  18. Multi-task learning for cross-platform siRNA efficacy prediction: an in-silico study.

    Liu, Qi; Xu, Qian; Zheng, Vincent W; Xue, Hong; Cao, Zhiwei; Yang, Qiang

    2010-04-10

    Gene silencing using exogenous small interfering RNAs (siRNAs) is now a widespread molecular tool for gene functional study and new-drug target identification. The key mechanism in this technique is to design efficient siRNAs that incorporated into the RNA-induced silencing complexes (RISC) to bind and interact with the mRNA targets to repress their translations to proteins. Although considerable progress has been made in the computational analysis of siRNA binding efficacy, few joint analysis of different RNAi experiments conducted under different experimental scenarios has been done in research so far, while the joint analysis is an important issue in cross-platform siRNA efficacy prediction. A collective analysis of RNAi mechanisms for different datasets and experimental conditions can often provide new clues on the design of potent siRNAs. An elegant multi-task learning paradigm for cross-platform siRNA efficacy prediction is proposed. Experimental studies were performed on a large dataset of siRNA sequences which encompass several RNAi experiments recently conducted by different research groups. By using our multi-task learning method, the synergy among different experiments is exploited and an efficient multi-task predictor for siRNA efficacy prediction is obtained. The 19 most popular biological features for siRNA according to their jointly importance in multi-task learning were ranked. Furthermore, the hypothesis is validated out that the siRNA binding efficacy on different messenger RNAs(mRNAs) have different conditional distribution, thus the multi-task learning can be conducted by viewing tasks at an "mRNA"-level rather than at the "experiment"-level. Such distribution diversity derived from siRNAs bound to different mRNAs help indicate that the properties of target mRNA have important implications on the siRNA binding efficacy. The knowledge gained from our study provides useful insights on how to analyze various cross-platform RNAi data for uncovering

  19. Multi-task learning for cross-platform siRNA efficacy prediction: an in-silico study

    Xue Hong

    2010-04-01

    Full Text Available Abstract Background Gene silencing using exogenous small interfering RNAs (siRNAs is now a widespread molecular tool for gene functional study and new-drug target identification. The key mechanism in this technique is to design efficient siRNAs that incorporated into the RNA-induced silencing complexes (RISC to bind and interact with the mRNA targets to repress their translations to proteins. Although considerable progress has been made in the computational analysis of siRNA binding efficacy, few joint analysis of different RNAi experiments conducted under different experimental scenarios has been done in research so far, while the joint analysis is an important issue in cross-platform siRNA efficacy prediction. A collective analysis of RNAi mechanisms for different datasets and experimental conditions can often provide new clues on the design of potent siRNAs. Results An elegant multi-task learning paradigm for cross-platform siRNA efficacy prediction is proposed. Experimental studies were performed on a large dataset of siRNA sequences which encompass several RNAi experiments recently conducted by different research groups. By using our multi-task learning method, the synergy among different experiments is exploited and an efficient multi-task predictor for siRNA efficacy prediction is obtained. The 19 most popular biological features for siRNA according to their jointly importance in multi-task learning were ranked. Furthermore, the hypothesis is validated out that the siRNA binding efficacy on different messenger RNAs(mRNAs have different conditional distribution, thus the multi-task learning can be conducted by viewing tasks at an "mRNA"-level rather than at the "experiment"-level. Such distribution diversity derived from siRNAs bound to different mRNAs help indicate that the properties of target mRNA have important implications on the siRNA binding efficacy. Conclusions The knowledge gained from our study provides useful insights on how to

  20. High Class-Imbalance in pre-miRNA Prediction: A Novel Approach Based on deepSOM.

    Stegmayer, Georgina; Yones, Cristian; Kamenetzky, Laura; Milone, Diego H

    2017-01-01

    The computational prediction of novel microRNA within a full genome involves identifying sequences having the highest chance of being a miRNA precursor (pre-miRNA). These sequences are usually named candidates to miRNA. The well-known pre-miRNAs are usually only a few in comparison to the hundreds of thousands of potential candidates to miRNA that have to be analyzed, which makes this task a high class-imbalance classification problem. The classical way of approaching it has been training a binary classifier in a supervised manner, using well-known pre-miRNAs as positive class and artificially defining the negative class. However, although the selection of positive labeled examples is straightforward, it is very difficult to build a set of negative examples in order to obtain a good set of training samples for a supervised method. In this work, we propose a novel and effective way of approaching this problem using machine learning, without the definition of negative examples. The proposal is based on clustering unlabeled sequences of a genome together with well-known miRNA precursors for the organism under study, which allows for the quick identification of the best candidates to miRNA as those sequences clustered with known precursors. Furthermore, we propose a deep model to overcome the problem of having very few positive class labels. They are always maintained in the deep levels as positive class while less likely pre-miRNA sequences are filtered level after level. Our approach has been compared with other methods for pre-miRNAs prediction in several species, showing effective predictivity of novel miRNAs. Additionally, we will show that our approach has a lower training time and allows for a better graphical navegability and interpretation of the results. A web-demo interface to try deepSOM is available at http://fich.unl.edu.ar/sinc/web-demo/deepsom/.

  1. Inferring microRNA regulation of mRNA with partially ordered samples of paired expression data and exogenous prediction algorithms.

    Brian Godsey

    Full Text Available MicroRNAs (miRs are known to play an important role in mRNA regulation, often by binding to complementary sequences in "target" mRNAs. Recently, several methods have been developed by which existing sequence-based target predictions can be combined with miR and mRNA expression data to infer true miR-mRNA targeting relationships. It has been shown that the combination of these two approaches gives more reliable results than either by itself. While a few such algorithms give excellent results, none fully addresses expression data sets with a natural ordering of the samples. If the samples in an experiment can be ordered or partially ordered by their expected similarity to one another, such as for time-series or studies of development processes, stages, or types, (e.g. cell type, disease, growth, aging, there are unique opportunities to infer miR-mRNA interactions that may be specific to the underlying processes, and existing methods do not exploit this. We propose an algorithm which specifically addresses [partially] ordered expression data and takes advantage of sample similarities based on the ordering structure. This is done within a Bayesian framework which specifies posterior distributions and therefore statistical significance for each model parameter and latent variable. We apply our model to a previously published expression data set of paired miR and mRNA arrays in five partially ordered conditions, with biological replicates, related to multiple myeloma, and we show how considering potential orderings can improve the inference of miR-mRNA interactions, as measured by existing knowledge about the involved transcripts.

  2. miRNA signatures can predict acute liver failure in hepatitis E infected pregnant females

    Nirupma Trehanpati

    2017-04-01

    Full Text Available Background: Acute viral hepatitis E (AVH-E can often result in acute liver failure (ALF during pregnancy. microRNAs serve as mediators in drug induced liver failure. We investigated their role as a biomarker in predicting ALF due to HEV (ALF-E. Methods: We performed next generation sequencing and subsequent validation studies in PBMCs of pregnant (P self limiting AVH-E, ALF due to HEV (ALF-E and compared with AVH-E in non-pregnant (NP females and healthy controls. Findings: Eleven microRNAs were significantly expressed in response to HEV infection; importantly, miR- 431, 654, 1468 and 4435, were distinctly expressed in pregnant self-limiting AVH-E and healthy females (p = 0.0005, but not in ALF-E. Sixteen exclusive microRNAs differentiated ALF-E from self limiting AVH-E in pregnant females. miR-450b which affects cellular proliferation and metabolic processes through RNF20 and SECB was predominanlty upregulated and correlated with poor outcome (ROC 0.958, p = 0.001. Interpretation: Our results reveal that a specific microRNA profile can predict fatality in ALF-E in pregnancy. These microRNAs could be exploited as prognostic biomarkers and help in the development of new therapeutic interventions. Keywords: Health sciences, Virology

  3. Increased Expression of microRNA-17 Predicts Poor Prognosis in Human Glioma

    Shengkui Lu

    2012-01-01

    Full Text Available Aim. To investigate the clinical significance of microRNA-17 (miR-17 expression in human gliomas. Methods. Quantitative real-time polymerase chain reaction (qRT-PCR analysis was used to characterize the expression patterns of miR-17 in 108 glioma and 20 normal brain tissues. The associations of miR-17 expression with clinicopathological factors and prognosis of glioma patients were also statistically analyzed. Results. Compared with normal brain tissues, miR-17 expression was significantly higher in glioma tissues (P<0.001. In addition, the increased expression of miR-17 in glioma was significantly associated with advanced pathological grade (P=0.006 and low Karnofsky performance score (KPS, P=0.01. Moreover, Kaplan-Meier survival and Cox regression analyses showed that miR-17 overexpression (P=0.008 and advanced pathological grade (P=0.02 were independent factors predicting poor prognosis for gliomas. Furthermore, subgroup analyses showed that miR-17 expression was significantly associated with poor overall survival in glioma patients with high pathological grades (for grade III~IV: P<0.001. Conclusions. Our data offer the convinced evidence that the increased expression of miR-17 may have potential value for predicting poor prognosis in glioma patients with high pathological grades, indicating that miR-17 may contribute to glioma progression and be a candidate therapeutic target for this disease.

  4. A nucleobase-centered coarse-grained representation for structure prediction of RNA motifs.

    Poblete, Simón; Bottaro, Sandro; Bussi, Giovanni

    2018-02-28

    We introduce the SPlit-and-conQueR (SPQR) model, a coarse-grained (CG) representation of RNA designed for structure prediction and refinement. In our approach, the representation of a nucleotide consists of a point particle for the phosphate group and an anisotropic particle for the nucleoside. The interactions are, in principle, knowledge-based potentials inspired by the $\\mathcal {E}$SCORE function, a base-centered scoring function. However, a special treatment is given to base-pairing interactions and certain geometrical conformations which are lost in a raw knowledge-based model. This results in a representation able to describe planar canonical and non-canonical base pairs and base-phosphate interactions and to distinguish sugar puckers and glycosidic torsion conformations. The model is applied to the folding of several structures, including duplexes with internal loops of non-canonical base pairs, tetraloops, junctions and a pseudoknot. For the majority of these systems, experimental structures are correctly predicted at the level of individual contacts. We also propose a method for efficiently reintroducing atomistic detail from the CG representation.

  5. Avian reovirus L2 genome segment sequences and predicted structure/function of the encoded RNA-dependent RNA polymerase protein

    Xu Wanhong

    2008-12-01

    Full Text Available Abstract Background The orthoreoviruses are infectious agents that possess a genome comprised of 10 double-stranded RNA segments encased in two concentric protein capsids. Like virtually all RNA viruses, an RNA-dependent RNA polymerase (RdRp enzyme is required for viral propagation. RdRp sequences have been determined for the prototype mammalian orthoreoviruses and for several other closely-related reoviruses, including aquareoviruses, but have not yet been reported for any avian orthoreoviruses. Results We determined the L2 genome segment nucleotide sequences, which encode the RdRp proteins, of two different avian reoviruses, strains ARV138 and ARV176 in order to define conserved and variable regions within reovirus RdRp proteins and to better delineate structure/function of this important enzyme. The ARV138 L2 genome segment was 3829 base pairs long, whereas the ARV176 L2 segment was 3830 nucleotides long. Both segments were predicted to encode λB RdRp proteins 1259 amino acids in length. Alignments of these newly-determined ARV genome segments, and their corresponding proteins, were performed with all currently available homologous mammalian reovirus (MRV and aquareovirus (AqRV genome segment and protein sequences. There was ~55% amino acid identity between ARV λB and MRV λ3 proteins, making the RdRp protein the most highly conserved of currently known orthoreovirus proteins, and there was ~28% identity between ARV λB and homologous MRV and AqRV RdRp proteins. Predictive structure/function mapping of identical and conserved residues within the known MRV λ3 atomic structure indicated most identical amino acids and conservative substitutions were located near and within predicted catalytic domains and lining RdRp channels, whereas non-identical amino acids were generally located on the molecule's surfaces. Conclusion The ARV λB and MRV λ3 proteins showed the highest ARV:MRV identity values (~55% amongst all currently known ARV and MRV

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

    Michaeli Shulamit

    2007-10-01

    Full Text Available Abstract Background 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. Results 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. Conclusion 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.

  7. A range of complex probabilistic models for RNA secondary structure prediction that includes the nearest-neighbor model and more.

    Rivas, Elena; Lang, Raymond; Eddy, Sean R

    2012-02-01

    The standard approach for single-sequence RNA secondary structure prediction uses a nearest-neighbor thermodynamic model with several thousand experimentally determined energy parameters. An attractive alternative is to use statistical approaches with parameters estimated from growing databases of structural RNAs. Good results have been reported for discriminative statistical methods using complex nearest-neighbor models, including CONTRAfold, Simfold, and ContextFold. Little work has been reported on generative probabilistic models (stochastic context-free grammars [SCFGs]) of comparable complexity, although probabilistic models are generally easier to train and to use. To explore a range of probabilistic models of increasing complexity, and to directly compare probabilistic, thermodynamic, and discriminative approaches, we created TORNADO, a computational tool that can parse a wide spectrum of RNA grammar architectures (including the standard nearest-neighbor model and more) using a generalized super-grammar that can be parameterized with probabilities, energies, or arbitrary scores. By using TORNADO, we find that probabilistic nearest-neighbor models perform comparably to (but not significantly better than) discriminative methods. We find that complex statistical models are prone to overfitting RNA structure and that evaluations should use structurally nonhomologous training and test data sets. Overfitting has affected at least one published method (ContextFold). The most important barrier to improving statistical approaches for RNA secondary structure prediction is the lack of diversity of well-curated single-sequence RNA secondary structures in current RNA databases.

  8. RAJA Performance Suite

    2017-09-01

    The RAJA Performance Suite is designed to evaluate performance of the RAJA performance portability library on a wide variety of important high performance computing (HPC) algorithmic lulmels. These kernels assess compiler optimizations and various parallel programming model backends accessible through RAJA, such as OpenMP, CUDA, etc. The Initial version of the suite contains 25 computational kernels, each of which appears in 6 variants: Baseline SequcntiaJ, RAJA SequentiaJ, Baseline OpenMP, RAJA OpenMP, Baseline CUDA, RAJA CUDA. All variants of each kernel perform essentially the same mathematical operations and the loop body code for each kernel is identical across all variants. There are a few kernels, such as those that contain reduction operations, that require CUDA-specific coding for their CUDA variants. ActuaJ computer instructions executed and how they run in parallel differs depending on the parallel programming model backend used and which optimizations are perfonned by the compiler used to build the Perfonnance Suite executable. The Suite will be used primarily by RAJA developers to perform regular assessments of RAJA performance across a range of hardware platforms and compilers as RAJA features are being developed. It will also be used by LLNL hardware and software vendor panners for new defining requirements for future computing platform procurements and acceptance testing. In particular, the RAJA Performance Suite will be used for compiler acceptance testing of the upcoming CORAUSierra machine {initial LLNL delivery expected in late-2017/early 2018) and the CORAL-2 procurement. The Suite will aJso be used to generate concise source code reproducers of compiler and runtime issues we uncover so that we may provide them to relevant vendors to be fixed.

  9. Early second-trimester serum miRNA profiling predicts gestational diabetes mellitus.

    Chun Zhao

    Full Text Available BACKGROUND: Gestational diabetes mellitus (GDM is one type of diabetes that presents during pregnancy and significantly increases the risk of a number of adverse consequences for the fetus and mother. The microRNAs (miRNA have recently been demonstrated to abundantly and stably exist in serum and to be potentially disease-specific. However, no reported study investigates the associations between serum miRNA and GDM. METHODOLOGY/PRINCIPAL FINDINGS: We systematically used the TaqMan Low Density Array followed by individual quantitative reverse transcription polymerase chain reaction assays to screen miRNAs in serum collected at 16-19 gestational weeks. The expression levels of three miRNAs (miR-132, miR-29a and miR-222 were significantly decreased in GDM women with respect to the controls in similar gestational weeks in our discovery evaluation and internal validation, and two miRNAs (miR-29a and miR-222 were also consistently validated in two-centric external validation sample sets. In addition, the knockdown of miR-29a could increase Insulin-induced gene 1 (Insig1 expression level and subsequently the level of Phosphoenolpyruvate Carboxy Kinase2 (PCK2 in HepG2 cell lines. CONCLUSIONS/SIGNIFICANCE: Serum miRNAs are differentially expressed between GDM women and controls and could be candidate biomarkers for predicting GDM. The utility of miR-29a, miR-222 and miR-132 as serum-based non-invasive biomarkers warrants further evaluation and optimization.

  10. Predicted RNA Binding Proteins Pes4 and Mip6 Regulate mRNA Levels, Translation, and Localization during Sporulation in Budding Yeast.

    Jin, Liang; Zhang, Kai; Sternglanz, Rolf; Neiman, Aaron M

    2017-05-01

    In response to starvation, diploid cells of Saccharomyces cerevisiae undergo meiosis and form haploid spores, a process collectively referred to as sporulation. The differentiation into spores requires extensive changes in gene expression. The transcriptional activator Ndt80 is a central regulator of this process, which controls many genes essential for sporulation. Ndt80 induces ∼300 genes coordinately during meiotic prophase, but different mRNAs within the NDT80 regulon are translated at different times during sporulation. The protein kinase Ime2 and RNA binding protein Rim4 are general regulators of meiotic translational delay, but how differential timing of individual transcripts is achieved was not known. This report describes the characterization of two related NDT80 -induced genes, PES4 and MIP6 , encoding predicted RNA binding proteins. These genes are necessary to regulate the steady-state expression, translational timing, and localization of a set of mRNAs that are transcribed by NDT80 but not translated until the end of meiosis II. Mutations in the predicted RNA binding domains within PES4 alter the stability of target mRNAs. PES4 and MIP6 affect only a small portion of the NDT80 regulon, indicating that they act as modulators of the general Ime2/Rim4 pathway for specific transcripts. Copyright © 2017 American Society for Microbiology.

  11. A framework for establishing predictive relationships between specific bacterial 16S rRNA sequence abundances and biotransformation rates.

    Helbling, Damian E; Johnson, David R; Lee, Tae Kwon; Scheidegger, Andreas; Fenner, Kathrin

    2015-03-01

    The rates at which wastewater treatment plant (WWTP) microbial communities biotransform specific substrates can differ by orders of magnitude among WWTP communities. Differences in taxonomic compositions among WWTP communities may predict differences in the rates of some types of biotransformations. In this work, we present a novel framework for establishing predictive relationships between specific bacterial 16S rRNA sequence abundances and biotransformation rates. We selected ten WWTPs with substantial variation in their environmental and operational metrics and measured the in situ ammonia biotransformation rate constants in nine of them. We isolated total RNA from samples from each WWTP and analyzed 16S rRNA sequence reads. We then developed multivariate models between the measured abundances of specific bacterial 16S rRNA sequence reads and the ammonia biotransformation rate constants. We constructed model scenarios that systematically explored the effects of model regularization, model linearity and non-linearity, and aggregation of 16S rRNA sequences into operational taxonomic units (OTUs) as a function of sequence dissimilarity threshold (SDT). A large percentage (greater than 80%) of model scenarios resulted in well-performing and significant models at intermediate SDTs of 0.13-0.14 and 0.26. The 16S rRNA sequences consistently selected into the well-performing and significant models at those SDTs were classified as Nitrosomonas and Nitrospira groups. We then extend the framework by applying it to the biotransformation rate constants of ten micropollutants measured in batch reactors seeded with the ten WWTP communities. We identified phylogenetic groups that were robustly selected into all well-performing and significant models constructed with biotransformation rates of isoproturon, propachlor, ranitidine, and venlafaxine. These phylogenetic groups can be used as predictive biomarkers of WWTP microbial community activity towards these specific

  12. Integration of Known DNA, RNA and Protein Biomarkers Provides Prediction of Anti-TNF Response in Rheumatoid Arthritis

    Folkersen, Lasse; Brynedal, Boel; Marcela Diaz-Gallo, Lina

    2016-01-01

    OBJECTIVE: In rheumatoid arthritis (RA) several recent efforts have sought to discover means of predicting which patients would benefit from treatment. However, results have been discrepant with few successful replications. Our objective was to build a biobank with DNA, RNA and protein measuremen...

  13. Early changes of placenta-derived messenger RNA in maternal plasma – potential value for preeclampsia prediction?

    Surugiu Sebastian

    2015-12-01

    Full Text Available Objective: the pourpose of the study was to determine if there are any differences between placenta derived plasmatic levels of messenger RNA in normal and future preeclamptic pregnancies and if these placental transcripts can predict preeclampsia long before clinical onset

  14. A novel method of predicting microRNA-disease associations based on microRNA, disease, gene and environment factor networks.

    Peng, Wei; Lan, Wei; Zhong, Jiancheng; Wang, Jianxin; Pan, Yi

    2017-07-15

    MicroRNAs have been reported to have close relationship with diseases due to their deregulation of the expression of target mRNAs. Detecting disease-related microRNAs is helpful for disease therapies. With the development of high throughput experimental techniques, a large number of microRNAs have been sequenced. However, it is still a big challenge to identify which microRNAs are related to diseases. Recently, researchers are interesting in combining multiple-biological information to identify the associations between microRNAs and diseases. In this work, we have proposed a novel method to predict the microRNA-disease associations based on four biological properties. They are microRNA, disease, gene and environment factor. Compared with previous methods, our method makes predictions not only by using the prior knowledge of associations among microRNAs, disease, environment factors and genes, but also by using the internal relationship among these biological properties. We constructed four biological networks based on the similarity of microRNAs, diseases, environment factors and genes, respectively. Then random walking was implemented on the four networks unequally. In the walking course, the associations can be inferred from the neighbors in the same networks. Meanwhile the association information can be transferred from one network to another. The results of experiment showed that our method achieved better prediction performance than other existing state-of-the-art methods. Copyright © 2017 Elsevier Inc. All rights reserved.

  15. Serum microRNA-122 predicts survival in patients with liver cirrhosis.

    Oliver Waidmann

    Full Text Available BACKGROUND: Liver cirrhosis is associated with high morbidity and mortality. MicroRNAs (miRs circulating in the blood are an emerging new class of biomarkers. In particular, the serum level of the liver-specific miR-122 might be a clinically useful new parameter in patients with acute or chronic liver disease. AIM: Here we investigated if the serum level of miR-122 might be a prognostic parameter in patients with liver cirrhosis. METHODS: 107 patients with liver cirrhosis in the test cohort and 143 patients in the validation cohort were prospectively enrolled into the present study. RNA was extracted from the sera obtained at the time of study enrollment and the level of miR-122 was assessed. Serum miR-122 levels were assessed by quantitative reverse-transcription PCR (RT-PCR and were compared to overall survival time and to different complications of liver cirrhosis. RESULTS: Serum miR-122 levels were reduced in patients with hepatic decompensation in comparison to patients with compensated liver disease. Patients with ascites, spontaneous bacterial peritonitis and hepatorenal syndrome had significantly lower miR-122 levels than patients without these complications. Multivariate Cox regression analysis revealed that the miR-122 serum levels were associated with survival independently from the MELD score, sex and age. CONCLUSIONS: Serum miR-122 is a new independent marker for prediction of survival of patients with liver cirrhosis.

  16. Prognostic and predictive roles of microRNA-383 in colorectal cancer

    Alavieh Fateh

    2016-08-01

    Full Text Available MicroRNAs (miRNAs are impressive regulators of gene expression that have a critical role in the pathogenesis of colorectal cancer (CRC. With respect to the aberrant expression of miRNA-383 (miR-383 in some types of human malignancy, this prospective study characterized its contribution to CRC tumorigenesis. The real-time reverse transcriptionpolymerase chain reaction was used to examine miR-383 expression levels prospectively in 40 sample pairs of CRC tissues and adjacent noncancerous tissues (>2 cm from cancer tissue. No significant relationship was found between miR-383 expression levels and clinicopathological features. The ability of miR-383 to function as a tumor marker was also examined. Showing significant changes overall, miR-383 expression levels were significantly down regulated in the group of CRC samples compared with matched noncancerous tissue samples. A receiver-operating characteristic (ROC curve also showed ROC area of 70% for miR-383 with 68 and 75% sensitivity and specificity, respectively. Therefore, miR-383 can be considered as a tumor marker in CRC and help as a potential predictive biomarker in the diagnosis of colorectal cancer.

  17. Assessment of the APCC Coupled MME Suite in Predicting the Distinctive Climate Impacts of Two Flavors of ENSO during Boreal Winter

    Jeong, Hye-In; Lee, Doo Young; Karumuri, Ashok; Ahn, Joong-Bae; Lee, June-Yi; Luo, Jing-Jia; Schemm, Jae-Kyung E.; Hendon, Harry H.; Braganza, Karl; Ham, Yoo-Geun

    2012-01-01

    Forecast skill of the APEC Climate Center (APCC) Multi-Model Ensemble (MME) seasonal forecast system in predicting two main types of El Nino-Southern Oscillation (ENSO), namely canonical (or cold tongue) and Modoki ENSO, and their regional climate impacts is assessed for boreal winter. The APCC MME is constructed by simple composite of ensemble forecasts from five independent coupled ocean-atmosphere climate models. Based on a hindcast set targeting boreal winter prediction for the period 19822004, we show that the MME can predict and discern the important differences in the patterns of tropical Pacific sea surface temperature anomaly between the canonical and Modoki ENSO one and four month ahead. Importantly, the four month lead MME beats the persistent forecast. The MME reasonably predicts the distinct impacts of the canonical ENSO, including the strong winter monsoon rainfall over East Asia, the below normal rainfall and above normal temperature over Australia, the anomalously wet conditions across the south and cold conditions over the whole area of USA, and the anomalously dry conditions over South America. However, there are some limitations in capturing its regional impacts, especially, over Australasia and tropical South America at a lead time of one and four months. Nonetheless, forecast skills for rainfall and temperature over East Asia and North America during ENSO Modoki are comparable to or slightly higher than those during canonical ENSO events.

  18. Cell-free placental mRNA in maternal plasma to predict placental invasion in patients with placenta accreta.

    El Behery, Manal M; Rasha L, Etewa; El Alfy, Yehya

    2010-04-01

    To evaluate whether measuring cell-free placental mRNA in maternal plasma improves the diagnostic accuracy of ultrasound and color Doppler in detecting placental invasion in patients at risk for placenta accreta. Thirty-five singleton pregnant women of more than 28 weeks of gestation and at risk for placenta accreta underwent ultrasound and color Doppler assessment. Cell-free placental mRNA in maternal plasma was measured using real-time reverse-transcription polymerase chain reaction. Patients were classified into 2 groups based on the findings at cesarean delivery and histological examination: women with placenta accreta (n=7) and women without placenta accreta (n=28). The median MoM (multiples of the median) value of cell-free placental mRNA was significantly higher in patients with placenta accreta than in those without placenta accreta (6.50 vs 2.60; Pplacental mRNA was significantly elevated in patients with placenta increta and percreta than in those with simple accreta. Six false-positive results were found on ultrasound, all from patients without placenta accreta and an insignificant rise in cell-free placental mRNA levels. Measuring cell-free placental mRNA in maternal plasma may increase the accuracy of ultrasound and color Doppler in prenatal prediction of placental invasion in patients with suspected placenta accreta. Copyright 2009 International Federation of Gynecology and Obstetrics. Published by Elsevier Ireland Ltd. All rights reserved.

  19. Evaluating Methods for Isolating Total RNA and Predicting the Success of Sequencing Phylogenetically Diverse Plant Transcriptomes

    Bruskiewich, Richard; Burris, Jason N.; Carrigan, Charlotte T.; Chase, Mark W.; Clarke, Neil D.; Covshoff, Sarah; dePamphilis, Claude W.; Edger, Patrick P.; Goh, Falicia; Graham, Sean; Greiner, Stephan; Hibberd, Julian M.; Jordon-Thaden, Ingrid; Kutchan, Toni M.; Leebens-Mack, James; Melkonian, Michael; Miles, Nicholas; Myburg, Henrietta; Patterson, Jordan; Pires, J. Chris; Ralph, Paula; Rolf, Megan; Sage, Rowan F.; Soltis, Douglas; Soltis, Pamela; Stevenson, Dennis; Stewart, C. Neal; Surek, Barbara; Thomsen, Christina J. M.; Villarreal, Juan Carlos; Wu, Xiaolei; Zhang, Yong; Deyholos, Michael K.; Wong, Gane Ka-Shu

    2012-01-01

    Next-generation sequencing plays a central role in the characterization and quantification of transcriptomes. Although numerous metrics are purported to quantify the quality of RNA, there have been no large-scale empirical evaluations of the major determinants of sequencing success. We used a combination of existing and newly developed methods to isolate total RNA from 1115 samples from 695 plant species in 324 families, which represents >900 million years of phylogenetic diversity from green algae through flowering plants, including many plants of economic importance. We then sequenced 629 of these samples on Illumina GAIIx and HiSeq platforms and performed a large comparative analysis to identify predictors of RNA quality and the diversity of putative genes (scaffolds) expressed within samples. Tissue types (e.g., leaf vs. flower) varied in RNA quality, sequencing depth and the number of scaffolds. Tissue age also influenced RNA quality but not the number of scaffolds ≥1000 bp. Overall, 36% of the variation in the number of scaffolds was explained by metrics of RNA integrity (RIN score), RNA purity (OD 260/230), sequencing platform (GAIIx vs HiSeq) and the amount of total RNA used for sequencing. However, our results show that the most commonly used measures of RNA quality (e.g., RIN) are weak predictors of the number of scaffolds because Illumina sequencing is robust to variation in RNA quality. These results provide novel insight into the methods that are most important in isolating high quality RNA for sequencing and assembling plant transcriptomes. The methods and recommendations provided here could increase the efficiency and decrease the cost of RNA sequencing for individual labs and genome centers. PMID:23185583

  20. Sequence-Based Prediction of RNA-Binding Proteins Using Random Forest with Minimum Redundancy Maximum Relevance Feature Selection

    Xin Ma

    2015-01-01

    Full Text Available The prediction of RNA-binding proteins is one of the most challenging problems in computation biology. Although some studies have investigated this problem, the accuracy of prediction is still not sufficient. In this study, a highly accurate method was developed to predict RNA-binding proteins from amino acid sequences using random forests with the minimum redundancy maximum relevance (mRMR method, followed by incremental feature selection (IFS. We incorporated features of conjoint triad features and three novel features: binding propensity (BP, nonbinding propensity (NBP, and evolutionary information combined with physicochemical properties (EIPP. The results showed that these novel features have important roles in improving the performance of the predictor. Using the mRMR-IFS method, our predictor achieved the best performance (86.62% accuracy and 0.737 Matthews correlation coefficient. High prediction accuracy and successful prediction performance suggested that our method can be a useful approach to identify RNA-binding proteins from sequence information.

  1. A Deep Learning Framework for Robust and Accurate Prediction of ncRNA-Protein Interactions Using Evolutionary Information.

    Yi, Hai-Cheng; You, Zhu-Hong; Huang, De-Shuang; Li, Xiao; Jiang, Tong-Hai; Li, Li-Ping

    2018-06-01

    The interactions between non-coding RNAs (ncRNAs) and proteins play an important role in many biological processes, and their biological functions are primarily achieved by binding with a variety of proteins. High-throughput biological techniques are used to identify protein molecules bound with specific ncRNA, but they are usually expensive and time consuming. Deep learning provides a powerful solution to computationally predict RNA-protein interactions. In this work, we propose the RPI-SAN model by using the deep-learning stacked auto-encoder network to mine the hidden high-level features from RNA and protein sequences and feed them into a random forest (RF) model to predict ncRNA binding proteins. Stacked assembling is further used to improve the accuracy of the proposed method. Four benchmark datasets, including RPI2241, RPI488, RPI1807, and NPInter v2.0, were employed for the unbiased evaluation of five established prediction tools: RPI-Pred, IPMiner, RPISeq-RF, lncPro, and RPI-SAN. The experimental results show that our RPI-SAN model achieves much better performance than other methods, with accuracies of 90.77%, 89.7%, 96.1%, and 99.33%, respectively. It is anticipated that RPI-SAN can be used as an effective computational tool for future biomedical researches and can accurately predict the potential ncRNA-protein interacted pairs, which provides reliable guidance for biological research. Copyright © 2018 The Author(s). Published by Elsevier Inc. All rights reserved.

  2. Protein-RNA interface residue prediction using machine learning: an assessment of the state of the art.

    Walia, Rasna R; Caragea, Cornelia; Lewis, Benjamin A; Towfic, Fadi; Terribilini, Michael; El-Manzalawy, Yasser; Dobbs, Drena; Honavar, Vasant

    2012-05-10

    RNA molecules play diverse functional and structural roles in cells. They function as messengers for transferring genetic information from DNA to proteins, as the primary genetic material in many viruses, as catalysts (ribozymes) important for protein synthesis and RNA processing, and as essential and ubiquitous regulators of gene expression in living organisms. Many of these functions depend on precisely orchestrated interactions between RNA molecules and specific proteins in cells. Understanding the molecular mechanisms by which proteins recognize and bind RNA is essential for comprehending the functional implications of these interactions, but the recognition 'code' that mediates interactions between proteins and RNA is not yet understood. Success in deciphering this code would dramatically impact the development of new therapeutic strategies for intervening in devastating diseases such as AIDS and cancer. Because of the high cost of experimental determination of protein-RNA interfaces, there is an increasing reliance on statistical machine learning methods for training predictors of RNA-binding residues in proteins. However, because of differences in the choice of datasets, performance measures, and data representations used, it has been difficult to obtain an accurate assessment of the current state of the art in protein-RNA interface prediction. We provide a review of published approaches for predicting RNA-binding residues in proteins and a systematic comparison and critical assessment of protein-RNA interface residue predictors trained using these approaches on three carefully curated non-redundant datasets. We directly compare two widely used machine learning algorithms (Naïve Bayes (NB) and Support Vector Machine (SVM)) using three different data representations in which features are encoded using either sequence- or structure-based windows. Our results show that (i) Sequence-based classifiers that use a position-specific scoring matrix (PSSM

  3. Transcription-factor occupancy at HOT regions quantitatively predicts RNA polymerase recruitment in five human cell lines.

    Foley, Joseph W

    2013-10-20

    BACKGROUND: High-occupancy target (HOT) regions are compact genome loci occupied by many different transcription factors (TFs). HOT regions were initially defined in invertebrate model organisms, and we here show that they are a ubiquitous feature of the human gene-regulation landscape. RESULTS: We identified HOT regions by a comprehensive analysis of ChIP-seq data from 96 DNA-associated proteins in 5 human cell lines. Most HOT regions co-localize with RNA polymerase II binding sites, but many are not near the promoters of annotated genes. At HOT promoters, TF occupancy is strongly predictive of transcription preinitiation complex recruitment and moderately predictive of initiating Pol II recruitment, but only weakly predictive of elongating Pol II and RNA transcript abundance. TF occupancy varies quantitatively within human HOT regions; we used this variation to discover novel associations between TFs. The sequence motif associated with any given TF\\'s direct DNA binding is somewhat predictive of its empirical occupancy, but a great deal of occupancy occurs at sites without the TF\\'s motif, implying indirect recruitment by another TF whose motif is present. CONCLUSIONS: Mammalian HOT regions are regulatory hubs that integrate the signals from diverse regulatory pathways to quantitatively tune the promoter for RNA polymerase II recruitment.

  4. Transcription-factor occupancy at HOT regions quantitatively predicts RNA polymerase recruitment in five human cell lines.

    Foley, Joseph W; Sidow, Arend

    2013-01-01

    BACKGROUND: High-occupancy target (HOT) regions are compact genome loci occupied by many different transcription factors (TFs). HOT regions were initially defined in invertebrate model organisms, and we here show that they are a ubiquitous feature of the human gene-regulation landscape. RESULTS: We identified HOT regions by a comprehensive analysis of ChIP-seq data from 96 DNA-associated proteins in 5 human cell lines. Most HOT regions co-localize with RNA polymerase II binding sites, but many are not near the promoters of annotated genes. At HOT promoters, TF occupancy is strongly predictive of transcription preinitiation complex recruitment and moderately predictive of initiating Pol II recruitment, but only weakly predictive of elongating Pol II and RNA transcript abundance. TF occupancy varies quantitatively within human HOT regions; we used this variation to discover novel associations between TFs. The sequence motif associated with any given TF's direct DNA binding is somewhat predictive of its empirical occupancy, but a great deal of occupancy occurs at sites without the TF's motif, implying indirect recruitment by another TF whose motif is present. CONCLUSIONS: Mammalian HOT regions are regulatory hubs that integrate the signals from diverse regulatory pathways to quantitatively tune the promoter for RNA polymerase II recruitment.

  5. Prediction of proton chemical shifts in RNA - Their use in structure refinement and validation

    Cromsigt, Jenny A.M.T.C.; Hilbers, Cees W.; Wijmenga, Sybren S.

    2001-01-01

    An analysis is presented of experimental versus calculated chemical shifts of the non-exchangeable protons for 28 RNA structures deposited in the Protein Data Bank, covering a wide range of structural building blocks. We have used existing models for ring-current and magnetic-anisotropy contributions to calculate the proton chemical shifts from the structures. Two different parameter sets were tried: (i) parameters derived by Ribas-Prado and Giessner-Prettre (GP set) [(1981) J. Mol. Struct.,76, 81-92.]; (ii) parameters derived by Case [(1995) J. Biomol. NMR, 6, 341-346]. Both sets lead to similar results. The detailed analysis was carried using the GP set. The root-mean-square-deviation between the predicted and observed chemical shifts of the complete database is 0.16 ppm with a Pearson correlation coefficient of 0.79. For protons in the usually well-defined A-helix environment these numbers are, 0.08 ppm and 0.96, respectively. As a result of this good correspondence, a reliable analysis could be made of the structural dependencies of the 1 H chemical shifts revealing their physical origin. For example, a down-field shift of either H2' or H3' or both indicates a high-syn/syn χ-angle. In an A-helix it is essentially the 5'-neighbor that affects the chemical shifts of H5, H6 and H8 protons. The H5, H6 and H8 resonances can therefore be assigned in an A-helix on the basis of their observed chemical shifts. In general, the chemical shifts were found to be quite sensitive to structural changes. We therefore propose that a comparison between calculated and observed 1 H chemical shifts is a good tool for validation and refinement of structures derived from NOEs and J-couplings

  6. Learning DHTMLX suite UI

    Geske, Eli

    2013-01-01

    A fast-paced, example-based guide to learning DHTMLX.""Learning DHTMLX Suite UI"" is for web designers who have a basic knowledge of JavaScript and who are looking for powerful tools that will give them an extra edge in their own application development. This book is also useful for experienced developers who wish to get started with DHTMLX without going through the trouble of learning its quirks through trial and error. Readers are expected to have some knowledge of JavaScript, HTML, Document Object Model, and the ability to install a local web server.

  7. A framework for multiple kernel support vector regression and its applications to siRNA efficacy prediction.

    Qiu, Shibin; Lane, Terran

    2009-01-01

    The cell defense mechanism of RNA interference has applications in gene function analysis and promising potentials in human disease therapy. To effectively silence a target gene, it is desirable to select appropriate initiator siRNA molecules having satisfactory silencing capabilities. Computational prediction for silencing efficacy of siRNAs can assist this screening process before using them in biological experiments. String kernel functions, which operate directly on the string objects representing siRNAs and target mRNAs, have been applied to support vector regression for the prediction and improved accuracy over numerical kernels in multidimensional vector spaces constructed from descriptors of siRNA design rules. To fully utilize information provided by string and numerical data, we propose to unify the two in a kernel feature space by devising a multiple kernel regression framework where a linear combination of the kernels is used. We formulate the multiple kernel learning into a quadratically constrained quadratic programming (QCQP) problem, which although yields global optimal solution, is computationally demanding and requires a commercial solver package. We further propose three heuristics based on the principle of kernel-target alignment and predictive accuracy. Empirical results demonstrate that multiple kernel regression can improve accuracy, decrease model complexity by reducing the number of support vectors, and speed up computational performance dramatically. In addition, multiple kernel regression evaluates the importance of constituent kernels, which for the siRNA efficacy prediction problem, compares the relative significance of the design rules. Finally, we give insights into the multiple kernel regression mechanism and point out possible extensions.

  8. Predictions of RNA-binding ability and aggregation propensity of proteins

    Agostini, Federico, 1985-

    2014-01-01

    RNA-binding proteins (RBPs) control the fate of a multitude of coding and non-coding transcripts. Formation of ribonucleoprotein (RNP) complexes fine-tunes regulation of post-transcriptional events and influences gene expression. Recently, it has been observed that non-canonical proteins with RNA-binding ability are enriched in structurally disordered and low-complexity regions that are generally involved in functional and dysfunctional associations. Therefore, it is possible that interaction...

  9. Clementine sensor suite

    Ledebuhr, A.G. [Lawrence Livermore National Lab., CA (United States)

    1994-11-15

    LLNL designed and built the suite of six miniaturized light-weight space-qualified sensors utilized in the Clementine mission. A major goal of the Clementine program was to demonstrate technologies originally developed for Ballistic Missile Defense Organization Programs. These sensors were modified to gather data from the moon. This overview presents each of these sensors and some preliminary on-orbit performance estimates. The basic subsystems of these sensors include optical baffles to reject off-axis stray light, light-weight ruggedized optical systems, filter wheel assemblies, radiation tolerant focal plane arrays, radiation hardened control and readout electronics and low mass and power mechanical cryogenic coolers for the infrared sensors. Descriptions of each sensor type are given along with design specifications, photographs and on-orbit data collected.

  10. HuMiTar: A sequence-based method for prediction of human microRNA targets

    Chen Ke

    2008-12-01

    Full Text Available Abstract Background MicroRNAs (miRs are small noncoding RNAs that bind to complementary/partially complementary sites in the 3' untranslated regions of target genes to regulate protein production of the target transcript and to induce mRNA degradation or mRNA cleavage. The ability to perform accurate, high-throughput identification of physiologically active miR targets would enable functional characterization of individual miRs. Current target prediction methods include traditional approaches that are based on specific base-pairing rules in the miR's seed region and implementation of cross-species conservation of the target site, and machine learning (ML methods that explore patterns that contrast true and false miR-mRNA duplexes. However, in the case of the traditional methods research shows that some seed region matches that are conserved are false positives and that some of the experimentally validated target sites are not conserved. Results We present HuMiTar, a computational method for identifying common targets of miRs, which is based on a scoring function that considers base-pairing for both seed and non-seed positions for human miR-mRNA duplexes. Our design shows that certain non-seed miR nucleotides, such as 14, 18, 13, 11, and 17, are characterized by a strong bias towards formation of Watson-Crick pairing. We contrasted HuMiTar with several representative competing methods on two sets of human miR targets and a set of ten glioblastoma oncogenes. Comparison with the two best performing traditional methods, PicTar and TargetScanS, and a representative ML method that considers the non-seed positions, NBmiRTar, shows that HuMiTar predictions include majority of the predictions of the other three methods. At the same time, the proposed method is also capable of finding more true positive targets as a trade-off for an increased number of predictions. Genome-wide predictions show that the proposed method is characterized by 1.99 signal

  11. GARN2: coarse-grained prediction of 3D structure of large RNA molecules by regret minimization.

    Boudard, Mélanie; Barth, Dominique; Bernauer, Julie; Denise, Alain; Cohen, Johanne

    2017-08-15

    Predicting the 3D structure of RNA molecules is a key feature towards predicting their functions. Methods which work at atomic or nucleotide level are not suitable for large molecules. In these cases, coarse-grained prediction methods aim to predict a shape which could be refined later by using more precise methods on smaller parts of the molecule. We developed a complete method for sampling 3D RNA structure at a coarse-grained model, taking a secondary structure as input. One of the novelties of our method is that a second step extracts two best possible structures close to the native, from a set of possible structures. Although our method benefits from the first version of GARN, some of the main features on GARN2 are very different. GARN2 is much faster than the previous version and than the well-known methods of the state-of-art. Our experiments show that GARN2 can also provide better structures than the other state-of-the-art methods. GARN2 is written in Java. It is freely distributed and available at http://garn.lri.fr/. melanie.boudard@lri.fr or johanne.cohen@lri.fr. Supplementary data are available at Bioinformatics online. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

  12. Analytical Tools for Space Suit Design

    Aitchison, Lindsay

    2011-01-01

    As indicated by the implementation of multiple small project teams within the agency, NASA is adopting a lean approach to hardware development that emphasizes quick product realization and rapid response to shifting program and agency goals. Over the past two decades, space suit design has been evolutionary in approach with emphasis on building prototypes then testing with the largest practical range of subjects possible. The results of these efforts show continuous improvement but make scaled design and performance predictions almost impossible with limited budgets and little time. Thus, in an effort to start changing the way NASA approaches space suit design and analysis, the Advanced Space Suit group has initiated the development of an integrated design and analysis tool. It is a multi-year-if not decadal-development effort that, when fully implemented, is envisioned to generate analysis of any given space suit architecture or, conversely, predictions of ideal space suit architectures given specific mission parameters. The master tool will exchange information to and from a set of five sub-tool groups in order to generate the desired output. The basic functions of each sub-tool group, the initial relationships between the sub-tools, and a comparison to state of the art software and tools are discussed.

  13. Circulating microRNA levels predict residual beta cell function and glycaemic control in children with type 1 diabetes mellitus

    Samandari, Nasim; Mirza, Aashiq H; Nielsen, Lotte B

    2017-01-01

    AIMS/HYPOTHESIS: We aimed to identify circulating microRNA (miRNA) that predicts clinical progression in a cohort of 123 children with new-onset type 1 diabetes mellitus. METHODS: Plasma samples were prospectively obtained at 1, 3, 6, 12 and 60 months after diagnosis from a subset of 40 children......RNAs revealed significant enrichment for pathways related to gonadotropin-releasing hormone receptor and angiogenesis pathways. CONCLUSIONS/INTERPRETATION: The miRNA hsa-miR-197-3p at 3 months was the strongest predictor of residual beta cell function 1 year after diagnosis in children with type 1 diabetes...... from the Danish Remission Phase Cohort, and profiled for miRNAs. At the same time points, meal-stimulated C-peptide and HbA1c levels were measured and insulin-dose adjusted HbA1c (IDAA1c) calculated. miRNAs that at 3 months after diagnosis predicted residual beta cell function and glycaemic control...

  14. Full-length RNA structure prediction of the HIV-1 genome reveals a conserved core domain

    Sükösd, Zsuzsanna; Andersen, Ebbe Sloth; Seemann, Ernst Stefan

    2015-01-01

    of the HIV-1 genome is highly variable in most regions, with a limited number of stable and conserved RNA secondary structures. Most interesting, a set of long distance interactions form a core organizing structure (COS) that organize the genome into three major structural domains. Despite overlapping...

  15. Influence of mRNA decay rates on the computational prediction of ...

    SEARCHU

    To understand the influences, we present a systematic method based on a gene dynamic ... data). The results indicate that mRNA decay rates do not significantly influence the .... For instance, k for a cubic B-spline equals 4 and the fitting.

  16. Changes in circulating microRNA-126 during treatment with chemotherapy and bevacizumab predicts treatment response in patients with metastatic colorectal cancer

    Hansen, T F; Carlsen, A L; Heegaard, N H H

    2015-01-01

    BACKGROUND: This study investigated the predictive value of circulating microRNA-126 (cir-miRNA-126) in patients with metastatic colorectal cancer (mCRC) treated with first-line chemotherapy combined with bevacizumab.METHODS: The study included 68 patients. Blood samples (plasma) were collected b...

  17. Molecular structure and thermodynamic predictions to create highly sensitive microRNA biosensors

    Larkey, Nicholas E.; Brucks, Corinne N.; Lansing, Shan S.; Le, Sophia D.; Smith, Natasha M.; Tran, Victoria; Zhang, Lulu; Burrows, Sean M.

    2016-01-01

    Many studies have established microRNAs (miRNAs) as post-transcriptional regulators in a variety of intracellular molecular processes. Abnormal changes in miRNA have been associated with several diseases. However, these changes are sometimes subtle and occur at nanomolar levels or lower. Several biosensing hurdles for in situ cellular/tissue analysis of miRNA limit detection of small amounts of miRNA. Of these limitations the most challenging are selectivity and sensor degradation creating high background signals and false signals. Recently we developed a reporter+probe biosensor for let-7a that showed potential to mitigate false signal from sensor degradation. Here we designed reporter+probe biosensors for miR-26a-2-3p and miR-27a-5p to better understand the effect of thermodynamics and molecular structures of the biosensor constituents on the analytical performance. Signal changes from interactions between Cy3 and Cy5 on the reporters were used to understand structural aspects of the reporter designs. Theoretical thermodynamic values, single stranded conformations, hetero- and homodimerization structures, and equilibrium concentrations of the reporters and probes were used to interpret the experimental observations. Studies of the sensitivity and selectivity revealed 5–9 nM detection limits in the presence and absence of interfering off-analyte miRNAs. These studies will aid in determining how to rationally design reporter+probe biosensors to overcome hurdles associated with highly sensitive miRNA biosensing. - Highlights: • Challenges facing highly sensitive miRNA biosensor designs are addressed. • Thermodynamic and molecular structure design metrics for reporter+probe biosensors are proposed. • The influence of ideal and non-ideal reporter hairpin structures on reporter+probe formation and signal change are discussed. • 5–9 nM limits of detection were observed with no interference from off-analytes.

  18. Molecular structure and thermodynamic predictions to create highly sensitive microRNA biosensors

    Larkey, Nicholas E.; Brucks, Corinne N.; Lansing, Shan S.; Le, Sophia D.; Smith, Natasha M.; Tran, Victoria; Zhang, Lulu; Burrows, Sean M., E-mail: sean.burrows@oregonstate.edu

    2016-02-25

    Many studies have established microRNAs (miRNAs) as post-transcriptional regulators in a variety of intracellular molecular processes. Abnormal changes in miRNA have been associated with several diseases. However, these changes are sometimes subtle and occur at nanomolar levels or lower. Several biosensing hurdles for in situ cellular/tissue analysis of miRNA limit detection of small amounts of miRNA. Of these limitations the most challenging are selectivity and sensor degradation creating high background signals and false signals. Recently we developed a reporter+probe biosensor for let-7a that showed potential to mitigate false signal from sensor degradation. Here we designed reporter+probe biosensors for miR-26a-2-3p and miR-27a-5p to better understand the effect of thermodynamics and molecular structures of the biosensor constituents on the analytical performance. Signal changes from interactions between Cy3 and Cy5 on the reporters were used to understand structural aspects of the reporter designs. Theoretical thermodynamic values, single stranded conformations, hetero- and homodimerization structures, and equilibrium concentrations of the reporters and probes were used to interpret the experimental observations. Studies of the sensitivity and selectivity revealed 5–9 nM detection limits in the presence and absence of interfering off-analyte miRNAs. These studies will aid in determining how to rationally design reporter+probe biosensors to overcome hurdles associated with highly sensitive miRNA biosensing. - Highlights: • Challenges facing highly sensitive miRNA biosensor designs are addressed. • Thermodynamic and molecular structure design metrics for reporter+probe biosensors are proposed. • The influence of ideal and non-ideal reporter hairpin structures on reporter+probe formation and signal change are discussed. • 5–9 nM limits of detection were observed with no interference from off-analytes.

  19. Mirnacle: machine learning with SMOTE and random forest for improving selectivity in pre-miRNA ab initio prediction.

    Marques, Yuri Bento; de Paiva Oliveira, Alcione; Ribeiro Vasconcelos, Ana Tereza; Cerqueira, Fabio Ribeiro

    2016-12-15

    MicroRNAs (miRNAs) are key gene expression regulators in plants and animals. Therefore, miRNAs are involved in several biological processes, making the study of these molecules one of the most relevant topics of molecular biology nowadays. However, characterizing miRNAs in vivo is still a complex task. As a consequence, in silico methods have been developed to predict miRNA loci. A common ab initio strategy to find miRNAs in genomic data is to search for sequences that can fold into the typical hairpin structure of miRNA precursors (pre-miRNAs). The current ab initio approaches, however, have selectivity issues, i.e., a high number of false positives is reported, which can lead to laborious and costly attempts to provide biological validation. This study presents an extension of the ab initio method miRNAFold, with the aim of improving selectivity through machine learning techniques, namely, random forest combined with the SMOTE procedure that copes with imbalance datasets. By comparing our method, termed Mirnacle, with other important approaches in the literature, we demonstrate that Mirnacle substantially improves selectivity without compromising sensitivity. For the three datasets used in our experiments, our method achieved at least 97% of sensitivity and could deliver a two-fold, 20-fold, and 6-fold increase in selectivity, respectively, compared with the best results of current computational tools. The extension of miRNAFold by the introduction of machine learning techniques, significantly increases selectivity in pre-miRNA ab initio prediction, which optimally contributes to advanced studies on miRNAs, as the need of biological validations is diminished. Hopefully, new research, such as studies of severe diseases caused by miRNA malfunction, will benefit from the proposed computational tool.

  20. TargetMiner: microRNA target prediction with systematic identification of tissue-specific negative examples.

    Bandyopadhyay, Sanghamitra; Mitra, Ramkrishna

    2009-10-15

    Prediction of microRNA (miRNA) target mRNAs using machine learning approaches is an important area of research. However, most of the methods suffer from either high false positive or false negative rates. One reason for this is the marked deficiency of negative examples or miRNA non-target pairs. Systematic identification of non-target mRNAs is still not addressed properly, and therefore, current machine learning approaches are compelled to rely on artificially generated negative examples for training. In this article, we have identified approximately 300 tissue-specific negative examples using a novel approach that involves expression profiling of both miRNAs and mRNAs, miRNA-mRNA structural interactions and seed-site conservation. The newly generated negative examples are validated with pSILAC dataset, which elucidate the fact that the identified non-targets are indeed non-targets.These high-throughput tissue-specific negative examples and a set of experimentally verified positive examples are then used to build a system called TargetMiner, a support vector machine (SVM)-based classifier. In addition to assessing the prediction accuracy on cross-validation experiments, TargetMiner has been validated with a completely independent experimental test dataset. Our method outperforms 10 existing target prediction algorithms and provides a good balance between sensitivity and specificity that is not reflected in the existing methods. We achieve a significantly higher sensitivity and specificity of 69% and 67.8% based on a pool of 90 feature set and 76.5% and 66.1% using a set of 30 selected feature set on the completely independent test dataset. In order to establish the effectiveness of the systematically generated negative examples, the SVM is trained using a different set of negative data generated using the method in Yousef et al. A significantly higher false positive rate (70.6%) is observed when tested on the independent set, while all other factors are kept the

  1. CRISPRstrand: predicting repeat orientations to determine the crRNA-encoding strand at CRISPR loci

    Alkhnbashi, Omer S.; Costa, Fabrizio; Shah, Shiraz Ali

    2014-01-01

    Motivation: The discovery of CRISPR-Cas systems almost 20 years ago rapidly changed our perception of the bacterial and archaeal immune systems. CRISPR loci consist of several repetitive DNA sequences called repeats, inter-spaced by stretches of variable length sequences called spacers. This CRISPR...... array is transcribed and processed into multiple mature RNA species (crRNAs). A single crRNA is integrated into an interference complex, together with CRISPR-associated (Cas) proteins, to bind and degrade invading nucleic acids. Although existing bioinformatics tools can recognize CRISPR loci...... by their characteristic repeat-spacer architecture, they generally output CRISPR arrays of ambiguous orientation and thus do not determine the strand from which crRNAs are processed. Knowledge of the correct orientation is crucial for many tasks, including the classification of CRISPR conservation, the detection...

  2. Covariant Evolutionary Event Analysis for Base Interaction Prediction Using a Relational Database Management System for RNA.

    Xu, Weijia; Ozer, Stuart; Gutell, Robin R

    2009-01-01

    With an increasingly large amount of sequences properly aligned, comparative sequence analysis can accurately identify not only common structures formed by standard base pairing but also new types of structural elements and constraints. However, traditional methods are too computationally expensive to perform well on large scale alignment and less effective with the sequences from diversified phylogenetic classifications. We propose a new approach that utilizes coevolutional rates among pairs of nucleotide positions using phylogenetic and evolutionary relationships of the organisms of aligned sequences. With a novel data schema to manage relevant information within a relational database, our method, implemented with a Microsoft SQL Server 2005, showed 90% sensitivity in identifying base pair interactions among 16S ribosomal RNA sequences from Bacteria, at a scale 40 times bigger and 50% better sensitivity than a previous study. The results also indicated covariation signals for a few sets of cross-strand base stacking pairs in secondary structure helices, and other subtle constraints in the RNA structure.

  3. An Algorithm for Template-Based Prediction of Secondary Structures of Individual RNA Sequences

    Pánek, Josef; Modrák, Martin; Schwarz, Marek

    2017-01-01

    Roč. 8, OCT 10 (2017), s. 1-11, č. článku 147. ISSN 1664-8021 R&D Projects: GA ČR GA15-00885S; GA MŠk(CZ) LM2015047 Institutional support: RVO:61388971 Keywords : RNA * secondary structure * homology Subject RIV: EE - Microbiology, Virology OBOR OECD: Microbiology Impact factor: 3.789, year: 2016

  4. Apparatus for storing protective suits

    Englemann, H.J.; Koller, J.; Schrader, H.R.; Schade, G.; Pedrerol, J.

    1975-01-01

    Arrangements are described for storing one or more protective suits when contaminated on the outside. In order to permit a person wearing a contaminated suit to leave a contaminated area safely, and without contaminating the environment, it has hitherto been the practice for the suit to be passed through a 'lock' and cleansed under decontaminating showers whilst still being worn. This procedure is time wasting and not always completely effective, and it may be necessary to provide a second suit for use whilst the first suit is being decontaminated. Repeated decontamination may also result in undue wear and tear. The arrangements described provide a 'lock' chamber in which a contaminated suit may be stowed away without its interior becoming contaminated, thus allowing repeated use by persons donning and shedding it. (U.K.)

  5. Bacterial vaginosis, human papilloma virus and herpes viridae do not predict vaginal HIV RNA shedding in women living with HIV in Denmark

    Wessman, Maria; Thorsteinsson, Kristina; Jensen, Jørgen S

    2017-01-01

    in the genital tract despite undetectable HIV RNA plasma viral load. We examined the prevalence and diagnostic predictors of BV and HIV-1 RNA vaginal shedding in women living with HIV (WLWH) in Denmark, taking into account the presence of human papillomavirus (HPV) and herpes viridae. METHODS: WLWH between 18......-51 years were recruited from six Departments of Infectious Diseases in Denmark during enrolment in the SHADE cohort; a prospective cohort study of WLWH attending regular outpatient care. BV was diagnosed by microscopy of vaginal swabs and PCR was used for detection of BV-associated bacteria, HPV, herpes...... RNA. Both before and after adjustment for BV, age, ethnicity, plasma HIV RNA, CD4 cell count, herpes viridae and HPV, we found no significant predictors of HIV RNA vaginal shedding. CONCLUSION: In well-treated WLWH, BV, herpes viridae or HPV do not predict vaginal HIV RNA shedding. This implies...

  6. PlantRNA_Sniffer: A SVM-Based Workflow to Predict Long Intergenic Non-Coding RNAs in Plants.

    Vieira, Lucas Maciel; Grativol, Clicia; Thiebaut, Flavia; Carvalho, Thais G; Hardoim, Pablo R; Hemerly, Adriana; Lifschitz, Sergio; Ferreira, Paulo Cavalcanti Gomes; Walter, Maria Emilia M T

    2017-03-04

    Non-coding RNAs (ncRNAs) constitute an important set of transcripts produced in the cells of organisms. Among them, there is a large amount of a particular class of long ncRNAs that are difficult to predict, the so-called long intergenic ncRNAs (lincRNAs), which might play essential roles in gene regulation and other cellular processes. Despite the importance of these lincRNAs, there is still a lack of biological knowledge and, currently, the few computational methods considered are so specific that they cannot be successfully applied to other species different from those that they have been originally designed to. Prediction of lncRNAs have been performed with machine learning techniques. Particularly, for lincRNA prediction, supervised learning methods have been explored in recent literature. As far as we know, there are no methods nor workflows specially designed to predict lincRNAs in plants. In this context, this work proposes a workflow to predict lincRNAs on plants, considering a workflow that includes known bioinformatics tools together with machine learning techniques, here a support vector machine (SVM). We discuss two case studies that allowed to identify novel lincRNAs, in sugarcane ( Saccharum spp.) and in maize ( Zea mays ). From the results, we also could identify differentially-expressed lincRNAs in sugarcane and maize plants submitted to pathogenic and beneficial microorganisms.

  7. PlantRNA_Sniffer: A SVM-Based Workflow to Predict Long Intergenic Non-Coding RNAs in Plants

    Lucas Maciel Vieira

    2017-03-01

    Full Text Available Non-coding RNAs (ncRNAs constitute an important set of transcripts produced in the cells of organisms. Among them, there is a large amount of a particular class of long ncRNAs that are difficult to predict, the so-called long intergenic ncRNAs (lincRNAs, which might play essential roles in gene regulation and other cellular processes. Despite the importance of these lincRNAs, there is still a lack of biological knowledge and, currently, the few computational methods considered are so specific that they cannot be successfully applied to other species different from those that they have been originally designed to. Prediction of lncRNAs have been performed with machine learning techniques. Particularly, for lincRNA prediction, supervised learning methods have been explored in recent literature. As far as we know, there are no methods nor workflows specially designed to predict lincRNAs in plants. In this context, this work proposes a workflow to predict lincRNAs on plants, considering a workflow that includes known bioinformatics tools together with machine learning techniques, here a support vector machine (SVM. We discuss two case studies that allowed to identify novel lincRNAs, in sugarcane (Saccharum spp. and in maize (Zea mays. From the results, we also could identify differentially-expressed lincRNAs in sugarcane and maize plants submitted to pathogenic and beneficial microorganisms.

  8. A 4-miRNA signature to predict survival in glioblastomas

    Hermansen, Simon K; Sørensen, Mia D; Hansen, Anker

    2017-01-01

    multiple genes representing an additional level of gene regulation possibly more prognostically powerful than a single gene. The aim of the study was to identify a novel miRNA signature with the ability to separate patients into prognostic subgroups. Samples from 40 glioblastoma patients were included...... association to survival in univariate (HR 8.50; 95% CI 3.06-23.62; psignature of miR-107 and miR-331 (miR sum score), which were the only miRNAs available...

  9. Structural modeling of tissue-specific mitochondrial alanyl-tRNA synthetase (AARS2 defects predicts differential effects on aminoacylation

    Liliya eEuro

    2015-02-01

    Full Text Available The accuracy of mitochondrial protein synthesis is dependent on the coordinated action of nuclear-encoded mitochondrial aminoacyl-tRNA synthetases (mtARSs and the mitochondrial DNA-encoded tRNAs. The recent advances in whole-exome sequencing have revealed the importance of the mtARS proteins for mitochondrial pathophysiology since nearly every nuclear gene for mtARS (out of 19 is now recognized as a disease gene for mitochondrial disease. Typically, defects in each mtARS have been identified in one tissue-specific disease, most commonly affecting the brain, or in one syndrome. However, mutations in the AARS2 gene for mitochondrial alanyl-tRNA synthetase (mtAlaRS have been reported both in patients with infantile-onset cardiomyopathy and in patients with childhood to adulthood-onset leukoencephalopathy. We present here an investigation of the effects of the described mutations on the structure of the synthetase, in an effort to understand the tissue-specific outcomes of the different mutations.The mtAlaRS differs from the other mtARSs because in addition to the aminoacylation domain, it has a conserved editing domain for deacylating tRNAs that have been mischarged with incorrect amino acids. We show that the cardiomyopathy phenotype results from a single allele, causing an amino acid change p.R592W in the editing domain of AARS2, whereas the leukodystrophy mutations are located in other domains of the synthetase. Nevertheless, our structural analysis predicts that all mutations reduce the aminoacylation activity of the synthetase, because all mtAlaRS domains contribute to tRNA binding for aminoacylation. According to our model, the cardiomyopathy mutations severely compromise aminoacylation whereas partial activity is retained by the mutation combinations found in the leukodystrophy patients. These predictions provide a hypothesis for the molecular basis of the distinct tissue-specific phenotypic outcomes.

  10. Isolation of a hyperthermophilic archaeum predicted by in situ RNA analysis.

    Huber, R; Burggraf, S; Mayer, T; Barns, S M; Rossnagel, P; Stetter, K O

    1995-07-06

    A variety of hyperthermophilic bacteria and archaea have been isolated from high-temperature environments by plating and serial dilutions. However, these techniques allow only the small percentage of organisms able to form colonies, or those that are predominant within environmental samples, to be obtained in pure culture. Recently, in situ 16S ribosomal RNA analyses of samples from the Obsidian hot pool at Yellowstone National Park, Wyoming, revealed a variety of archaeal sequences, which were all different from those of previously isolated species. This suggests substantial diversity of archaea with so far unknown morphological, physiological and biochemical features, which may play an important part within high-temperature ecosystems. Here we describe a procedure to obtain pure cultures of unknown organisms harbouring specific 16S rRNA sequences identified previously within the environment. It combines visual recognition of single cells by phylogenetic staining and cloning by 'optical tweezers'. Our result validates polymerase chain reaction data on the existence of large archael communities.

  11. Ciculating miRNA-21 as a Biomarker Predicts Polycystic Ovary Syndrome (PCOS) in Patients.

    Jiang, Liyan; Li, Wei; Wu, Minmin; Cao, Sifan

    2015-01-01

    Polycystic ovary syndrome (PCOS) is characterized by hyperandrogenism, hyperinsulinemia, and infertility. In PCOS, abnormal regulation of relevant genes is required for follicular development. By binding to the 3' untranslated region (3'URT), microRNAs (miRNAs) are widely involved in posttranscriptional gene regulation. However, few studies have been conducted on circulating miRNA expression in PCOS. This study aims to describe altered expression of circulating miR-21 in PCOS. The expression of serum miRNAs of PCOS patients were explored using the TaqMan Low Density Array followed by individual quantitative reverse transcription polymerase chain reaction assays. The protein level of LATS1 was determined using Western blot. To validate whether miR-21 targeted LATS1, the luciferase assay was applied. In comparison with normal subjects, the circulating level of miRNA-21 was significantly enhanced in PCOS patients. In PCOS patients, the expression levels of MST1/2, LATS1/2, TAZ were much lower than the control subjects. Luciferase reporter assay revealed that LATS1 was a downstream target of miR-21. In comparison with normal subjects, serum miR-21 is obviously increased in PCOS patients. Through targeting LATS1, miR-21 could prompt PCOS progression and could act as a novel non-invasive biomarker for diagnosis of PCOS.

  12. Divergent homologs of the predicted small RNA BpCand697 in Burkholderia spp.

    Damiri, Nadzirah; Mohd-Padil, Hirzahida; Firdaus-Raih, Mohd

    2015-09-01

    The small RNA (sRNA) gene candidate, BpCand697 was previously reported to be unique to Burkholderia spp. and is encoded at 3' non-coding region of a putative AraC family transcription regulator gene. This study demonstrates the conservation of BpCand697 sequence across 32 Burkholderia spp. including B. pseudomallei, B. mallei, B. thailandensis and Burkholderia sp. by integrating both sequence homology and secondary structural analyses of BpCand697 within the dataset. The divergent sequence of BpCand697 was also used as a discriminatory power in clustering the dataset according to the potential virulence of Burkholderia spp., showing that B. thailandensis was clearly secluded from the virulent cluster of B. pseudomallei and B. mallei. Finally, the differential co-transcript expression of BpCand697 and its flanking gene, bpsl2391 was detected in Burkholderia pseudomallei D286 after grown under two different culture conditions using nutrient-rich and minimal media. It is hypothesized that the differential expression of BpCand697-bpsl2391 co-transcript between the two standard prepared media might correlate with nutrient availability in the culture media, suggesting that the physical co-localization of BpCand697 in B. pseudomallei D286 might be directly or indirectly involved with the transcript regulation of bpsl2391 under the selected in vitro culture conditions.

  13. An expression meta-analysis of predicted microRNA targets identifies a diagnostic signature for lung cancer

    Liang Yu

    2008-12-01

    Full Text Available Abstract Background Patients diagnosed with lung adenocarcinoma (AD and squamous cell carcinoma (SCC, two major histologic subtypes of lung cancer, currently receive similar standard treatments, but resistance to adjuvant chemotherapy is prevalent. Identification of differentially expressed genes marking AD and SCC may prove to be of diagnostic value and help unravel molecular basis of their histogenesis and biologies, and deliver more effective and specific systemic therapy. Methods MiRNA target genes were predicted by union of miRanda, TargetScan, and PicTar, followed by screening for matched gene symbols in NCBI human sequences and Gene Ontology (GO terms using the PANTHER database that was also used for analyzing the significance of biological processes and pathways within each ontology term. Microarray data were extracted from Gene Expression Omnibus repository, and tumor subtype prediction by gene expression used Prediction Analysis of Microarrays. Results Computationally predicted target genes of three microRNAs, miR-34b/34c/449, that were detected in human lung, testis, and fallopian tubes but not in other normal tissues, were filtered by representation of GO terms and their ability to classify lung cancer subtypes, followed by a meta-analysis of microarray data to classify AD and SCC. Expression of a minimal set of 17 predicted miR-34b/34c/449 target genes derived from the developmental process GO category was identified from a training set to classify 41 AD and 17 SCC, and correctly predicted in average 87% of 354 AD and 82% of 282 SCC specimens from total 9 independent published datasets. The accuracy of prediction still remains comparable when classifying 103 AD and 79 SCC samples from another 4 published datasets that have only 14 to 16 of the 17 genes available for prediction (84% and 85% for AD and SCC, respectively. Expression of this signature in two published datasets of epithelial cells obtained at bronchoscopy from cigarette

  14. Over-expression of the miRNA cluster at chromosome 14q32 in the alcoholic brain correlates with suppression of predicted target mRNA required for oligodendrocyte proliferation.

    Manzardo, A M; Gunewardena, S; Butler, M G

    2013-09-10

    We examined miRNA expression from RNA isolated from the frontal cortex (Broadman area 9) of 9 alcoholics (6 males, 3 females, mean age 48 years) and 9 matched controls using both the Affymetrix GeneChip miRNA 2.0 and Human Exon 1.0 ST Arrays to further characterize genetic influences in alcoholism and the effects of alcohol consumption on predicted target mRNA expression. A total of 12 human miRNAs were significantly up-regulated in alcohol dependent subjects (fold change≥1.5, false discovery rate (FDR)≤0.3; p<0.05) compared with controls including a cluster of 4 miRNAs (e.g., miR-377, miR-379) from the maternally expressed 14q32 chromosome region. The status of the up-regulated miRNAs was supported using the high-throughput method of exon microarrays showing decreased predicted mRNA gene target expression as anticipated from the same RNA aliquot. Predicted mRNA targets were involved in cellular adhesion (e.g., THBS2), tissue differentiation (e.g., CHN2), neuronal migration (e.g., NDE1), myelination (e.g., UGT8, CNP) and oligodendrocyte proliferation (e.g., ENPP2, SEMA4D1). Our data support an association of alcoholism with up-regulation of a cluster of miRNAs located in the genomic imprinted domain on chromosome 14q32 with their predicted gene targets involved with oligodendrocyte growth, differentiation and signaling. Copyright © 2013 Elsevier B.V. All rights reserved.

  15. AthMethPre: a web server for the prediction and query of mRNA m6A sites in Arabidopsis thaliana.

    Xiang, Shunian; Yan, Zhangming; Liu, Ke; Zhang, Yaou; Sun, Zhirong

    2016-10-18

    N 6 -Methyladenosine (m 6 A) is the most prevalent and abundant modification in mRNA that has been linked to many key biological processes. High-throughput experiments have generated m 6 A-peaks across the transcriptome of A. thaliana, but the specific methylated sites were not assigned, which impedes the understanding of m 6 A functions in plants. Therefore, computational prediction of mRNA m 6 A sites becomes emergently important. Here, we present a method to predict the m 6 A sites for A. thaliana mRNA sequence(s). To predict the m 6 A sites of an mRNA sequence, we employed the support vector machine to build a classifier using the features of the positional flanking nucleotide sequence and position-independent k-mer nucleotide spectrum. Our method achieved good performance and was applied to a web server to provide service for the prediction of A. thaliana m 6 A sites. The server also provides a comprehensive database of predicted transcriptome-wide m 6 A sites and curated m 6 A-seq peaks from the literature for query and visualization. The AthMethPre web server is the first web server that provides a user-friendly tool for the prediction and query of A. thaliana mRNA m 6 A sites, which is freely accessible for public use at .

  16. Predicted overlapping microRNA regulators of acetylcholine packaging and degradation in neuroinflammation-related disorders

    Bettina eNadorp

    2014-02-01

    Full Text Available MicroRNAs (miRNAs can notably control many targets each and regulate entire cellular pathways, but whether miRNAs can regulate complete neurotransmission processes is largely unknown. Here, we report that miRNAs with complementary sequence motifs to the key genes involved in acetylcholine (ACh synthesis and/or packaging show massive overlap with those regulating ACh degradation. To address this topic, we first searched for miRNAs that could target the 3’-untranslated regions of the choline acetyltransferase (ChAT gene that controls ACh synthesis; the vesicular ACh transporter (VAChT, encoded from an intron in the ChAT gene and the ACh hydrolyzing genes acetyl- and/or butyrylcholinesterase (AChE, BChE. Intriguingly, we found that many of the miRNAs targeting these genes are primate-specific, and that changes in their levels associate with inflammation, anxiety, brain damage, cardiac, neurodegenerative or pain-related syndromes. To validate the in vivo relevance of this dual interaction, we selected the evolutionarily conserved miR-186, which targets both the stress-inducible soluble readthrough variant AChE-R and the major peripheral cholinesterase BChE. We exposed mice to predator scent stress and searched for potential associations between consequent changes in their miR-186, AChE-R and BChE levels. Both intestinal miR-186 as well as BChE and AChE-R activities were conspicuously elevated one week post-exposure, highlighting the previously unknown involvement of miR-186 and BChE in psychological stress responses. Overlapping miRNA regulation emerges from our findings as a recently evolved surveillance mechanism over cholinergic neurotransmission in health and disease; and the corresponding miRNA details and disease relevance may serve as a useful resource for studying the molecular mechanisms underlying this surveillance.

  17. Adobe Creative Suite 4 Bible

    Padova, Ted

    2009-01-01

    As one of the few books to cover integration and workflow issues between Photoshop, Illustrator, InDesign, GoLive, Acrobat, and Version Cue, this comprehensive reference is the one book that Creative Suite users need; Two well-known and respected authors cover topics such as developing consistent color-managed workflows, moving files among the Creative Suite applications, preparing files for print or the Web, repurposing documents, and using the Creative Suite with Microsoft Office documents; More than 1,200 pages are packed with valuable advice and techniques for tackling common everyday issu

  18. Quantum-mechanical predictions of DNA and RNA ionization by energetic proton beams.

    Galassi, M E; Champion, C; Weck, P F; Rivarola, R D; Fojón, O; Hanssen, J

    2012-04-07

    Among the numerous constituents of eukaryotic cells, the DNA macromolecule is considered as the most important critical target for radiation-induced damages. However, up to now ion-induced collisions on DNA components remain scarcely approached and theoretical support is still lacking for describing the main ionizing processes. In this context, we here report a theoretical description of the proton-induced ionization of the DNA and RNA bases as well as the sugar-phosphate backbone. Two different quantum-mechanical models are proposed: the first one based on a continuum distorted wave-eikonal initial state treatment and the second perturbative one developed within the first Born approximation with correct boundary conditions (CB1). Besides, the molecular structure information of the biological targets studied here was determined by ab initio calculations with the Gaussian 09 software at the restricted Hartree-Fock level of theory with geometry optimization. Doubly, singly differential and total ionization cross sections also provided by the two models were compared for a large range of incident and ejection energies and a very good agreement was observed for all the configurations investigated. Finally, in comparison with the rare experiment, we have noted a large underestimation of the total ionization cross sections of uracil impacted by 80 keV protons,whereas a very good agreement was shown with the recently reported ionization cross sections for protons on adenine, at both the differential and the total scale.

  19. Detection of AR-V7 mRNA in whole blood may not predict the effectiveness of novel endocrine drugs for castration-resistant prostate cancer.

    Takeuchi, Takumi; Okuno, Yumiko; Hattori-Kato, Mami; Zaitsu, Masayoshi; Mikami, Koji

    2016-01-01

    A splice variant of androgen receptor (AR), AR-V7, lacks in androgen-binding portion and leads to aggressive cancer characteristics. Reverse transcription-polymerase chain reactions (PCRs) and subsequent nested PCRs for the amplification of AR-V7 and prostate-specific antigen (PSA) transcripts were done for whole blood of patients with prostate cancer and male controls. With primary reverse transcription PCRs, AR-V7 and PSA were detected in 4.5% and 4.7% of prostate cancer, respectively. With nested PCRs, AR-V7 messenger RNA (mRNA) was positive in 43.8% of castration-sensitive prostate cancer and 48.1% of castration-resistant prostate cancer (CRPC), while PSA mRNA was positive in 6.3% of castration-sensitive prostate cancer and 18.5% of CRPC. Whole-blood samples of controls showed AR-V7 mRNA expression by nested PCR. Based on multivariate analysis, expression of AR-V7 mRNA in whole blood was not significantly correlated with clinical parameters and PSA mRNA in blood, while univariate analysis showed a correlation between AR-V7 mRNA and metastasis at initial diagnosis. Detection of AR-V7 mRNA did not predict the reduction of serum PSA in patients with CRPC following abiraterone and enzalutamide administration. In conclusion, AR-V7 mRNA expression in normal hematopoietic cells may have annihilated the manifestation of aggressiveness of prostate cancer and the prediction of the effectiveness of abiraterone and enzalutamide by the assessment of AR-V7 mRNA in blood.

  20. Diagnostic value of microRNA-143 in predicting in-stent restenosis for patients with lower extremity arterial occlusive disease

    Yu, Zhi-Hai; Wang, Hai-Tao; Tu, Can

    2017-01-01

    Purpose This study was conducted to explore the diagnostic value of microRNA-143 (miRNA-143) in predicting in-stent restenosis (ISR) of lower extremity arterial occlusive disease (LEAOD). Methods From February 2012 to March 2015, 165 patients (112 males and 53 females) with LEAOD undergoing interventional treatment were enrolled in this study. Serum miRNA-143 expression was detected using quantitative real-time polymerase chain reaction (qRT-PCR). Patients were assigned into the restenosis an...

  1. EDL Sensor Suite, Phase I

    National Aeronautics and Space Administration — Optical Air Data Systems (OADS) L.L.C. proposes a LIDAR based remote measurement sensor suite capable of satisfying a significant number of the desired sensing...

  2. Satellite Ocean Heat Content Suite

    National Oceanic and Atmospheric Administration, Department of Commerce — This collection contains an operational Satellite Ocean Heat Content Suite (SOHCS) product generated by NOAA National Environmental Satellite, Data, and Information...

  3. EVA Suit Microbial Leakage Investigation

    National Aeronautics and Space Administration — The objective of this project is to collect microbial samples from various EVA suits to determine how much microbial contamination is typically released during...

  4. A Semi-Supervised Learning Algorithm for Predicting Four Types MiRNA-Disease Associations by Mutual Information in a Heterogeneous Network.

    Zhang, Xiaotian; Yin, Jian; Zhang, Xu

    2018-03-02

    Increasing evidence suggests that dysregulation of microRNAs (miRNAs) may lead to a variety of diseases. Therefore, identifying disease-related miRNAs is a crucial problem. Currently, many computational approaches have been proposed to predict binary miRNA-disease associations. In this study, in order to predict underlying miRNA-disease association types, a semi-supervised model called the network-based label propagation algorithm is proposed to infer multiple types of miRNA-disease associations (NLPMMDA) by mutual information derived from the heterogeneous network. The NLPMMDA method integrates disease semantic similarity, miRNA functional similarity, and Gaussian interaction profile kernel similarity information of miRNAs and diseases to construct a heterogeneous network. NLPMMDA is a semi-supervised model which does not require verified negative samples. Leave-one-out cross validation (LOOCV) was implemented for four known types of miRNA-disease associations and demonstrated the reliable performance of our method. Moreover, case studies of lung cancer and breast cancer confirmed effective performance of NLPMMDA to predict novel miRNA-disease associations and their association types.

  5. Space Suit Joint Torque Testing

    Valish, Dana J.

    2011-01-01

    In 2009 and early 2010, a test was performed to quantify the torque required to manipulate joints in several existing operational and prototype space suits in an effort to develop joint torque requirements appropriate for a new Constellation Program space suit system. The same test method was levied on the Constellation space suit contractors to verify that their suit design meets the requirements. However, because the original test was set up and conducted by a single test operator there was some question as to whether this method was repeatable enough to be considered a standard verification method for Constellation or other future space suits. In order to validate the method itself, a representative subset of the previous test was repeated, using the same information that would be available to space suit contractors, but set up and conducted by someone not familiar with the previous test. The resultant data was compared using graphical and statistical analysis and a variance in torque values for some of the tested joints was apparent. Potential variables that could have affected the data were identified and re-testing was conducted in an attempt to eliminate these variables. The results of the retest will be used to determine if further testing and modification is necessary before the method can be validated.

  6. Deep learning improves prediction of CRISPR-Cpf1 guide RNA activity.

    Kim, Hui Kwon; Min, Seonwoo; Song, Myungjae; Jung, Soobin; Choi, Jae Woo; Kim, Younggwang; Lee, Sangeun; Yoon, Sungroh; Kim, Hyongbum Henry

    2018-03-01

    We present two algorithms to predict the activity of AsCpf1 guide RNAs. Indel frequencies for 15,000 target sequences were used in a deep-learning framework based on a convolutional neural network to train Seq-deepCpf1. We then incorporated chromatin accessibility information to create the better-performing DeepCpf1 algorithm for cell lines for which such information is available and show that both algorithms outperform previous machine learning algorithms on our own and published data sets.

  7. Development of Power Assisting Suit

    Yamamoto, Keijiro; Ishii, Mineo; Hyodo, Kazuhito; Yoshimitsu, Toshihiro; Matsuo, Takashi

    In order to realize a wearable power assisting suit for assisting a nurse to carry a patient in her arms, the power supply and control systems of the suit have to be miniaturized, and it has to be wireless and pipeline-less. The new wearable suit consists of shoulders, arms, back, waist and legs units to be fitted on the nurse's body. The arms, waist and legs have new pneumatic rotary actuators driven directly by micro air pumps supplied by portable Ni-Cd batteries. The muscle forces are sensed by a new muscle hardness sensor utilizing a sensing tip mounted on a force sensing film device. An embedded microcomputer is used for the calculations of control signals. The new wearable suit was applied practically to a human body and a series of movement experiments that weights in the arms were held and taken up and down was performed. Each unit of the suit could transmit assisting torque directly to each joint verifying its practicability.

  8. Integrative miRNA-Gene Expression Analysis Enables Refinement of Associated Biology and Prediction of Response to Cetuximab in Head and Neck Squamous Cell Cancer

    Loris De Cecco

    2017-01-01

    Full Text Available This paper documents the process by which we, through gene and miRNA expression profiling of the same samples of head and neck squamous cell carcinomas (HNSCC and an integrative miRNA-mRNA expression analysis, were able to identify candidate biomarkers of progression-free survival (PFS in patients treated with cetuximab-based approaches. Through sparse partial least square–discriminant analysis (sPLS-DA and supervised analysis, 36 miRNAs were identified in two components that clearly separated long- and short-PFS patients. Gene set enrichment analysis identified a significant correlation between the miRNA first-component and EGFR signaling, keratinocyte differentiation, and p53. Another significant correlation was identified between the second component and RAS, NOTCH, immune/inflammatory response, epithelial–mesenchymal transition (EMT, and angiogenesis pathways. Regularized canonical correlation analysis of sPLS-DA miRNA and gene data combined with the MAGIA2 web-tool highlighted 16 miRNAs and 84 genes that were interconnected in a total of 245 interactions. After feature selection by a smoothed t-statistic support vector machine, we identified three miRNAs and five genes in the miRNA-gene network whose expression result was the most relevant in predicting PFS (Area Under the Curve, AUC = 0.992. Overall, using a well-defined clinical setting and up-to-date bioinformatics tools, we are able to give the proof of principle that an integrative miRNA-mRNA expression could greatly contribute to the refinement of the biology behind a predictive model.

  9. RNA-sequence data normalization through in silico prediction of reference genes: the bacterial response to DNA damage as case study.

    Berghoff, Bork A; Karlsson, Torgny; Källman, Thomas; Wagner, E Gerhart H; Grabherr, Manfred G

    2017-01-01

    Measuring how gene expression changes in the course of an experiment assesses how an organism responds on a molecular level. Sequencing of RNA molecules, and their subsequent quantification, aims to assess global gene expression changes on the RNA level (transcriptome). While advances in high-throughput RNA-sequencing (RNA-seq) technologies allow for inexpensive data generation, accurate post-processing and normalization across samples is required to eliminate any systematic noise introduced by the biochemical and/or technical processes. Existing methods thus either normalize on selected known reference genes that are invariant in expression across the experiment, assume that the majority of genes are invariant, or that the effects of up- and down-regulated genes cancel each other out during the normalization. Here, we present a novel method, moose 2 , which predicts invariant genes in silico through a dynamic programming (DP) scheme and applies a quadratic normalization based on this subset. The method allows for specifying a set of known or experimentally validated invariant genes, which guides the DP. We experimentally verified the predictions of this method in the bacterium Escherichia coli , and show how moose 2 is able to (i) estimate the expression value distances between RNA-seq samples, (ii) reduce the variation of expression values across all samples, and (iii) to subsequently reveal new functional groups of genes during the late stages of DNA damage. We further applied the method to three eukaryotic data sets, on which its performance compares favourably to other methods. The software is implemented in C++ and is publicly available from http://grabherr.github.io/moose2/. The proposed RNA-seq normalization method, moose 2 , is a valuable alternative to existing methods, with two major advantages: (i) in silico prediction of invariant genes provides a list of potential reference genes for downstream analyses, and (ii) non-linear artefacts in RNA-seq data

  10. Suited Contingency Ops Food - 2

    Glass, J. W.; Leong, M. L.; Douglas, G. L.

    2014-01-01

    The contingency scenario for an emergency cabin depressurization event may require crewmembers to subsist in a pressurized suit for up to 144 hours. This scenario requires the capability for safe nutrition delivery through a helmet feed port against a 4 psi pressure differential to enable crewmembers to maintain strength and cognition to perform critical tasks. Two nutritional delivery prototypes were developed and analyzed for compatibility with the helmet feed port interface and for operational effectiveness against the pressure differential. The bag-in-bag (BiB) prototype, designed to equalize the suit pressure with the beverage pouch and enable a crewmember to drink normally, delivered water successfully to three different subjects in suits pressurized to 4 psi. The Boa restrainer pouch, designed to provide mechanical leverage to overcome the pressure differential, did not operate sufficiently. Guidelines were developed and compiled for contingency beverages that provide macro-nutritional requirements, a minimum one-year shelf life, and compatibility with the delivery hardware. Evaluation results and food product parameters have the potential to be used to improve future prototype designs and develop complete nutritional beverages for contingency events. These feeding capabilities would have additional use on extended surface mission EVAs, where the current in-suit drinking device may be insufficient.

  11. The ZPIC educational code suite

    Calado, R.; Pardal, M.; Ninhos, P.; Helm, A.; Mori, W. B.; Decyk, V. K.; Vieira, J.; Silva, L. O.; Fonseca, R. A.

    2017-10-01

    Particle-in-Cell (PIC) codes are used in almost all areas of plasma physics, such as fusion energy research, plasma accelerators, space physics, ion propulsion, and plasma processing, and many other areas. In this work, we present the ZPIC educational code suite, a new initiative to foster training in plasma physics using computer simulations. Leveraging on our expertise and experience from the development and use of the OSIRIS PIC code, we have developed a suite of 1D/2D fully relativistic electromagnetic PIC codes, as well as 1D electrostatic. These codes are self-contained and require only a standard laptop/desktop computer with a C compiler to be run. The output files are written in a new file format called ZDF that can be easily read using the supplied routines in a number of languages, such as Python, and IDL. The code suite also includes a number of example problems that can be used to illustrate several textbook and advanced plasma mechanisms, including instructions for parameter space exploration. We also invite contributions to this repository of test problems that will be made freely available to the community provided the input files comply with the format defined by the ZPIC team. The code suite is freely available and hosted on GitHub at https://github.com/zambzamb/zpic. Work partially supported by PICKSC.

  12. Characterization of novel precursor miRNAs using next generation sequencing and prediction of miRNA targets in Atlantic halibut.

    Teshome Tilahun Bizuayehu

    Full Text Available BACKGROUND: microRNAs (miRNAs are implicated in regulation of many cellular processes. miRNAs are processed to their mature functional form in a step-wise manner by multiple proteins and cofactors in the nucleus and cytoplasm. Many miRNAs are conserved across vertebrates. Mature miRNAs have recently been characterized in Atlantic halibut (Hippoglossus hippoglossus L.. The aim of this study was to identify and characterize precursor miRNA (pre-miRNAs and miRNA targets in this non-model flatfish. Discovery of miRNA precursor forms and targets in non-model organisms is difficult because of limited source information available. Therefore, we have developed a methodology to overcome this limitation. METHODS: Genomic DNA and small transcriptome of Atlantic halibut were sequenced using Roche 454 pyrosequencing and SOLiD next generation sequencing (NGS, respectively. Identified pre- miRNAs were further validated with reverse-transcription PCR. miRNA targets were identified using miRanda and RNAhybrid target prediction tools using sequences from public databases. Some of miRNA targets were also identified using RACE-PCR. miRNA binding sites were validated with luciferase assay using the RTS34st cell line. RESULTS: We obtained more than 1.3 M and 92 M sequence reads from 454 genomic DNA sequencing and SOLiD small RNA sequencing, respectively. We identified 34 known and 9 novel pre-miRNAs. We predicted a number of miRNA target genes involved in various biological pathways. miR-24 binding to kisspeptin 1 receptor-2 (kiss1-r2 was confirmed using luciferase assay. CONCLUSION: This study demonstrates that identification of conserved and novel pre-miRNAs in a non-model vertebrate lacking substantial genomic resources can be performed by combining different next generation sequencing technologies. Our results indicate a wide conservation of miRNA precursors and involvement of miRNA in multiple regulatory pathways, and provide resources for further research on miRNA

  13. Conservation of σ28-Dependent Non-Coding RNA Paralogs and Predicted σ54-Dependent Targets in Thermophilic Campylobacter Species.

    My Thanh Le

    Full Text Available Assembly of flagella requires strict hierarchical and temporal control via flagellar sigma and anti-sigma factors, regulatory proteins and the assembly complex itself, but to date non-coding RNAs (ncRNAs have not been described to regulate genes directly involved in flagellar assembly. In this study we have investigated the possible role of two ncRNA paralogs (CjNC1, CjNC4 in flagellar assembly and gene regulation of the diarrhoeal pathogen Campylobacter jejuni. CjNC1 and CjNC4 are 37/44 nt identical and predicted to target the 5' untranslated region (5' UTR of genes transcribed from the flagellar sigma factor σ54. Orthologs of the σ54-dependent 5' UTRs and ncRNAs are present in the genomes of other thermophilic Campylobacter species, and transcription of CjNC1 and CNC4 is dependent on the flagellar sigma factor σ28. Surprisingly, inactivation and overexpression of CjNC1 and CjNC4 did not affect growth, motility or flagella-associated phenotypes such as autoagglutination. However, CjNC1 and CjNC4 were able to mediate sequence-dependent, but Hfq-independent, partial repression of fluorescence of predicted target 5' UTRs in an Escherichia coli-based GFP reporter gene system. This hints towards a subtle role for the CjNC1 and CjNC4 ncRNAs in post-transcriptional gene regulation in thermophilic Campylobacter species, and suggests that the currently used phenotypic methodologies are insufficiently sensitive to detect such subtle phenotypes. The lack of a role of Hfq in the E. coli GFP-based system indicates that the CjNC1 and CjNC4 ncRNAs may mediate post-transcriptional gene regulation in ways that do not conform to the paradigms obtained from the Enterobacteriaceae.

  14. Conservation of σ28-Dependent Non-Coding RNA Paralogs and Predicted σ54-Dependent Targets in Thermophilic Campylobacter Species

    Le, My Thanh; van Veldhuizen, Mart; Porcelli, Ida; Bongaerts, Roy J.; Gaskin, Duncan J. H.; Pearson, Bruce M.; van Vliet, Arnoud H. M.

    2015-01-01

    Assembly of flagella requires strict hierarchical and temporal control via flagellar sigma and anti-sigma factors, regulatory proteins and the assembly complex itself, but to date non-coding RNAs (ncRNAs) have not been described to regulate genes directly involved in flagellar assembly. In this study we have investigated the possible role of two ncRNA paralogs (CjNC1, CjNC4) in flagellar assembly and gene regulation of the diarrhoeal pathogen Campylobacter jejuni. CjNC1 and CjNC4 are 37/44 nt identical and predicted to target the 5' untranslated region (5' UTR) of genes transcribed from the flagellar sigma factor σ54. Orthologs of the σ54-dependent 5' UTRs and ncRNAs are present in the genomes of other thermophilic Campylobacter species, and transcription of CjNC1 and CNC4 is dependent on the flagellar sigma factor σ28. Surprisingly, inactivation and overexpression of CjNC1 and CjNC4 did not affect growth, motility or flagella-associated phenotypes such as autoagglutination. However, CjNC1 and CjNC4 were able to mediate sequence-dependent, but Hfq-independent, partial repression of fluorescence of predicted target 5' UTRs in an Escherichia coli-based GFP reporter gene system. This hints towards a subtle role for the CjNC1 and CjNC4 ncRNAs in post-transcriptional gene regulation in thermophilic Campylobacter species, and suggests that the currently used phenotypic methodologies are insufficiently sensitive to detect such subtle phenotypes. The lack of a role of Hfq in the E. coli GFP-based system indicates that the CjNC1 and CjNC4 ncRNAs may mediate post-transcriptional gene regulation in ways that do not conform to the paradigms obtained from the Enterobacteriaceae. PMID:26512728

  15. Bacterial vaginosis, human papilloma virus and herpes viridae do not predict vaginal HIV RNA shedding in women living with HIV in Denmark.

    Wessman, Maria; Thorsteinsson, Kristina; Jensen, Jørgen S; Storgaard, Merete; Rönsholt, Frederikke F; Johansen, Isik S; Pedersen, Gitte; Nørregård Nielsen, Lars; Bonde, Jesper; Katzenstein, Terese L; Weis, Nina; Lebech, Anne-Mette

    2017-05-31

    Bacterial vaginosis (BV) has been found to be associated with HIV acquisition and transmission. This is suggested to be due to higher HIV RNA levels in cervicovaginal fluids in women living with HIV (WLWH) with BV, as bacteria associated with BV may induce viral replication and shedding in the genital tract despite undetectable HIV RNA plasma viral load. We examined the prevalence and diagnostic predictors of BV and HIV-1 RNA vaginal shedding in women living with HIV (WLWH) in Denmark, taking into account the presence of human papillomavirus (HPV) and herpes viridae. WLWH between 18-51 years were recruited from six Departments of Infectious Diseases in Denmark during enrolment in the SHADE cohort; a prospective cohort study of WLWH attending regular outpatient care. BV was diagnosed by microscopy of vaginal swabs and PCR was used for detection of BV-associated bacteria, HPV, herpes viridae, and vaginal HIV viral load. Median age of the 150 included women was 41 years; ethnicity was predominantly White (35%) or Black (47%). The majority (96%) was on ART and had undetectable (85%) plasma HIV RNA (<40 copies/mL). BV was diagnosed in 32%. Overall, 11% had detectable vaginal HIV RNA. Both before and after adjustment for BV, age, ethnicity, plasma HIV RNA, CD4 cell count, herpes viridae and HPV, we found no significant predictors of HIV RNA vaginal shedding. In well-treated WLWH, BV, herpes viridae or HPV do not predict vaginal HIV RNA shedding. This implies that HIV shedding does not seem to be increased by BV.

  16. NAViGaTing the micronome--using multiple microRNA prediction databases to identify signalling pathway-associated microRNAs.

    Elize A Shirdel

    2011-02-01

    Full Text Available MicroRNAs are a class of small RNAs known to regulate gene expression at the transcript level, the protein level, or both. Since microRNA binding is sequence-based but possibly structure-specific, work in this area has resulted in multiple databases storing predicted microRNA:target relationships computed using diverse algorithms. We integrate prediction databases, compare predictions to in vitro data, and use cross-database predictions to model the microRNA:transcript interactome--referred to as the micronome--to study microRNA involvement in well-known signalling pathways as well as associations with disease. We make this data freely available with a flexible user interface as our microRNA Data Integration Portal--mirDIP (http://ophid.utoronto.ca/mirDIP.mirDIP integrates prediction databases to elucidate accurate microRNA:target relationships. Using NAViGaTOR to produce interaction networks implicating microRNAs in literature-based, KEGG-based and Reactome-based pathways, we find these signalling pathway networks have significantly more microRNA involvement compared to chance (p<0.05, suggesting microRNAs co-target many genes in a given pathway. Further examination of the micronome shows two distinct classes of microRNAs; universe microRNAs, which are involved in many signalling pathways; and intra-pathway microRNAs, which target multiple genes within one signalling pathway. We find universe microRNAs to have more targets (p<0.0001, to be more studied (p<0.0002, and to have higher degree in the KEGG cancer pathway (p<0.0001, compared to intra-pathway microRNAs.Our pathway-based analysis of mirDIP data suggests microRNAs are involved in intra-pathway signalling. We identify two distinct classes of microRNAs, suggesting a hierarchical organization of microRNAs co-targeting genes both within and between pathways, and implying differential involvement of universe and intra-pathway microRNAs at the disease level.

  17. Pre-mRNA Splicing in Plants: In Vivo Functions of RNA-Binding Proteins Implicated in the Splicing Process

    Katja Meyer

    2015-07-01

    Full Text Available Alternative pre-messenger RNA splicing in higher plants emerges as an important layer of regulation upon exposure to exogenous and endogenous cues. Accordingly, mutants defective in RNA-binding proteins predicted to function in the splicing process show severe phenotypic alterations. Among those are developmental defects, impaired responses to pathogen threat or abiotic stress factors, and misregulation of the circadian timing system. A suite of splicing factors has been identified in the model plant Arabidopsis thaliana. Here we summarize recent insights on how defects in these splicing factors impair plant performance.

  18. Novel prediction of anticancer drug chemosensitivity in cancer cell lines: evidence of moderation by microRNA expressions.

    Yang, Daniel S

    2014-01-01

    The objectives of this study are (1) to develop a novel "moderation" model of drug chemosensitivity and (2) to investigate if miRNA expression moderates the relationship between gene expression and drug chemosensitivity, specifically for HSP90 inhibitors applied to human cancer cell lines. A moderation model integrating the interaction between miRNA and gene expressions was developed to examine if miRNA expression affects the strength of the relationship between gene expression and chemosensitivity. Comprehensive datasets on miRNA expressions, gene expressions, and drug chemosensitivities were obtained from National Cancer Institute's NCI-60 cell lines including nine different cancer types. A workflow including steps of selecting genes, miRNAs, and compounds, correlating gene expression with chemosensitivity, and performing multivariate analysis was utilized to test the proposed model. The proposed moderation model identified 12 significantly-moderating miRNAs: miR-15b*, miR-16-2*, miR-9, miR-126*, miR-129*, miR-138, miR-519e*, miR-624*, miR-26b, miR-30e*, miR-32, and miR-196a, as well as two genes ERCC2 and SF3B1 which affect chemosensitivities of Tanespimycin and Alvespimycin - both HSP90 inhibitors. A bootstrap resampling of 2,500 times validates the significance of all 12 identified miRNAs. The results confirm that certain miRNA and gene expressions interact to produce an effect on drug response. The lack of correlation between miRNA and gene expression themselves suggests that miRNA transmits its effect through translation inhibition/control rather than mRNA degradation. The results suggest that miRNAs could serve not only as prognostic biomarkers for cancer treatment outcome but also as interventional agents to modulate desired chemosensitivity.

  19. Identification of Gene Networks for Residual Feed Intake in Angus Cattle Using Genomic Prediction and RNA-seq.

    Weber, Kristina L; Welly, Bryan T; Van Eenennaam, Alison L; Young, Amy E; Porto-Neto, Laercio R; Reverter, Antonio; Rincon, Gonzalo

    2016-01-01

    Improvement in feed conversion efficiency can improve the sustainability of beef cattle production, but genomic selection for feed efficiency affects many underlying molecular networks and physiological traits. This study describes the differences between steer progeny of two influential Angus bulls with divergent genomic predictions for residual feed intake (RFI). Eight steer progeny of each sire were phenotyped for growth and feed intake from 8 mo. of age (average BW 254 kg, with a mean difference between sire groups of 4.8 kg) until slaughter at 14-16 mo. of age (average BW 534 kg, sire group difference of 28.8 kg). Terminal samples from pituitary gland, skeletal muscle, liver, adipose, and duodenum were collected from each steer for transcriptome sequencing. Gene expression networks were derived using partial correlation and information theory (PCIT), including differentially expressed (DE) genes, tissue specific (TS) genes, transcription factors (TF), and genes associated with RFI from a genome-wide association study (GWAS). Relative to progeny of the high RFI sire, progeny of the low RFI sire had -0.56 kg/d finishing period RFI (P = 0.05), -1.08 finishing period feed conversion ratio (P = 0.01), +3.3 kg^0.75 finishing period metabolic mid-weight (MMW; P = 0.04), +28.8 kg final body weight (P = 0.01), -12.9 feed bunk visits per day (P = 0.02) with +0.60 min/visit duration (P = 0.01), and +0.0045 carcass specific gravity (weight in air/weight in air-weight in water, a predictor of carcass fat content; P = 0.03). RNA-seq identified 633 DE genes between sire groups among 17,016 expressed genes. PCIT analysis identified >115,000 significant co-expression correlations between genes and 25 TF hubs, i.e. controllers of clusters of DE, TS, and GWAS SNP genes. Pathway analysis suggests low RFI bull progeny possess heightened gut inflammation and reduced fat deposition. This multi-omics analysis shows how differences in RFI genomic breeding values can impact other

  20. Identification of Gene Networks for Residual Feed Intake in Angus Cattle Using Genomic Prediction and RNA-seq.

    Kristina L Weber

    Full Text Available Improvement in feed conversion efficiency can improve the sustainability of beef cattle production, but genomic selection for feed efficiency affects many underlying molecular networks and physiological traits. This study describes the differences between steer progeny of two influential Angus bulls with divergent genomic predictions for residual feed intake (RFI. Eight steer progeny of each sire were phenotyped for growth and feed intake from 8 mo. of age (average BW 254 kg, with a mean difference between sire groups of 4.8 kg until slaughter at 14-16 mo. of age (average BW 534 kg, sire group difference of 28.8 kg. Terminal samples from pituitary gland, skeletal muscle, liver, adipose, and duodenum were collected from each steer for transcriptome sequencing. Gene expression networks were derived using partial correlation and information theory (PCIT, including differentially expressed (DE genes, tissue specific (TS genes, transcription factors (TF, and genes associated with RFI from a genome-wide association study (GWAS. Relative to progeny of the high RFI sire, progeny of the low RFI sire had -0.56 kg/d finishing period RFI (P = 0.05, -1.08 finishing period feed conversion ratio (P = 0.01, +3.3 kg^0.75 finishing period metabolic mid-weight (MMW; P = 0.04, +28.8 kg final body weight (P = 0.01, -12.9 feed bunk visits per day (P = 0.02 with +0.60 min/visit duration (P = 0.01, and +0.0045 carcass specific gravity (weight in air/weight in air-weight in water, a predictor of carcass fat content; P = 0.03. RNA-seq identified 633 DE genes between sire groups among 17,016 expressed genes. PCIT analysis identified >115,000 significant co-expression correlations between genes and 25 TF hubs, i.e. controllers of clusters of DE, TS, and GWAS SNP genes. Pathway analysis suggests low RFI bull progeny possess heightened gut inflammation and reduced fat deposition. This multi-omics analysis shows how differences in RFI genomic breeding values can impact other

  1. The Mapping of Predicted Triplex DNA:RNA in the Drosophila Genome Reveals a Prominent Location in Development- and Morphogenesis-Related Genes

    Claude Pasquier

    2017-07-01

    Full Text Available Double-stranded DNA is able to form triple-helical structures by accommodating a third nucleotide strand. A nucleic acid triplex occurs according to Hoogsteen rules that predict the stability and affinity of the third strand bound to the Watson–Crick duplex. The “triplex-forming oligonucleotide” (TFO can be a short sequence of RNA that binds to the major groove of the targeted duplex only when this duplex presents a sequence of purine or pyrimidine bases in one of the DNA strands. Many nuclear proteins are known to bind triplex DNA or DNA:RNA, but their biological functions are unexplored. We identified sequences that are capable of engaging as the “triplex-forming oligonucleotide” in both the pre-lncRNA and pre-mRNA collections of Drosophila melanogaster. These motifs were matched against the Drosophila genome in order to identify putative sequences of triplex formation in intergenic regions, promoters, and introns/exons. Most of the identified TFOs appear to be located in the intronic region of the analyzed genes. Computational prediction of the most targeted genes by TFOs originating from pre-lncRNAs and pre-mRNAs revealed that they are restrictively associated with development- and morphogenesis-related gene networks. The refined analysis by Gene Ontology enrichment demonstrates that some individual TFOs present genome-wide scale matches that are located in numerous genes and regulatory sequences. The triplex DNA:RNA computational mapping at the genome-wide scale suggests broad interference in the regulatory process of the gene networks orchestrated by TFO RNAs acting in association simultaneously at multiple sites.

  2. Automated classification of RNA 3D motifs and the RNA 3D Motif Atlas

    Petrov, Anton I.; Zirbel, Craig L.; Leontis, Neocles B.

    2013-01-01

    The analysis of atomic-resolution RNA three-dimensional (3D) structures reveals that many internal and hairpin loops are modular, recurrent, and structured by conserved non-Watson–Crick base pairs. Structurally similar loops define RNA 3D motifs that are conserved in homologous RNA molecules, but can also occur at nonhomologous sites in diverse RNAs, and which often vary in sequence. To further our understanding of RNA motif structure and sequence variability and to provide a useful resource for structure modeling and prediction, we present a new method for automated classification of internal and hairpin loop RNA 3D motifs and a new online database called the RNA 3D Motif Atlas. To classify the motif instances, a representative set of internal and hairpin loops is automatically extracted from a nonredundant list of RNA-containing PDB files. Their structures are compared geometrically, all-against-all, using the FR3D program suite. The loops are clustered into motif groups, taking into account geometric similarity and structural annotations and making allowance for a variable number of bulged bases. The automated procedure that we have implemented identifies all hairpin and internal loop motifs previously described in the literature. All motif instances and motif groups are assigned unique and stable identifiers and are made available in the RNA 3D Motif Atlas (http://rna.bgsu.edu/motifs), which is automatically updated every four weeks. The RNA 3D Motif Atlas provides an interactive user interface for exploring motif diversity and tools for programmatic data access. PMID:23970545

  3. Safety in the use of pressurized suits

    1984-01-01

    This Code of Practice describes the procedures relating to the safe operation of Pressurized Suit Areas and their supporting services. It is directed at personnel responsible for the design and/or operation of Pressurized Suit Areas. (author)

  4. Predictive value of BRCA1/2 mRNA expression for response to neoadjuvant chemotherapy in BRCA-negative breast cancers.

    Xu, Ye; Ouyang, Tao; Li, Jinfeng; Wang, Tianfeng; Fan, Zhaoqing; Fan, Tie; Lin, Benyao; Xie, Yuntao

    2018-01-01

    It is well known that BRCA1 and BRCA2 play a central role in DNA repair, but the relationship between BRCA1 and BRCA2 mRNA expression and response to neoadjuvant chemotherapy in sporadic breast cancer patients has not been well established. Here, we investigate the association between BRCA1 or BRCA2 mRNA expression levels and pathological response in 674 BRCA1/2 mutation-negative breast cancer patients who received neoadjuvant chemotherapy. BRCA1 and BRCA2 mRNA expression were assessed using quantitative real-time polymerase chain reaction in core biopsy breast cancer tissue obtained prior to the initiation of neoadjuvant chemotherapy. A total 129 patients (19.1%) achieved pathological complete response (pCR) after neoadjuvant chemotherapy. Among patients treated with anthracycline-based chemotherapy (n = 531), BRCA1 mRNA low expression patients had a significantly higher pCR rate than intermediate or high BRCA1 mRNA expression groups (24.6% vs 16.8% or 14.0%, P = .031) and retained borderline significance (OR = 1.54, 95% CI = 0.93-2.56, P = .094) in multivariate analysis. Among the 129 patients who received a taxane-based regimen, pCR rate showed no differences in BRCA1 low, intermediate, and high mRNA level subgroups (19.6%, 26.8% and 21.4%, respectively; P = .71). BRCA2 mRNA level was not associated with pCR rate in the anthracyline-based treated subgroup (P = .60) or the taxane-based regimen subgroup (P = .82). Taken together, our findings suggested that BRCA1 mRNA expression could be used as a predictive marker in BRCA1/2 mutation-negative breast cancer patients who received neoadjuvant anthracycline-based treatment. © 2017 The Authors. Cancer Science published by John Wiley & Sons Australia, Ltd on behalf of Japanese Cancer Association.

  5. Automated integration of lidar into the LANDFIRE product suite

    Birgit Peterson; Kurtis J. Nelson; Carl Seielstad; Jason Stoker; W. Matt Jolly; Russell Parsons

    2015-01-01

    Accurate information about three-dimensional canopy structure and wildland fuel across the landscape is necessary for fire behaviour modelling system predictions. Remotely sensed data are invaluable for assessing these canopy characteristics over large areas; lidar data, in particular, are uniquely suited for quantifying three-dimensional canopy structure. Although...

  6. Z-2 Suit Support Stand and MKIII Suit Center of Gravity Test

    Nguyen, Tuan Q.

    2014-01-01

    NASA's next generation spacesuits are the Z-Series suits, made for a range of possible exploration missions in the near future. The prototype Z-1 suit has been developed and assembled to incorporate new technologies that has never been utilized before in the Apollo suits and the Extravehicular Mobility Unit (EMU). NASA engineers tested the Z-1 suit extensively in order to developed design requirements for the new Z-2 suit. At the end of 2014, NASA will be receiving the new Z-2 suit to perform more testing and to further develop the new technologies of the suit. In order to do so, a suit support stand will be designed and fabricated to support the Z-2 suit during maintenance, sizing, and structural leakage testing. The Z-2 Suit Support Stand (Z2SSS) will be utilized for these purposes in the early testing stages of the Z-2 suit.

  7. Machine Learning Approaches Toward Building Predictive Models for Small Molecule Modulators of miRNA and Its Utility in Virtual Screening of Molecular Databases.

    Periwal, Vinita; Scaria, Vinod

    2017-01-01

    The ubiquitous role of microRNAs (miRNAs) in a number of pathological processes has suggested that they could act as potential drug targets. RNA-binding small molecules offer an attractive means for modulating miRNA function. The availability of bioassay data sets for a variety of biological assays and molecules in public domain provides a new opportunity toward utilizing them to create models and further utilize them for in silico virtual screening approaches to prioritize or assign potential functions for small molecules. Here, we describe a computational strategy based on machine learning for creation of predictive models from high-throughput biological screens for virtual screening of small molecules with the potential to inhibit microRNAs. Such models could be potentially used for computational prioritization of small molecules before performing high-throughput biological assay.

  8. Splice site prediction in Arabidopsis thaliana pre-mRNA by combining local and global sequence information

    Hebsgaard, Stefan M.; Korning, Peter G.; Tolstrup, Niels

    1996-01-01

    Artificial neural networks have been combined with a rule based system to predict intron splice sites in the dicot plant Arabidopsis thaliana. A two step prediction scheme, where a global prediction of the coding potential regulates a cutoff level for a local predicition of splice sites, is refin...

  9. Effects of using coding potential, sequence conservation and mRNA structure conservation for predicting pyrroly-sine containing genes

    Have, Christian Theil; Zambach, Sine; Christiansen, Henning

    2013-01-01

    for prediction of pyrrolysine incorporating genes in genomes of bacteria and archaea leading to insights about the factors driving pyrrolysine translation and identification of new gene candidates. The method predicts known conserved genes with high recall and predicts several other promising candidates...... for experimental verification. The method is implemented as a computational pipeline which is available on request....

  10. Small, synthetic, GC-rich mRNA stem-loop modules 5' proximal to the AUG start-codon predictably tune gene expression in yeast.

    Lamping, Erwin; Niimi, Masakazu; Cannon, Richard D

    2013-07-29

    A large range of genetic tools has been developed for the optimal design and regulation of complex metabolic pathways in bacteria. However, fewer tools exist in yeast that can precisely tune the expression of individual enzymes in novel metabolic pathways suitable for industrial-scale production of non-natural compounds. Tuning expression levels is critical for reducing the metabolic burden of over-expressed proteins, the accumulation of toxic intermediates, and for redirecting metabolic flux from native pathways involving essential enzymes without negatively affecting the viability of the host. We have developed a yeast membrane protein hyper-expression system with critical advantages over conventional, plasmid-based, expression systems. However, expression levels are sometimes so high that they adversely affect protein targeting/folding or the growth and/or phenotype of the host. Here we describe the use of small synthetic mRNA control modules that allowed us to predictably tune protein expression levels to any desired level. Down-regulation of expression was achieved by engineering small GC-rich mRNA stem-loops into the 5' UTR that inhibited translation initiation of the yeast ribosomal 43S preinitiation complex (PIC). Exploiting the fact that the yeast 43S PIC has great difficulty scanning through GC-rich mRNA stem-loops, we created yeast strains containing 17 different RNA stem-loop modules in the 5' UTR that expressed varying amounts of the fungal multidrug efflux pump reporter Cdr1p from Candida albicans. Increasing the length of mRNA stem-loops (that contained only GC-pairs) near the AUG start-codon led to a surprisingly large decrease in Cdr1p expression; ~2.7-fold for every additional GC-pair added to the stem, while the mRNA levels remained largely unaffected. An mRNA stem-loop of seven GC-pairs (∆G = -15.8 kcal/mol) reduced Cdr1p expression levels by >99%, and even the smallest possible stem-loop of only three GC-pairs (∆G = -4.4 kcal/mol) inhibited

  11. Small, synthetic, GC-rich mRNA stem-loop modules 5′ proximal to the AUG start-codon predictably tune gene expression in yeast

    2013-01-01

    Background A large range of genetic tools has been developed for the optimal design and regulation of complex metabolic pathways in bacteria. However, fewer tools exist in yeast that can precisely tune the expression of individual enzymes in novel metabolic pathways suitable for industrial-scale production of non-natural compounds. Tuning expression levels is critical for reducing the metabolic burden of over-expressed proteins, the accumulation of toxic intermediates, and for redirecting metabolic flux from native pathways involving essential enzymes without negatively affecting the viability of the host. We have developed a yeast membrane protein hyper-expression system with critical advantages over conventional, plasmid-based, expression systems. However, expression levels are sometimes so high that they adversely affect protein targeting/folding or the growth and/or phenotype of the host. Here we describe the use of small synthetic mRNA control modules that allowed us to predictably tune protein expression levels to any desired level. Down-regulation of expression was achieved by engineering small GC-rich mRNA stem-loops into the 5′ UTR that inhibited translation initiation of the yeast ribosomal 43S preinitiation complex (PIC). Results Exploiting the fact that the yeast 43S PIC has great difficulty scanning through GC-rich mRNA stem-loops, we created yeast strains containing 17 different RNA stem-loop modules in the 5′ UTR that expressed varying amounts of the fungal multidrug efflux pump reporter Cdr1p from Candida albicans. Increasing the length of mRNA stem-loops (that contained only GC-pairs) near the AUG start-codon led to a surprisingly large decrease in Cdr1p expression; ~2.7-fold for every additional GC-pair added to the stem, while the mRNA levels remained largely unaffected. An mRNA stem-loop of seven GC-pairs (∆G = −15.8 kcal/mol) reduced Cdr1p expression levels by >99%, and even the smallest possible stem-loop of only three GC-pairs (

  12. A Parametric Model of Shoulder Articulation for Virtual Assessment of Space Suit Fit

    Kim, K. Han; Young, Karen S.; Bernal, Yaritza; Boppana, Abhishektha; Vu, Linh Q.; Benson, Elizabeth A.; Jarvis, Sarah; Rajulu, Sudhakar L.

    2016-01-01

    Suboptimal suit fit is a known risk factor for crewmember shoulder injury. Suit fit assessment is however prohibitively time consuming and cannot be generalized across wide variations of body shapes and poses. In this work, we have developed a new design tool based on the statistical analysis of body shape scans. This tool is aimed at predicting the skin deformation and shape variations for any body size and shoulder pose for a target population. This new process, when incorporated with CAD software, will enable virtual suit fit assessments, predictively quantifying the contact volume, and clearance between the suit and body surface at reduced time and cost.

  13. Computational sequence analysis of predicted long dsRNA transcriptomes of major crops reveals sequence complementarity with human genes.

    Jensen, Peter D; Zhang, Yuanji; Wiggins, B Elizabeth; Petrick, Jay S; Zhu, Jin; Kerstetter, Randall A; Heck, Gregory R; Ivashuta, Sergey I

    2013-01-01

    Long double-stranded RNAs (long dsRNAs) are precursors for the effector molecules of sequence-specific RNA-based gene silencing in eukaryotes. Plant cells can contain numerous endogenous long dsRNAs. This study demonstrates that such endogenous long dsRNAs in plants have sequence complementarity to human genes. Many of these complementary long dsRNAs have perfect sequence complementarity of at least 21 nucleotides to human genes; enough complementarity to potentially trigger gene silencing in targeted human cells if delivered in functional form. However, the number and diversity of long dsRNA molecules in plant tissue from crops such as lettuce, tomato, corn, soy and rice with complementarity to human genes that have a long history of safe consumption supports a conclusion that long dsRNAs do not present a significant dietary risk.

  14. Long non-coding RNA PVT1 as a novel potential biomarker for predicting the prognosis of colorectal cancer.

    Fan, Heng; Zhu, Jian-Hua; Yao, Xue-Qing

    2018-05-01

    Long non-coding RNA (lncRNA) plays a very important role in the occurrence and development of various tumors, and is a potential biomarker for cancer diagnosis and prognosis. The purpose of this study was to investigate the relationship between the expression of lncRNA plasmacytoma variant translocation 1 (PVT1) and the prognostic significance in patients with colorectal cancer. The expression of PVT1 was measured by real-time quantitative reverse transcription-polymerase chain reaction (qRT-PCR) in cancerous and adjacent tissues of 210 colorectal cancer patients. The disease-free survival and overall survival of colorectal cancer patients were evaluated by Kaplan-Meier analysis, and univariate and multivariate analysis were performed by Cox proportional-hazards model. Our results revealed that PVT1 expression in cancer tissues of colorectal cancer was significantly higher than that of adjacent tissues ( Pcolorectal cancer patients, whether at TNM I/II stage or at TNM III/IV stage. A multivariate Cox regression analysis demonstrated that high PVT1 expression was an independent predictor of poor prognosis in colorectal cancer patients. Our results suggest that high PVT1 expression might be a potential biomarker for assessing tumor recurrence and prognosis in colorectal cancer patients.

  15. Concepts and introduction to RNA bioinformatics

    Gorodkin, Jan; Hofacker, Ivo L.; Ruzzo, Walter L.

    2014-01-01

    RNA bioinformatics and computational RNA biology have emerged from implementing methods for predicting the secondary structure of single sequences. The field has evolved to exploit multiple sequences to take evolutionary information into account, such as compensating (and structure preserving) base...... for interactions between RNA and proteins.Here, we introduce the basic concepts of predicting RNA secondary structure relevant to the further analyses of RNA sequences. We also provide pointers to methods addressing various aspects of RNA bioinformatics and computational RNA biology....

  16. Combinatorics of RNA-RNA interaction

    Li, Thomas J X; Reidys, Christian

    2012-01-01

    RNA-RNA binding is an important phenomenon observed for many classes of non-coding RNAs and plays a crucial role in a number of regulatory processes. Recently several MFE folding algorithms for predicting the joint structure of two interacting RNA molecules have been proposed. Here joint structure...... means that in a diagram representation the intramolecular bonds of each partner are pseudoknot-free, that the intermolecular binding pairs are noncrossing, and that there is no so-called "zigzag" configuration. This paper presents the combinatorics of RNA interaction structures including...

  17. The BRITNeY Suite Animation Tool

    Westergaard, Michael; Lassen, Kristian Bisgaard

    2006-01-01

    This paper describes the BRITNeY suite, a tool which enables users to create visualizations of formal models. BRITNeY suite is integrated with CPN Tools, and we give an example of how to extend a simple stop-and-wait protocol with a visualization in the form of message sequence charts. We also sh...... examples of animations created during industrial projects to give an impression of what is possible with the BRITNeY suite....

  18. Deep sequencing of small RNA libraries from human prostate epithelial and stromal cells reveal distinct pattern of microRNAs primarily predicted to target growth factors.

    Singh, Savita; Zheng, Yun; Jagadeeswaran, Guru; Ebron, Jey Sabith; Sikand, Kavleen; Gupta, Sanjay; Sunker, Ramanjulu; Shukla, Girish C

    2016-02-28

    Complex epithelial and stromal cell interactions are required during the development and progression of prostate cancer. Regulatory small non-coding microRNAs (miRNAs) participate in the spatiotemporal regulation of messenger RNA (mRNA) and regulation of translation affecting a large number of genes involved in prostate carcinogenesis. In this study, through deep-sequencing of size fractionated small RNA libraries we profiled the miRNAs of prostate epithelial (PrEC) and stromal (PrSC) cells. Over 50 million reads were obtained for PrEC in which 860,468 were unique sequences. Similarly, nearly 76 million reads for PrSC were obtained in which over 1 million were unique reads. Expression of many miRNAs of broadly conserved and poorly conserved miRNA families were identified. Sixteen highly expressed miRNAs with significant change in expression in PrSC than PrEC were further analyzed in silico. ConsensusPathDB showed the target genes of these miRNAs were significantly involved in adherence junction, cell adhesion, EGRF, TGF-β and androgen signaling. Let-7 family of tumor-suppressor miRNAs expression was highly pervasive in both, PrEC and PrSC cells. In addition, we have also identified several miRNAs that are unique to PrEC or PrSC cells and their predicted putative targets are a group of transcription factors. This study provides perspective on the miRNA expression in PrEC and PrSC, and reveals a global trend in miRNA interactome. We conclude that the most abundant miRNAs are potential regulators of development and differentiation of the prostate gland by targeting a set of growth factors. Additionally, high level expression of the most members of let-7 family miRNAs suggests their role in the fine tuning of the growth and proliferation of prostate epithelial and stromal cells. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

  19. Expression profiles analysis of long non-coding RNAs identified novel lncRNA biomarkers with predictive value in outcome of cutaneous melanoma.

    Ma, Xu; He, Zhijuan; Li, Ling; Yang, Daping; Liu, Guofeng

    2017-09-29

    Recent advancements in cancer biology have identified a large number of lncRNAs that are dysregulated expression in the development and tumorigenesis of cancers, highlighting the importance of lncRNAs as a key player for human cancers. However, the prognostic value of lncRNAs still remains unclear and needs to be further investigated. In the present study, we aim to assess the prognostic value of lncRNAs in cutaneous melanoma by integrated lncRNA expression profiles from TCGA database and matched clinical information from a large cohort of patients with cutaneous melanoma. We finally identified a set of six lncRNAs that are significantly associated with survival of patients with cutaneous melanoma. A linear combination of six lncRNAs ( LINC01260, HCP5, PIGBOS1, RP11-247L20.4, CTA-292E10.6 and CTB-113P19.5 ) was constructed as a six-lncRNA signature which classified patients of training cohort into the high-risk group and low-risk group with significantly different survival time. The prognostic value of the six-lncRNA signature was validated in both the validation cohort and entire TCGA cohort. Moreover, the six-lncRNA signature is independent of known clinic-pathological factors by multivariate Cox regression analysis and demonstrated good performance for predicting three- and five-year overall survival by time-dependent receiver operating characteristic (ROC) analysis. Our study provides novel insights into the molecular heterogeneity of cutaneous melanoma and also shows potentially important implications of lncRNAs for prognosis and therapy for cutaneous melanoma.

  20. HPC Benchmark Suite NMx, Phase I

    National Aeronautics and Space Administration — Intelligent Automation Inc., (IAI) and University of Central Florida (UCF) propose to develop a comprehensive numerical test suite for benchmarking current and...

  1. ASDA - Advanced Suit Design Analyzer computer program

    Bue, Grant C.; Conger, Bruce C.; Iovine, John V.; Chang, Chi-Min

    1992-01-01

    An ASDA model developed to evaluate the heat and mass transfer characteristics of advanced pressurized suit design concepts for low pressure or vacuum planetary applications is presented. The model is based on a generalized 3-layer suit that uses the Systems Integrated Numerical Differencing Analyzer '85 in conjunction with a 41-node FORTRAN routine. The latter simulates the transient heat transfer and respiratory processes of a human body in a suited environment. The user options for the suit encompass a liquid cooled garment, a removable jacket, a CO2/H2O permeable layer, and a phase change layer.

  2. Correlated miR-mRNA expression signatures of mouse hematopoietic stem and progenitor cell subsets predict "Stemness" and "Myeloid" interaction networks.

    Diane Heiser

    Full Text Available Several individual miRNAs (miRs have been implicated as potent regulators of important processes during normal and malignant hematopoiesis. In addition, many miRs have been shown to fine-tune intricate molecular networks, in concert with other regulatory elements. In order to study hematopoietic networks as a whole, we first created a map of global miR expression during early murine hematopoiesis. Next, we determined the copy number per cell for each miR in each of the examined stem and progenitor cell types. As data is emerging indicating that miRs function robustly mainly when they are expressed above a certain threshold (∼100 copies per cell, our database provides a resource for determining which miRs are expressed at a potentially functional level in each cell type. Finally, we combine our miR expression map with matched mRNA expression data and external prediction algorithms, using a Bayesian modeling approach to create a global landscape of predicted miR-mRNA interactions within each of these hematopoietic stem and progenitor cell subsets. This approach implicates several interaction networks comprising a "stemness" signature in the most primitive hematopoietic stem cell (HSC populations, as well as "myeloid" patterns associated with two branches of myeloid development.

  3. Correlated miR-mRNA expression signatures of mouse hematopoietic stem and progenitor cell subsets predict "Stemness" and "Myeloid" interaction networks.

    Heiser, Diane; Tan, Yee Sun; Kaplan, Ian; Godsey, Brian; Morisot, Sebastien; Cheng, Wen-Chih; Small, Donald; Civin, Curt I

    2014-01-01

    Several individual miRNAs (miRs) have been implicated as potent regulators of important processes during normal and malignant hematopoiesis. In addition, many miRs have been shown to fine-tune intricate molecular networks, in concert with other regulatory elements. In order to study hematopoietic networks as a whole, we first created a map of global miR expression during early murine hematopoiesis. Next, we determined the copy number per cell for each miR in each of the examined stem and progenitor cell types. As data is emerging indicating that miRs function robustly mainly when they are expressed above a certain threshold (∼100 copies per cell), our database provides a resource for determining which miRs are expressed at a potentially functional level in each cell type. Finally, we combine our miR expression map with matched mRNA expression data and external prediction algorithms, using a Bayesian modeling approach to create a global landscape of predicted miR-mRNA interactions within each of these hematopoietic stem and progenitor cell subsets. This approach implicates several interaction networks comprising a "stemness" signature in the most primitive hematopoietic stem cell (HSC) populations, as well as "myeloid" patterns associated with two branches of myeloid development.

  4. Two microRNA signatures for malignancy and immune infiltration predict overall survival in advanced epithelial ovarian cancer.

    Korsunsky, Ilya; Parameswaran, Janaki; Shapira, Iuliana; Lovecchio, John; Menzin, Andrew; Whyte, Jill; Dos Santos, Lisa; Liang, Sharon; Bhuiya, Tawfiqul; Keogh, Mary; Khalili, Houman; Pond, Cassandra; Liew, Anthony; Shih, Andrew; Gregersen, Peter K; Lee, Annette T

    2017-10-01

    MicroRNAs have been established as key regulators of tumor gene expression and as prime biomarker candidates for clinical phenotypes in epithelial ovarian cancer (EOC). We analyzed the coexpression and regulatory structure of microRNAs and their co-localized gene targets in primary tumor tissue of 20 patients with advanced EOC in order to construct a regulatory signature for clinical prognosis. We performed an integrative analysis to identify two prognostic microRNA/mRNA coexpression modules, each enriched for consistent biological functions. One module, enriched for malignancy-related functions, was found to be upregulated in malignant versus benign samples. The second module, enriched for immune-related functions, was strongly correlated with imputed intratumoral immune infiltrates of T cells, natural killer cells, cytotoxic lymphocytes, and macrophages. We validated the prognostic relevance of the immunological module microRNAs in the publicly available The Cancer Genome Atlas data set. These findings provide novel functional roles for microRNAs in the progression of advanced EOC and possible prognostic signatures for survival. © American Federation for Medical Research (unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

  5. LncRNA-SNHG16 predicts poor prognosis and promotes tumor proliferation through epigenetically silencing p21 in bladder cancer.

    Cao, Xianxiang; Xu, Jing; Yue, Dong

    2018-02-01

    More and more evidences have ensured the crucial functions of long non-coding RNAs (lncRNAs) in multiple tumors. It has been discovered that lncRNA-SNHG16 is involved in many tumors. Even so, it is still necessary to study SNHG16 comprehensively in bladder cancer. In terms of our study, the level of SNHG16 both in the tumor tissues and cell lines was measured and the relationship among SNHG16, clinicopathological traits and prognosis was explored. Interference assays were applied to determine the biological functions of SNHG16. It was discovered that the level of SNHG16 was evidently enhanced both in tissues and cell lines of bladder cancer. Patients with highly expressed SNHG16 suffered from poor overall survival. Multivariable Cox proportional hazards regression analysis implied that highly expressed SNHG16 could be used as an independent prognostic marker. It could be known from functional assays that silenced SNHG16 impaired cell proliferation, owing to the effects of SNHG16 on cell cycle and apoptosis. Finally, mechanism experiments revealed that SNHG16 could epigenetically silence the expression of p21. The facts above pointed out that lncRNA-SNHG16 might be quite vital for the diagnosis and development of bladder cancer, and could even become an important therapeutic target for bladder cancer.

  6. Engineering Software Suite Validates System Design

    2007-01-01

    EDAptive Computing Inc.'s (ECI) EDAstar engineering software tool suite, created to capture and validate system design requirements, was significantly funded by NASA's Ames Research Center through five Small Business Innovation Research (SBIR) contracts. These programs specifically developed Syscape, used to capture executable specifications of multi-disciplinary systems, and VectorGen, used to automatically generate tests to ensure system implementations meet specifications. According to the company, the VectorGen tests considerably reduce the time and effort required to validate implementation of components, thereby ensuring their safe and reliable operation. EDASHIELD, an additional product offering from ECI, can be used to diagnose, predict, and correct errors after a system has been deployed using EDASTAR -created models. Initial commercialization for EDASTAR included application by a large prime contractor in a military setting, and customers include various branches within the U.S. Department of Defense, industry giants like the Lockheed Martin Corporation, Science Applications International Corporation, and Ball Aerospace and Technologies Corporation, as well as NASA's Langley and Glenn Research Centers

  7. Sibelius. Karelia Suite, Op. 11 / Robert Layton

    Layton, Robert

    1996-01-01

    Uuest heliplaadist "Sibelius. Karelia Suite, Op. 11. Luonnotar, Op. 70 a. Andante festivo. The Oceanides, Op. 73. King Christian II, Op. 27-Suite. Finlandia, Op. 26a. Gothenburg Symphony Orchester, Neeme Järvi" DG 447 760-2GH (72 minutes: DDD)

  8. Evaluating Suit Fit Using Performance Degradation

    Margerum, Sarah E.; Cowley, Matthew; Harvill, Lauren; Benson, Elizabeth; Rajulu, Sudhakar

    2011-01-01

    The Mark III suit has multiple sizes of suit components (arm, leg, and gloves) as well as sizing inserts to tailor the fit of the suit to an individual. This study sought to determine a way to identify the point an ideal suit fit transforms into a bad fit and how to quantify this breakdown using mobility-based physical performance data. This study examined the changes in human physical performance via degradation of the elbow and wrist range of motion of the planetary suit prototype (Mark III) with respect to changes in sizing and as well as how to apply that knowledge to suit sizing options and improvements in suit fit. The methods implemented in this study focused on changes in elbow and wrist mobility due to incremental suit sizing modifications. This incremental sizing was within a range that included both optimum and poor fit. Suited range of motion data was collected using a motion analysis system for nine isolated and functional tasks encompassing the elbow and wrist joints. A total of four subjects were tested with motions involving both arms simultaneously as well as the right arm only. The results were then compared across sizing configurations. The results of this study indicate that range of motion may be used as a viable parameter to quantify at what stage suit sizing causes a detriment in performance; however the human performance decrement appeared to be based on the interaction of multiple joints along a limb, not a single joint angle. The study was able to identify a preliminary method to quantify the impact of size on performance and to develop a means to gauge tolerances around optimal size. More work is needed to improve the assessment of optimal fit and to compensate for multiple joint interactions.

  9. Histone modification profiles are predictive for tissue/cell-type specific expression of both protein-coding and microRNA genes

    Zhang Michael Q

    2011-05-01

    Full Text Available Abstract Background Gene expression is regulated at both the DNA sequence level and through modification of chromatin. However, the effect of chromatin on tissue/cell-type specific gene regulation (TCSR is largely unknown. In this paper, we present a method to elucidate the relationship between histone modification/variation (HMV and TCSR. Results A classifier for differentiating CD4+ T cell-specific genes from housekeeping genes using HMV data was built. We found HMV in both promoter and gene body regions to be predictive of genes which are targets of TCSR. For example, the histone modification types H3K4me3 and H3K27ac were identified as the most predictive for CpG-related promoters, whereas H3K4me3 and H3K79me3 were the most predictive for nonCpG-related promoters. However, genes targeted by TCSR can be predicted using other type of HMVs as well. Such redundancy implies that multiple type of underlying regulatory elements, such as enhancers or intragenic alternative promoters, which can regulate gene expression in a tissue/cell-type specific fashion, may be marked by the HMVs. Finally, we show that the predictive power of HMV for TCSR is not limited to protein-coding genes in CD4+ T cells, as we successfully predicted TCSR targeted genes in muscle cells, as well as microRNA genes with expression specific to CD4+ T cells, by the same classifier which was trained on HMV data of protein-coding genes in CD4+ T cells. Conclusion We have begun to understand the HMV patterns that guide gene expression in both tissue/cell-type specific and ubiquitous manner.

  10. Bifurcations in the interplay of messenger RNA, protein and nonprotein coding RNA

    Zhdanov, Vladimir P

    2008-01-01

    The interplay of messenger RNA (mRNA), protein, produced via translation of this RNA, and nonprotein coding RNA (ncRNA) may include regulation of the ncRNA production by protein and (i) ncRNA-protein association resulting in suppression of the protein regulatory activity or (ii) ncRNA-mRNA association resulting in degradation of the miRNA-mRNA complex. The kinetic models describing these two scenarios are found to predict bistability provided that protein suppresses the ncRNA formation

  11. Mirnovo: genome-free prediction of microRNAs from small RNA sequencing data and single-cells using decision forests.

    Vitsios, Dimitrios M; Kentepozidou, Elissavet; Quintais, Leonor; Benito-Gutiérrez, Elia; van Dongen, Stijn; Davis, Matthew P; Enright, Anton J

    2017-12-01

    The discovery of microRNAs (miRNAs) remains an important problem, particularly given the growth of high-throughput sequencing, cell sorting and single cell biology. While a large number of miRNAs have already been annotated, there may well be large numbers of miRNAs that are expressed in very particular cell types and remain elusive. Sequencing allows us to quickly and accurately identify the expression of known miRNAs from small RNA-Seq data. The biogenesis of miRNAs leads to very specific characteristics observed in their sequences. In brief, miRNAs usually have a well-defined 5' end and a more flexible 3' end with the possibility of 3' tailing events, such as uridylation. Previous approaches to the prediction of novel miRNAs usually involve the analysis of structural features of miRNA precursor hairpin sequences obtained from genome sequence. We surmised that it may be possible to identify miRNAs by using these biogenesis features observed directly from sequenced reads, solely or in addition to structural analysis from genome data. To this end, we have developed mirnovo, a machine learning based algorithm, which is able to identify known and novel miRNAs in animals and plants directly from small RNA-Seq data, with or without a reference genome. This method performs comparably to existing tools, however is simpler to use with reduced run time. Its performance and accuracy has been tested on multiple datasets, including species with poorly assembled genomes, RNaseIII (Drosha and/or Dicer) deficient samples and single cells (at both embryonic and adult stage). © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

  12. Z-1 Prototype Space Suit Testing Summary

    Ross, Amy

    2013-01-01

    The Advanced Space Suit team of the NASA-Johnson Space Center performed a series of test with the Z-1 prototype space suit in 2012. This paper discusses, at a summary level, the tests performed and results from those tests. The purpose of the tests were two-fold: 1) characterize the suit performance so that the data could be used in the downselection of components for the Z-2 Space Suit and 2) develop interfaces with the suitport and exploration vehicles through pressurized suit evaluations. Tests performed included isolated and functional range of motion data capture, Z-1 waist and hip testing, joint torque testing, CO2 washout testing, fit checks and subject familiarizations, an exploration vehicle aft deck and suitport controls interface evaluation, delta pressure suitport tests including pressurized suit don and doff, and gross mobility and suitport ingress and egress demonstrations in reduced gravity. Lessons learned specific to the Z-1 prototype and to suit testing techniques will be presented.

  13. Wnt/catenin β1/microRNA 183 predicts recurrence and prognosis of patients with colorectal cancer.

    Chen, Yuzhuo; Song, Weiliang

    2018-04-01

    The present study assessed the association between the Wnt/catenin β1 (CTNNB1)/microRNA (miR)183 signaling pathway and the recurrence and prognosis of colorectal cancer. The expression of Wnt, CTNNB1 and miR183 in primary colorectal cancer tissue was increased compared with that in the paracarcinoma tissue. Disease-free survival and overall survival were decreased in patients with colorectal cancer and increased miR183 expression compared with those in patients with colorectal cancer and decreased miR183 expression. The human colorectal cancer cell line HCT-116 was treated with 5 µM inhibitor of Wnt response (IWR-2) for 24 h to inhibit Wnt protein expression. Downregulating Wnt and CTNNB1 expression inhibited the viability of, and induced cell death and caspase 3 protein expression in, HCT-116 cells. The expression of BCL2 associated X protein and miR183 was increased, and cyclin D1 protein expression was suppressed, by the downregulation of Wnt and CTNNB1 expression in HCT-116 cells. Collectively, the results of the present study suggested that the Wnt/CTNNB1/miR183 signaling pathway may represent a promising biomarker for the recurrence and prognosis of colorectal cancer.

  14. The Cancer Exome Generated by Alternative mRNA Splicing Dilutes Predicted HLA Class I Epitope Density

    Stranzl, Thomas; Larsen, Mette Voldby; Lund, Ole

    2012-01-01

    Several studies have shown that cancers actively regulate alternative splicing. Altered splicing mechanisms in cancer lead to cancer-specific transcripts different from the pool of transcripts occurring only in healthy tissue. At the same time, altered presentation of HLA class I epitopes...... is frequently observed in various types of cancer. Down-regulation of genes related to HLA class I antigen processing has been observed in several cancer types, leading to fewer HLA class I antigens on the cell surface. Here, we use a peptidome wide analysis of predicted alternative splice forms, based...... on a publicly available database, to show that peptides over-represented in cancer splice variants comprise significantly fewer predicted HLA class I epitopes compared to peptides from normal transcripts. Peptides over-represented in cancer transcripts are in the case of the three most common HLA class I...

  15. DNA Topoisomerase I Gene Copy Number and mRNA Expression Assessed as Predictive Biomarkers for Adjuvant Irinotecan in Stage II/III Colon Cancer

    Nygård, Sune Boris; Vainer, Ben; Nielsen, Signe L

    2016-01-01

    FISH and follow-up data were obtained from 534 patients. TOP1 gain was identified in 27 % using a single-probe enumeration strategy (≥ 4 TOP1 signals per cell), and in 31 % when defined by a TOP1/CEN20 ratio ≥ 1.5. The effect of additional irinotecan was not dependent on TOP1 FISH status. TOP1 m......PURPOSE: Prospective-retrospective assessment of the TOP1 gene copy number and TOP1 mRNA expression as predictive biomarkers for adjuvant irinotecan in stage II/III colon cancer (CC). EXPERIMENTAL DESIGN: Formalin-fixed, paraffin-embedded tissue microarrays were obtained from an adjuvant CC trial...... (PETACC3) where patients were randomized to 5-fluorouracil/folinic acid with or without additional irinotecan. TOP1 copy number status was analyzed by fluorescence in situ hybridization (FISH) using a TOP1/CEN20 dual-probe combination. TOP1 mRNA data were available from previous analyses. RESULTS: TOP1...

  16. Oracle SOA Suite 11g performance cookbook

    Brasier, Matthew; Wright, Nicholas

    2013-01-01

    This is a Cookbook with interesting, hands-on recipes, giving detailed descriptions and lots of practical walkthroughs for boosting the performance of your Oracle SOA Suite.This book is for Oracle SOA Suite 11g administrators, developers, and architects who want to understand how they can maximise the performance of their SOA Suite infrastructure. The recipes contain easy to follow step-by-step instructions and include many helpful and practical tips. It is suitable for anyone with basic operating system and application server administration experience.

  17. Harnessing NGS and Big Data Optimally: Comparison of miRNA Prediction from Assembled versus Non-assembled Sequencing Data--The Case of the Grass Aegilops tauschii Complex Genome.

    Budak, Hikmet; Kantar, Melda

    2015-07-01

    MicroRNAs (miRNAs) are small, endogenous, non-coding RNA molecules that regulate gene expression at the post-transcriptional level. As high-throughput next generation sequencing (NGS) and Big Data rapidly accumulate for various species, efforts for in silico identification of miRNAs intensify. Surprisingly, the effect of the input genomics sequence on the robustness of miRNA prediction was not evaluated in detail to date. In the present study, we performed a homology-based miRNA and isomiRNA prediction of the 5D chromosome of bread wheat progenitor, Aegilops tauschii, using two distinct sequence data sets as input: (1) raw sequence reads obtained from 454-GS FLX Titanium sequencing platform and (2) an assembly constructed from these reads. We also compared this method with a number of available plant sequence datasets. We report here the identification of 62 and 22 miRNAs from raw reads and the assembly, respectively, of which 16 were predicted with high confidence from both datasets. While raw reads promoted sensitivity with the high number of miRNAs predicted, 55% (12 out of 22) of the assembly-based predictions were supported by previous observations, bringing specificity forward compared to the read-based predictions, of which only 37% were supported. Importantly, raw reads could identify several repeat-related miRNAs that could not be detected with the assembly. However, raw reads could not capture 6 miRNAs, for which the stem-loops could only be covered by the relatively longer sequences from the assembly. In summary, the comparison of miRNA datasets obtained by these two strategies revealed that utilization of raw reads, as well as assemblies for in silico prediction, have distinct advantages and disadvantages. Consideration of these important nuances can benefit future miRNA identification efforts in the current age of NGS and Big Data driven life sciences innovation.

  18. The Los Alamos suite of relativistic atomic physics codes

    Fontes, C J; Zhang, H L; Jr, J Abdallah; Clark, R E H; Kilcrease, D P; Colgan, J; Cunningham, R T; Hakel, P; Magee, N H; Sherrill, M E

    2015-01-01

    The Los Alamos suite of relativistic atomic physics codes is a robust, mature platform that has been used to model highly charged ions in a variety of ways. The suite includes capabilities for calculating data related to fundamental atomic structure, as well as the processes of photoexcitation, electron-impact excitation and ionization, photoionization and autoionization within a consistent framework. These data can be of a basic nature, such as cross sections and collision strengths, which are useful in making predictions that can be compared with experiments to test fundamental theories of highly charged ions, such as quantum electrodynamics. The suite can also be used to generate detailed models of energy levels and rate coefficients, and to apply them in the collisional-radiative modeling of plasmas over a wide range of conditions. Such modeling is useful, for example, in the interpretation of spectra generated by a variety of plasmas. In this work, we provide a brief overview of the capabilities within the Los Alamos relativistic suite along with some examples of its application to the modeling of highly charged ions. (paper)

  19. Heat and mass transfer in air-fed pressurised suits

    Tesch, K.; Collins, M.W.; Karayiannis, T.G.; Atherton, M.A.; Edwards, P.

    2009-01-01

    Air-fed pressurised suits are used to protect workers against contamination and hazardous environments. The specific application here is the necessity for regular clean-up maintenance within the torus chamber of fusion reactors. The current design of suiting has been developed empirically. It is, therefore, very desirable to formulate a thermo-fluids model, which will be able to define optimum designs and operating parameters. Two factors indicate that the modelling should be as comprehensive as possible. Firstly, the overall thermo-fluids problem is three-dimensional and includes mass as well as heat transfer. The fluid field is complex, bounded on one side by the human body and on the other by what may be distensible, porous and multi-layer clothing. In this paper, we report firstly the modelling necessary for the additional mass and heat transport processes. This involves the use of Fick's and Fourier's laws and conjugate heat transfer. The results of an initial validation study are presented. Temperatures at the outlet of the suits were obtained experimentally and compared with those predicted by the overall CFD model. Realistic three-dimensional geometries were used for the suit and human body. Calculations were for turbulent flow with single- and two-component (species) models

  20. Phylogenetic Reconstruction of the Calosphaeriales and Togniniales Using Five Genes and Predicted RNA Secondary Structures of ITS, and Flabellascus tenuirostris gen. et sp. nov.

    Réblová, Martina; Jaklitsch, Walter M; Réblová, Kamila; Štěpánek, Václav

    2015-01-01

    The Calosphaeriales is revisited with new collection data, living cultures, morphological studies of ascoma centrum, secondary structures of the internal transcribed spacer (ITS) rDNA and phylogeny based on novel DNA sequences of five nuclear ribosomal and protein-coding loci. Morphological features, molecular evidence and information from predicted RNA secondary structures of ITS converged upon robust phylogenies of the Calosphaeriales and Togniniales. The current concept of the Calosphaeriales includes the Calosphaeriaceae and Pleurostomataceae encompassing five monophyletic genera, Calosphaeria, Flabellascus gen. nov., Jattaea, Pleurostoma and Togniniella, strongly supported by Bayesian and Maximum Likelihood methods. The structural elements of ITS1 form characteristic patterns that are phylogenetically conserved, corroborate observations based on morphology and have a high predictive value at the generic level. Three major clades containing 44 species of Phaeoacremonium were recovered in the closely related Togniniales based on ITS, actin and β-tubulin sequences. They are newly characterized by sexual and RNA structural characters and ecology. This approach is a first step towards understanding of the molecular systematics of Phaeoacremonium and possibly its new classification. In the Calosphaeriales, Jattaea aphanospora sp. nov. and J. ribicola sp. nov. are introduced, Calosphaeria taediosa is combined in Jattaea and epitypified. The sexual morph of Phaeoacremonium cinereum was encountered for the first time on decaying wood and obtained in vitro. In order to achieve a single nomenclature, the genera of asexual morphs linked with the Calosphaeriales are transferred to synonymy of their sexual morphs following the principle of priority, i.e. Calosphaeriophora to Calosphaeria, Phaeocrella to Togniniella and Pleurostomophora to Pleurostoma. Three new combinations are proposed, i.e. Pleurostoma ochraceum comb. nov., P. repens comb. nov. and P. richardsiae comb

  1. HPC Benchmark Suite NMx, Phase II

    National Aeronautics and Space Administration — In the phase II effort, Intelligent Automation Inc., (IAI) and University of Central Florida (UCF) propose to develop a comprehensive numerical test suite for...

  2. Coupled Human-Space Suit Mobility Studies

    National Aeronautics and Space Administration — Current EVA mobility studies only allow for comparisons of how the suit moves when actuated by a human and how the human moves when unsuited. There are now new...

  3. Strauss: Der Rosenkavalier - Suite / Michael Kennedy

    Kennedy, Michael

    1990-01-01

    Uuest heliplaadist "Strauss: Der Rosenkavalier - Suite, Salome-Dance of the seven veils, Capriccio-Prelude, Intermezzo, Morgen Mittag um elf! Felicity Lott, Scottish National Orchestra, Neeme Järvi" Chandos ABRD 1397. ABTD 1397. CHAN 8758

  4. Interoperative efficiency in minimally invasive surgery suites.

    van Det, M J; Meijerink, W J H J; Hoff, C; Pierie, J P E N

    2009-10-01

    Performing minimally invasive surgery (MIS) in a conventional operating room (OR) requires additional specialized equipment otherwise stored outside the OR. Before the procedure, the OR team must collect, prepare, and connect the equipment, then take it away afterward. These extra tasks pose a thread to OR efficiency and may lengthen turnover times. The dedicated MIS suite has permanently installed laparoscopic equipment that is operational on demand. This study presents two experiments that quantify the superior efficiency of the MIS suite in the interoperative period. Preoperative setup and postoperative breakdown times in the conventional OR and the MIS suite in an experimental setting and in daily practice were analyzed. In the experimental setting, randomly chosen OR teams simulated the setup and breakdown for a standard laparoscopic cholecystectomy (LC) and a complex laparoscopic sigmoid resection (LS). In the clinical setting, the interoperative period for 66 LCs randomly assigned to the conventional OR or the MIS suite were analyzed. In the experimental setting, the setup and breakdown times were significantly shorter in the MIS suite. The difference between the two types of OR increased for the complex procedure: 2:41 min for the LC (p < 0.001) and 10:47 min for the LS (p < 0.001). In the clinical setting, the setup and breakdown times as a whole were not reduced in the MIS suite. Laparoscopic setup and breakdown times were significantly shorter in the MIS suite (mean difference, 5:39 min; p < 0.001). Efficiency during the interoperative period is significantly improved in the MIS suite. The OR nurses' tasks are relieved, which may reduce mental and physical workload and improve job satisfaction and patient safety. Due to simultaneous tasks of other disciplines, an overall turnover time reduction could not be achieved.

  5. Space Suit Joint Torque Measurement Method Validation

    Valish, Dana; Eversley, Karina

    2012-01-01

    In 2009 and early 2010, a test method was developed and performed to quantify the torque required to manipulate joints in several existing operational and prototype space suits. This was done in an effort to develop joint torque requirements appropriate for a new Constellation Program space suit system. The same test method was levied on the Constellation space suit contractors to verify that their suit design met the requirements. However, because the original test was set up and conducted by a single test operator there was some question as to whether this method was repeatable enough to be considered a standard verification method for Constellation or other future development programs. In order to validate the method itself, a representative subset of the previous test was repeated, using the same information that would be available to space suit contractors, but set up and conducted by someone not familiar with the previous test. The resultant data was compared using graphical and statistical analysis; the results indicated a significant variance in values reported for a subset of the re-tested joints. Potential variables that could have affected the data were identified and a third round of testing was conducted in an attempt to eliminate and/or quantify the effects of these variables. The results of the third test effort will be used to determine whether or not the proposed joint torque methodology can be applied to future space suit development contracts.

  6. The ViennaRNA web services.

    Gruber, Andreas R; Bernhart, Stephan H; Lorenz, Ronny

    2015-01-01

    The ViennaRNA package is a widely used collection of programs for thermodynamic RNA secondary structure prediction. Over the years, many additional tools have been developed building on the core programs of the package to also address issues related to noncoding RNA detection, RNA folding kinetics, or efficient sequence design considering RNA-RNA hybridizations. The ViennaRNA web services provide easy and user-friendly web access to these tools. This chapter describes how to use this online platform to perform tasks such as prediction of minimum free energy structures, prediction of RNA-RNA hybrids, or noncoding RNA detection. The ViennaRNA web services can be used free of charge and can be accessed via http://rna.tbi.univie.ac.at.

  7. A Preoperative Measurement of Serum MicroRNA-125b May Predict the Presence of Microvascular Invasion in Hepatocellular Carcinomas Patients

    Mei Liu

    2016-06-01

    Full Text Available The high recurrence rate remains a major problem that strongly influenced the prognosis of hepatocellular carcinoma (HCC patients who received hepatectomy. The presence of microvascular invasion (MVI is regarded as the most important risk factor that contributes to the postoperative recurrence. Our previous study has hinted that serum microRNA-125b (miR-125b was associated with MVI. The aim of the present study was to identify whether serum miR-125b can serve as a biomarker to reliably predict microvascular invasion (MVI preoperatively. MiR-125b was quantified in 108 HCC patients’ serum before they received surgery by quantitative real-time PCR (qRT-PCR. Our results revealed that MVI was associated with relapse free survival (RFS of postoperative HCC patients; surgical margin width was associated with postoperative RFS in MVI present patients, but not in the patients without MVI. Multivariate analysis revealed that miR-125b, tumor size and AFP were the independent predictive factors associated with MVI in this cohort (P = .001, .001, .003, respectively. The probability of the predictive accuracy of miR-125b was 76.95% (51.32% specificity and 87.50% sensitivity, which was almost equal to the classifier established by combination of AFP and tumor size (78.82% probability, 65.63% specificity and 84.21% sensitivity. Furthermore, the combination of tumor size, AFP and miR-125b yielded a ROC curve area of 86.68% (72.37% specificity and 84.38% sensitivity. Our study indicated that serum miR-125b can be used to predict MVI of HCC patients before they received hepatic resection. Therefore, miR-125b can potentially guide individualized treatment, which helps HCC patients, with or without MVI, to benefit from different surgical approach.

  8. An RNA-Based Digital Circulating Tumor Cell Signature Is Predictive of Drug Response and Early Dissemination in Prostate Cancer.

    Miyamoto, David T; Lee, Richard J; Kalinich, Mark; LiCausi, Joseph A; Zheng, Yu; Chen, Tianqi; Milner, John D; Emmons, Erin; Ho, Uyen; Broderick, Katherine; Silva, Erin; Javaid, Sarah; Kwan, Tanya Todorova; Hong, Xin; Dahl, Douglas M; McGovern, Francis J; Efstathiou, Jason A; Smith, Matthew R; Sequist, Lecia V; Kapur, Ravi; Wu, Chin-Lee; Stott, Shannon L; Ting, David T; Giobbie-Hurder, Anita; Toner, Mehmet; Maheswaran, Shyamala; Haber, Daniel A

    2018-03-01

    Blood-based biomarkers are critical in metastatic prostate cancer, where characteristic bone metastases are not readily sampled, and they may enable risk stratification in localized disease. We established a sensitive and high-throughput strategy for analyzing prostate circulating tumor cells (CTC) using microfluidic cell enrichment followed by digital quantitation of prostate-derived transcripts. In a prospective study of 27 patients with metastatic castration-resistant prostate cancer treated with first-line abiraterone, pretreatment elevation of the digital CTC M score identifies a high-risk population with poor overall survival (HR = 6.0; P = 0.01) and short radiographic progression-free survival (HR = 3.2; P = 0.046). Expression of HOXB13 in CTCs identifies 6 of 6 patients with ≤12-month survival, with a subset also expressing the ARV7 splice variant. In a second cohort of 34 men with localized prostate cancer, an elevated preoperative CTC L score predicts microscopic dissemination to seminal vesicles and/or lymph nodes ( P digital quantitation of CTC-specific transcripts enables noninvasive monitoring that may guide treatment selection in both metastatic and localized prostate cancer. Significance: There is an unmet need for biomarkers to guide prostate cancer therapies, for curative treatment of localized cancer and for application of molecularly targeted agents in metastatic disease. Digital quantitation of prostate CTC-derived transcripts in blood specimens is predictive of abiraterone response in metastatic cancer and of early dissemination in localized cancer. Cancer Discov; 8(3); 288-303. ©2018 AACR. See related commentary by Heitzer and Speicher, p. 269 This article is highlighted in the In This Issue feature, p. 253 . ©2018 American Association for Cancer Research.

  9. RNA-TVcurve: a Web server for RNA secondary structure comparison based on a multi-scale similarity of its triple vector curve representation.

    Li, Ying; Shi, Xiaohu; Liang, Yanchun; Xie, Juan; Zhang, Yu; Ma, Qin

    2017-01-21

    RNAs have been found to carry diverse functionalities in nature. Inferring the similarity between two given RNAs is a fundamental step to understand and interpret their functional relationship. The majority of functional RNAs show conserved secondary structures, rather than sequence conservation. Those algorithms relying on sequence-based features usually have limitations in their prediction performance. Hence, integrating RNA structure features is very critical for RNA analysis. Existing algorithms mainly fall into two categories: alignment-based and alignment-free. The alignment-free algorithms of RNA comparison usually have lower time complexity than alignment-based algorithms. An alignment-free RNA comparison algorithm was proposed, in which novel numerical representations RNA-TVcurve (triple vector curve representation) of RNA sequence and corresponding secondary structure features are provided. Then a multi-scale similarity score of two given RNAs was designed based on wavelet decomposition of their numerical representation. In support of RNA mutation and phylogenetic analysis, a web server (RNA-TVcurve) was designed based on this alignment-free RNA comparison algorithm. It provides three functional modules: 1) visualization of numerical representation of RNA secondary structure; 2) detection of single-point mutation based on secondary structure; and 3) comparison of pairwise and multiple RNA secondary structures. The inputs of the web server require RNA primary sequences, while corresponding secondary structures are optional. For the primary sequences alone, the web server can compute the secondary structures using free energy minimization algorithm in terms of RNAfold tool from Vienna RNA package. RNA-TVcurve is the first integrated web server, based on an alignment-free method, to deliver a suite of RNA analysis functions, including visualization, mutation analysis and multiple RNAs structure comparison. The comparison results with two popular RNA

  10. Integration of Immune Cell Populations, mRNA-Seq, and CpG Methylation to Better Predict Humoral Immunity to Influenza Vaccination: Dependence of mRNA-Seq/CpG Methylation on Immune Cell Populations

    Gregory A. Poland

    2017-04-01

    lower performance (AUC = 0.67, but highlighted well-known mechanisms. Our analysis demonstrated that each of the three data sets (cell composition, mRNA-Seq, and DNA methylation may provide distinct information for the prediction of humoral immune response outcomes. We believe that these findings are important for the interpretation of current omics-based studies and set the stage for a more thorough understanding of interindividual immune responses to influenza vaccination.

  11. RNA Microarray Analysis of Macroscopically Normal Articular Cartilage from Knees Undergoing Partial Medial Meniscectomy: Potential Prediction of the Risk for Developing Osteoarthritis.

    Muhammad Farooq Rai

    Full Text Available (i To provide baseline knowledge of gene expression in macroscopically normal articular cartilage, (ii to test the hypothesis that age, body-mass-index (BMI, and sex are associated with cartilage RNA transcriptome, and (iii to predict individuals at potential risk for developing "pre-osteoarthritis" (OA based on screening of genetic risk-alleles associated with OA and gene transcripts differentially expressed between normal and OA cartilage.Healthy-appearing cartilage was obtained from the medial femoral notch of 12 knees with a meniscus tear undergoing arthroscopic partial meniscectomy. Cartilage had no radiographic, magnetic-resonance-imaging or arthroscopic evidence for degeneration. RNA was subjected to Affymetrix microarrays followed by validation of selected transcripts by microfluidic digital polymerase-chain-reaction. The underlying biological processes were explored computationally. Transcriptome-wide gene expression was probed for association with known OA genetic risk-alleles assembled from published literature and for comparison with gene transcripts differentially expressed between healthy and OA cartilage from other studies.We generated a list of 27,641 gene transcripts in healthy cartilage. Several gene transcripts representing numerous biological processes were correlated with age and BMI and differentially expressed by sex. Based on disease-specific Ingenuity Pathways Analysis, gene transcripts associated with aging were enriched for bone/cartilage disease while the gene expression profile associated with BMI was enriched for growth-plate calcification and OA. When segregated by genetic risk-alleles, two clusters of study patients emerged, one cluster containing transcripts predicted by risk studies. When segregated by OA-associated gene transcripts, three clusters of study patients emerged, one of which is remarkably similar to gene expression pattern in OA.Our study provides a list of gene transcripts in healthy

  12. RNA Crystallization

    Golden, Barbara L.; Kundrot, Craig E.

    2003-01-01

    RNA molecules may be crystallized using variations of the methods developed for protein crystallography. As the technology has become available to syntheisize and purify RNA molecules in the quantities and with the quality that is required for crystallography, the field of RNA structure has exploded. The first consideration when crystallizing an RNA is the sequence, which may be varied in a rational way to enhance crystallizability or prevent formation of alternate structures. Once a sequence has been designed, the RNA may be synthesized chemically by solid-state synthesis, or it may be produced enzymatically using RNA polymerase and an appropriate DNA template. Purification of milligram quantities of RNA can be accomplished by HPLC or gel electrophoresis. As with proteins, crystallization of RNA is usually accomplished by vapor diffusion techniques. There are several considerations that are either unique to RNA crystallization or more important for RNA crystallization. Techniques for design, synthesis, purification, and crystallization of RNAs will be reviewed here.

  13. Suites of dwarfs around Nearby giant galaxies

    Karachentsev, Igor D.; Kaisina, Elena I.; Makarov, Dmitry I.

    2014-01-01

    The Updated Nearby Galaxy Catalog (UNGC) contains the most comprehensive summary of distances, radial velocities, and luminosities for 800 galaxies located within 11 Mpc from us. The high density of observables in the UNGC makes this sample indispensable for checking results of N-body simulations of cosmic structures on a ∼1 Mpc scale. The environment of each galaxy in the UNGC was characterized by a tidal index Θ 1 , depending on the separation and mass of the galaxy's main disturber (MD). We grouped UNGC galaxies with a common MD in suites, and ranked suite members according to their Θ 1 . All suite members with positive Θ 1 are assumed to be physical companions of the MD. About 58% of the sample are members of physical groups. The distribution of suites by the number of members, n, follows a relation N(n) ∼ n –2 . The 20 most populated suites contain 468 galaxies, i.e., 59% of the UNGC sample. The fraction of MDs among the brightest galaxies is almost 100% and drops to 50% at M B = –18 m . We discuss various properties of MDs, as well as galaxies belonging to their suites. The suite abundance practically does not depend on the morphological type, linear diameter, or hydrogen mass of the MD, the tightest correlation being with the MD dynamical mass. Dwarf galaxies around MDs exhibit well-known segregation effects: the population of the outskirts has later morphological types, richer H I contents, and higher rates of star formation activity. Nevertheless, there are some intriguing cases where dwarf spheroidal galaxies occur at the far periphery of the suites, as well as some late-type dwarfs residing close to MDs. Comparing simulation results with galaxy groups, most studies assume the Local Group is fairly typical. However, we recognize that the nearby groups significantly differ from each other and there is considerable variation in their properties. The suites of companions around the Milky Way and M31, consisting of the Local Group, do not

  14. Semiautomated improvement of RNA alignments

    Andersen, Ebbe Sloth; Lind-Thomsen, Allan; Knudsen, Bjarne

    2007-01-01

    connects to external tools to provide a flexible semiautomatic editing environment. A new method, Pcluster, is introduced for dividing the sequences of an RNA alignment into subgroups with secondary structure differences. Pcluster was used to evaluate 574 seed alignments obtained from the Rfam database...... and we identified 71 alignments with significant prediction of inconsistent base pairs and 102 alignments with significant prediction of novel base pairs. Four RNA families were used to illustrate how SARSE can be used to manually or automatically correct the inconsistent base pairs detected by Pcluster......: the mir-399 RNA, vertebrate telomase RNA (vert-TR), bacterial transfer-messenger RNA (tmRNA), and the signal recognition particle (SRP) RNA. The general use of the method is illustrated by the ability to accommodate pseudoknots and handle even large and divergent RNA families. The open architecture...

  15. Z-2 Prototype Space Suit Development

    Ross, Amy; Rhodes, Richard; Graziosi, David; Jones, Bobby; Lee, Ryan; Haque, Bazle Z.; Gillespie, John W., Jr.

    2014-01-01

    NASA's Z-2 prototype space suit is the highest fidelity pressure garment from both hardware and systems design perspectives since the Space Shuttle Extravehicular Mobility Unit (EMU) was developed in the late 1970's. Upon completion the Z-2 will be tested in the 11 foot human-rated vacuum chamber and the Neutral Buoyancy Laboratory (NBL) at the NASA Johnson Space Center to assess the design and to determine applicability of the configuration to micro-, low- (asteroid), and planetary- (surface) gravity missions. This paper discusses the 'firsts' that the Z-2 represents. For example, the Z-2 sizes to the smallest suit scye bearing plane distance for at least the last 25 years and is being designed with the most intensive use of human models with the suit model.

  16. Advanced EVA Suit Camera System Development Project

    Mock, Kyla

    2016-01-01

    The National Aeronautics and Space Administration (NASA) at the Johnson Space Center (JSC) is developing a new extra-vehicular activity (EVA) suit known as the Advanced EVA Z2 Suit. All of the improvements to the EVA Suit provide the opportunity to update the technology of the video imagery. My summer internship project involved improving the video streaming capabilities of the cameras that will be used on the Z2 Suit for data acquisition. To accomplish this, I familiarized myself with the architecture of the camera that is currently being tested to be able to make improvements on the design. Because there is a lot of benefit to saving space, power, and weight on the EVA suit, my job was to use Altium Design to start designing a much smaller and simplified interface board for the camera's microprocessor and external components. This involved checking datasheets of various components and checking signal connections to ensure that this architecture could be used for both the Z2 suit and potentially other future projects. The Orion spacecraft is a specific project that may benefit from this condensed camera interface design. The camera's physical placement on the suit also needed to be determined and tested so that image resolution can be maximized. Many of the options of the camera placement may be tested along with other future suit testing. There are multiple teams that work on different parts of the suit, so the camera's placement could directly affect their research or design. For this reason, a big part of my project was initiating contact with other branches and setting up multiple meetings to learn more about the pros and cons of the potential camera placements we are analyzing. Collaboration with the multiple teams working on the Advanced EVA Z2 Suit is absolutely necessary and these comparisons will be used as further progress is made for the overall suit design. This prototype will not be finished in time for the scheduled Z2 Suit testing, so my time was

  17. RNA Origami

    Sparvath, Steffen Lynge

    introducerede vores gruppe den enkeltstrengede RNA-origami metode, der giver mulighed for cotranscriptional foldning af veldefinerede nanostrukturer, og er en central del af arbejdet præsenteret heri. Denne ph.d.-afhandling udforsker potentielle anvendelser af RNA-origami nanostrukturer, som nanomedicin eller...... biosensorer. Afhandlingen består af en introduktion til RNA-nanoteknologi feltet, en introduktion af enkeltstrenget RNA-origami design, og fire studier, der beskriver design, produktion og karakterisering af både strukturelle og funktionelle RNA-origamier. Flere RNA-origami designs er blevet undersøgt, og...... projekterne, der indgår i denne afhandling, inkluderer de nyeste fremskridt indenfor strukturel RNA-nanoteknologi og udvikling af funktionelle RNA-baserede enheder. Det første studie beskriver konstruktion og karakterisering af en enkeltstrenget 6-helix RNA-origami stuktur, som er den første demonstration af...

  18. RNA STRAND: The RNA Secondary Structure and Statistical Analysis Database

    Andronescu Mirela

    2008-08-01

    Full Text Available Abstract Background The ability to access, search and analyse secondary structures of a large set of known RNA molecules is very important for deriving improved RNA energy models, for evaluating computational predictions of RNA secondary structures and for a better understanding of RNA folding. Currently there is no database that can easily provide these capabilities for almost all RNA molecules with known secondary structures. Results In this paper we describe RNA STRAND – the RNA secondary STRucture and statistical ANalysis Database, a curated database containing known secondary structures of any type and organism. Our new database provides a wide collection of known RNA secondary structures drawn from public databases, searchable and downloadable in a common format. Comprehensive statistical information on the secondary structures in our database is provided using the RNA Secondary Structure Analyser, a new tool we have developed to analyse RNA secondary structures. The information thus obtained is valuable for understanding to which extent and with which probability certain structural motifs can appear. We outline several ways in which the data provided in RNA STRAND can facilitate research on RNA structure, including the improvement of RNA energy models and evaluation of secondary structure prediction programs. In order to keep up-to-date with new RNA secondary structure experiments, we offer the necessary tools to add solved RNA secondary structures to our database and invite researchers to contribute to RNA STRAND. Conclusion RNA STRAND is a carefully assembled database of trusted RNA secondary structures, with easy on-line tools for searching, analyzing and downloading user selected entries, and is publicly available at http://www.rnasoft.ca/strand.

  19. Immersion Suit Usage Within the RAAF

    1992-01-01

    IMMERSION SUIT USED UVIC QDIS HOLDINGS 202. in 12 Sizes, held by ALSS 492SQN REQUIREMENTS No comment USAGE POLICY REFERENCE DIRAF) AAP 7215.004-1 (P3C...held by ALSS 492SQN. REQUIREMENTS No comment ISACE POLICY REFERENCE DIIAF) AAP 7215.004-1 (P3C Flight Manual) RAAF Supplement No 92 USAGE POUICY UVIC...TYPE P3C REFERENCE Telecon FLTLT Toft I I SQNfRESO AVMED Dated 22 Mar 91 IMMERSION SUIT USED UVIC QDIS HOLDINGS No comment REQUIREMENTS No comment USAGE

  20. Advanced Sensor Platform to Evaluate Manloads for Exploration Suit Architectures

    National Aeronautics and Space Administration — Space suit manloads are defined as the outer bounds of force that the human occupant of a suit is able to exert onto the suit during motion. They are defined on a...

  1. What's New with MS Office Suites

    Goldsborough, Reid

    2012-01-01

    If one buys a new PC, laptop, or netbook computer today, it probably comes preloaded with Microsoft Office 2010 Starter Edition. This is a significantly limited, advertising-laden version of Microsoft's suite of productivity programs, Microsoft Office. This continues the trend of PC makers providing ever more crippled versions of Microsoft's…

  2. Antigravity Suits For Studies Of Weightlessness

    Kravik, Stein E.; Greenleaf, John

    1992-01-01

    Report presents results of research on use of "antigravity" suit, one applying positive pressure to lower body to simulate some effects of microgravity. Research suggests lower-body positive pressure is alternative to bed rest or immersion in water in terrestrial studies of cardioregulatory, renal, electrolyte, and hormonal changes induced in humans by microgravity.

  3. Prokofiev. "Romeo and Juliet" - Suites / Iran March

    March, Iran

    1991-01-01

    Uuest heliplaadist "Prokofiev. "Romeo and Juliet" - Suites: N 1 Op. 64 bis a; N 2 Op. 64 ter b; N 3 Op. 101 c. Royal Scottish National Orchestra /Neeme Järvi" Chandos cassette ABTD 1536; CD CHAN 8940 (78 minutes) etc

  4. A Suite of Tools for Technology Assessment

    2007-09-01

    Saden, Povinelli & Rosen, 1989). • This was a significant change in emphasis on the part of NASA, where technology had previously viewed as merely...Cost Analysis Symposium, April 13, 2005. A Suite of Tools for Technology Assessment 24 Bibliography - continued: • Sadin, Stanley T.; Povinelli

  5. 28 CFR 36.501 - Private suits.

    2010-07-01

    ... ACCOMMODATIONS AND IN COMMERCIAL FACILITIES Enforcement § 36.501 Private suits. (a) General. Any person who is... order. Upon timely application, the court may, in its discretion, permit the Attorney General to... general public importance. Upon application by the complainant and in such circumstances as the court may...

  6. Open architecture of smart sensor suites

    Müller, Wilmuth; Kuwertz, Achim; Grönwall, Christina; Petersson, Henrik; Dekker, Rob; Reinert, Frank; Ditzel, Maarten

    2017-10-01

    Experiences from recent conflicts show the strong need for smart sensor suites comprising different multi-spectral imaging sensors as core elements as well as additional non-imaging sensors. Smart sensor suites should be part of a smart sensor network - a network of sensors, databases, evaluation stations and user terminals. Its goal is to optimize the use of various information sources for military operations such as situation assessment, intelligence, surveillance, reconnaissance, target recognition and tracking. Such a smart sensor network will enable commanders to achieve higher levels of situational awareness. Within the study at hand, an open system architecture was developed in order to increase the efficiency of sensor suites. The open system architecture for smart sensor suites, based on a system-of-systems approach, enables combining different sensors in multiple physical configurations, such as distributed sensors, co-located sensors combined in a single package, tower-mounted sensors, sensors integrated in a mobile platform, and trigger sensors. The architecture was derived from a set of system requirements and relevant scenarios. Its mode of operation is adaptable to a series of scenarios with respect to relevant objects of interest, activities to be observed, available transmission bandwidth, etc. The presented open architecture is designed in accordance with the NATO Architecture Framework (NAF). The architecture allows smart sensor suites to be part of a surveillance network, linked e.g. to a sensor planning system and a C4ISR center, and to be used in combination with future RPAS (Remotely Piloted Aircraft Systems) for supporting a more flexible dynamic configuration of RPAS payloads.

  7. Statistical Evaluation of Causal Factors Associated with Astronaut Shoulder Injury in Space Suits.

    Anderson, Allison P; Newman, Dava J; Welsch, Roy E

    2015-07-01

    Shoulder injuries due to working inside the space suit are some of the most serious and debilitating injuries astronauts encounter. Space suit injuries occur primarily in the Neutral Buoyancy Laboratory (NBL) underwater training facility due to accumulated musculoskeletal stress. We quantitatively explored the underlying causal mechanisms of injury. Logistic regression was used to identify relevant space suit components, training environment variables, and anthropometric dimensions related to an increased propensity for space-suited injury. Two groups of subjects were analyzed: those whose reported shoulder incident is attributable to the NBL or working in the space suit, and those whose shoulder incidence began in active duty, meaning working in the suit could be a contributing factor. For both groups, percent of training performed in the space suit planar hard upper torso (HUT) was the most important predictor variable for injury. Frequency of training and recovery between training were also significant metrics. The most relevant anthropometric dimensions were bideltoid breadth, expanded chest depth, and shoulder circumference. Finally, record of previous injury was found to be a relevant predictor for subsequent injury. The first statistical model correctly identifies 39% of injured subjects, while the second model correctly identifies 68% of injured subjects. A review of the literature suggests this is the first work to quantitatively evaluate the hypothesized causal mechanisms of all space-suited shoulder injuries. Although limited in predictive capability, each of the identified variables can be monitored and modified operationally to reduce future impacts on an astronaut's health.

  8. ANALYSIS OF DESIGN ELEMENTS IN SKI SUITS

    Birsen Çileroğlu

    2014-06-01

    Full Text Available Popularity of Ski Sport in 19th century necessitated a new perspective on protective skiing clothing ag ainst the mountain climates and excessive cold. Winter clothing were the basis of ski attire during this period. By the beginning of 20th century lining cloth were used to minimize the wind effect. The difference between the men and women’s ski attire of the time consisted of a knee - length skirts worn over the golf trousers. Subsequent to the First World War, skiing suit models were influenced by the period uniforms and the producers reflected the fashion trends to the ski clothing. In conformance with th e prevailing trends, ski trousers were designed and produced for the women thus leading to reduction in gender differences. Increases in the ski tourism and holding of the first winter olympics in 1924 resulted in variations in ski attires, development of design characteristics, growth in user numbers, and enlargement of production capacities. Designers emphasized in their collections combined presence of elegance and practicality in the skiing attire. In 1930s, the ski suits influenced by pilots’ uniforms included characteristics permitting freedom of motion, and the design elements exhibited changes in terms of style, material and aerodynamics. In time, the ski attires showed varying design features distinguishing professionals from the amateurs. While protective functionality was primary consideration for the amateurs, for professionals the aerodynamic design was also a leading factor. Eventually, the increased differences in design characteristics were exhibited in ski suit collections, World reknown brands were formed, production and sales volumes showed significant rise. During 20th century the ski suits influenced by fashion trends to acquire unique styles reached a position of dominance to impact current fashion trends, and apart from sports attir es they became a style determinant in the clothing of cold climates. Ski suits

  9. Extending and Enhancing SAS (Static Analysis Suite)

    Ho, David

    2016-01-01

    The Static Analysis Suite (SAS) is an open-source software package used to perform static analysis on C and C++ code, helping to ensure safety, readability and maintainability. In this Summer Student project, SAS was enhanced to improve ease of use and user customisation. A straightforward method of integrating static analysis into a project at compilation time was provided using the automated build tool CMake. The process of adding checkers to the suite was streamlined and simplied by developing an automatic code generator. To make SAS more suitable for continuous integration, a reporting mechanism summarising results was added. This suitability has been demonstrated by inclusion of SAS in the Future Circular Collider Software nightly build system. Scalability of the improved package was demonstrated by using the tool to analyse the ROOT code base.

  10. Enhancements to the opera-3d suite

    Riley, C.P.

    1997-01-01

    The OPERA-3D suite of programs has been enhanced to include 2 additional 3 dimensional finite element based solvers, with complimentary features in the pre- and postprocessing. SOPRANO computes electromagnetic fields at high frequency including displacement current effects. It has 2 modules emdash a deterministic solution at a user defined frequency and an eigenvalue solution for modal analysis. It is suitable for designing microwave structures and cavities found in particle accelerators. SCALA computes electrostatic fields in the presence of space charge from charged particle beams. The user may define the emission characteristics of electrodes or plasma surfaces and compute the resultant space charge limited beams, including the presence of magnetic fields. Typical applications in particle accelerators are electron guns and ion sources. Other enhancements to the suite include additional capabilities in TOSCA and ELEKTRA, the static and dynamic solvers. copyright 1997 American Institute of Physics

  11. The BTeV Software Tutorial Suite

    Kutschke, Robert K.

    2004-01-01

    The BTeV Collaboration is starting to develop its C++ based offline software suite, an integral part of which is a series of tutorials. These tutorials are targeted at a diverse audience, including new graduate students, experienced physicists with little or no C++ experience, those with just enough C++ to be dangerous, and experts who need only an overview of the available tools. The tutorials must both teach C++ in general and the BTeV specific tools in particular. Finally, they must teach physicists how to find and use the detailed documentation. This report will review the status of the BTeV experiment, give an overview of the plans for and the state of the software and will then describe the plans for the tutorial suite

  12. Bacterial vaginosis, human papilloma virus and herpes viridae do not predict vaginal HIV RNA shedding in women living with HIV in Denmark

    Wessman, Maria; Thorsteinsson, Kristina; Jensen, Jørgen S

    2017-01-01

    in the genital tract despite undetectable HIV RNA plasma viral load. We examined the prevalence and diagnostic predictors of BV and HIV-1 RNA vaginal shedding in women living with HIV (WLWH) in Denmark, taking into account the presence of human papillomavirus (HPV) and herpes viridae. Methods: WLWH between 18...

  13. A new device for the inflation of the antigravity suit.

    Brodrick, P M

    1986-02-01

    The 'Schuco' orthopaedic tourniquet inflator can be simply converted into a suitable device for inflating an antigravity suit (G-suit). The antigravity suit may be used on neurosurgical patients undergoing procedures in the sitting position to help prevent hypotension and air embolism. The availability of this device may encourage the more widespread use of an antigravity suit in neuro-anaesthetic practice.

  14. The Apollo Number: space suits, self-support, and the walk-run transition.

    Christopher E Carr

    Full Text Available BACKGROUND: How space suits affect the preferred walk-run transition is an open question with relevance to human biomechanics and planetary extravehicular activity. Walking and running energetics differ; in reduced gravity (<0.5 g, running, unlike on Earth, uses less energy per distance than walking. METHODOLOGY/PRINCIPAL FINDINGS: The walk-run transition (denoted * correlates with the Froude Number (Fr = v(2/gL, velocity v, gravitational acceleration g, leg length L. Human unsuited Fr* is relatively constant (approximately 0.5 with gravity but increases substantially with decreasing gravity below approximately 0.4 g, rising to 0.9 in 1/6 g; space suits appear to lower Fr*. Because of pressure forces, space suits partially (1 g or completely (lunar-g support their own weight. We define the Apollo Number (Ap = Fr/M as an expected invariant of locomotion under manipulations of M, the ratio of human-supported to total transported mass. We hypothesize that for lunar suited conditions Ap* but not Fr* will be near 0.9, because the Apollo Number captures the effect of space suit self-support. We used the Apollo Lunar Surface Journal and other sources to identify 38 gait events during lunar exploration for which we could determine gait type (walk/lope/run and calculate Ap. We estimated the binary transition between walk/lope (0 and run (1, yielding Fr* (0.36+/-0.11, mean+/-95% CI and Ap* (0.68+/-0.20. CONCLUSIONS/SIGNIFICANCE: The Apollo Number explains 60% of the difference between suited and unsuited Fr*, appears to capture in large part the effects of space suits on the walk-run transition, and provides several testable predictions for space suit locomotion and, of increasing relevance here on Earth, exoskeleton locomotion. The knowledge of how space suits affect gait transitions can be used to optimize space suits for use on the Moon and Mars.

  15. Space suit bioenergetics: framework and analysis of unsuited and suited activity.

    Carr, Christopher E; Newman, Dava J

    2007-11-01

    Metabolic costs limit the duration and intensity of extravehicular activity (EVA), an essential component of future human missions to the Moon and Mars. Energetics Framework: We present a framework for comparison of energetics data across and between studies. This framework, applied to locomotion, differentiates between muscle efficiency and energy recovery, two concepts often confused in the literature. The human run-walk transition in Earth gravity occurs at the point for which energy recovery is approximately the same for walking and running, suggesting a possible role for recovery in gait transitions. Muscular Energetics: Muscle physiology limits the overall efficiency by which chemical energy is converted through metabolism to useful work. Unsuited Locomotion: Walking and running use different methods of energy storage and release. These differences contribute to the relative changes in the metabolic cost of walking and running as gravity is varied, with the metabolic cost of locomoting at a given velocity changing in proportion to gravity for running and less than in proportion for walking. Space Suits: Major factors affecting the energetic cost of suited movement include suit pressurization, gravity, velocity, surface slope, and space suit configuration. Apollo lunar surface EVA traverse metabolic rates, while unexpectedly low, were higher than other activity categories. The Lunar Roving Vehicle facilitated even lower metabolic rates, thus longer duration EVAs. Muscles and tendons act like springs during running; similarly, longitudinal pressure forces in gas pressure space suits allow spring-like storage and release of energy when suits are self-supporting.

  16. RNAcontext: a new method for learning the sequence and structure binding preferences of RNA-binding proteins.

    Hilal Kazan

    2010-07-01

    Full Text Available Metazoan genomes encode hundreds of RNA-binding proteins (RBPs. These proteins regulate post-transcriptional gene expression and have critical roles in numerous cellular processes including mRNA splicing, export, stability and translation. Despite their ubiquity and importance, the binding preferences for most RBPs are not well characterized. In vitro and in vivo studies, using affinity selection-based approaches, have successfully identified RNA sequence associated with specific RBPs; however, it is difficult to infer RBP sequence and structural preferences without specifically designed motif finding methods. In this study, we introduce a new motif-finding method, RNAcontext, designed to elucidate RBP-specific sequence and structural preferences with greater accuracy than existing approaches. We evaluated RNAcontext on recently published in vitro and in vivo RNA affinity selected data and demonstrate that RNAcontext identifies known binding preferences for several control proteins including HuR, PTB, and Vts1p and predicts new RNA structure preferences for SF2/ASF, RBM4, FUSIP1 and SLM2. The predicted preferences for SF2/ASF are consistent with its recently reported in vivo binding sites. RNAcontext is an accurate and efficient motif finding method ideally suited for using large-scale RNA-binding affinity datasets to determine the relative binding preferences of RBPs for a wide range of RNA sequences and structures.

  17. RNA-PAIRS: RNA probabilistic assignment of imino resonance shifts

    Bahrami, Arash; Clos, Lawrence J.; Markley, John L.; Butcher, Samuel E.; Eghbalnia, Hamid R.

    2012-01-01

    The significant biological role of RNA has further highlighted the need for improving the accuracy, efficiency and the reach of methods for investigating RNA structure and function. Nuclear magnetic resonance (NMR) spectroscopy is vital to furthering the goals of RNA structural biology because of its distinctive capabilities. However, the dispersion pattern in the NMR spectra of RNA makes automated resonance assignment, a key step in NMR investigation of biomolecules, remarkably challenging. Herein we present RNA Probabilistic Assignment of Imino Resonance Shifts (RNA-PAIRS), a method for the automated assignment of RNA imino resonances with synchronized verification and correction of predicted secondary structure. RNA-PAIRS represents an advance in modeling the assignment paradigm because it seeds the probabilistic network for assignment with experimental NMR data, and predicted RNA secondary structure, simultaneously and from the start. Subsequently, RNA-PAIRS sets in motion a dynamic network that reverberates between predictions and experimental evidence in order to reconcile and rectify resonance assignments and secondary structure information. The procedure is halted when assignments and base-parings are deemed to be most consistent with observed crosspeaks. The current implementation of RNA-PAIRS uses an initial peak list derived from proton-nitrogen heteronuclear multiple quantum correlation ( 1 H– 15 N 2D HMQC) and proton–proton nuclear Overhauser enhancement spectroscopy ( 1 H– 1 H 2D NOESY) experiments. We have evaluated the performance of RNA-PAIRS by using it to analyze NMR datasets from 26 previously studied RNAs, including a 111-nucleotide complex. For moderately sized RNA molecules, and over a range of comparatively complex structural motifs, the average assignment accuracy exceeds 90%, while the average base pair prediction accuracy exceeded 93%. RNA-PAIRS yielded accurate assignments and base pairings consistent with imino resonances for a

  18. RNA-PAIRS: RNA probabilistic assignment of imino resonance shifts

    Bahrami, Arash; Clos, Lawrence J.; Markley, John L.; Butcher, Samuel E. [National Magnetic Resonance Facility at Madison (United States); Eghbalnia, Hamid R., E-mail: eghbalhd@uc.edu [University of Cincinnati, Department of Molecular and Cellular Physiology (United States)

    2012-04-15

    The significant biological role of RNA has further highlighted the need for improving the accuracy, efficiency and the reach of methods for investigating RNA structure and function. Nuclear magnetic resonance (NMR) spectroscopy is vital to furthering the goals of RNA structural biology because of its distinctive capabilities. However, the dispersion pattern in the NMR spectra of RNA makes automated resonance assignment, a key step in NMR investigation of biomolecules, remarkably challenging. Herein we present RNA Probabilistic Assignment of Imino Resonance Shifts (RNA-PAIRS), a method for the automated assignment of RNA imino resonances with synchronized verification and correction of predicted secondary structure. RNA-PAIRS represents an advance in modeling the assignment paradigm because it seeds the probabilistic network for assignment with experimental NMR data, and predicted RNA secondary structure, simultaneously and from the start. Subsequently, RNA-PAIRS sets in motion a dynamic network that reverberates between predictions and experimental evidence in order to reconcile and rectify resonance assignments and secondary structure information. The procedure is halted when assignments and base-parings are deemed to be most consistent with observed crosspeaks. The current implementation of RNA-PAIRS uses an initial peak list derived from proton-nitrogen heteronuclear multiple quantum correlation ({sup 1}H-{sup 15}N 2D HMQC) and proton-proton nuclear Overhauser enhancement spectroscopy ({sup 1}H-{sup 1}H 2D NOESY) experiments. We have evaluated the performance of RNA-PAIRS by using it to analyze NMR datasets from 26 previously studied RNAs, including a 111-nucleotide complex. For moderately sized RNA molecules, and over a range of comparatively complex structural motifs, the average assignment accuracy exceeds 90%, while the average base pair prediction accuracy exceeded 93%. RNA-PAIRS yielded accurate assignments and base pairings consistent with imino

  19. NIH bows to part of Rifkin suit.

    Sun, M

    1984-11-30

    Having lost a round in its legal battle with Jeremy Rifkin over field tests of genetically engineered bacteria, the National Institutes of Health will conduct the simpler of two ecological analyses required by the National Environmental Policy Act on three proposed experiments. In May 1984 a federal district court ruling halted a University of California field test pending a decision on Rifkin's 1983 suit, which alleged that NIH had violated the Act by approving experiments without studying the ecological consequences. Still to be decided by the U.S. Court of Appeals is whether NIH must also issue full-scale environmental impact statements.

  20. Geophysical characterization from Itu intrusive suite

    Pascholati, M.E.

    1989-01-01

    The integrated use of geophysical, geological, geochemical, petrographical and remote sensing data resulted in a substantial increase in the knowledge of the Itu Intrusive Suite. The main geophysical method was gamma-ray spectrometry together with fluorimetry and autoradiography. Three methods were used for calculation of laboratory gamma-ray spectrometry data. For U, the regression method was the best one. For K and Th, equations system and absolute calibration presented the best results. Surface gamma-ray spectrometry allowed comparison with laboratory data and permitted important contribution to the study of environmental radiation. (author)

  1. Implementing Sentinels in the TARGIT BI Suite

    Middelfart, Morten; Pedersen, Torben Bach

    2011-01-01

    This paper describes the implementation of socalled sentinels in the TARGIT BI Suite. Sentinels are a novel type of rules that can warn a user if one or more measure changes in a multi-dimensional data cube are expected to cause a change to another measure critical to the user. Sentinels notify u...... pattern mining or correlation techniques. We demonstrate, through extensive experiments, that mining and usage of sentinels is feasible with good performance for the typical users on a real, operational data warehouse....

  2. ANALYSIS OF DESIGN ELEMENTS IN SKI SUITS

    Çileroğlu, Birsen; Kelleci Özeren, Figen; Kıvılcımlar, İnci Seda

    2015-01-01

    Popularity of Ski Sport in 19th century necessitated a new perspective on protective skiing clothing against the mountain climates and excessive cold. Winter clothing were the basis of ski attire during this period.  By the beginning of 20th century lining cloth were used to minimize the wind effect. The difference between the men and women’s ski attire of the time consisted of a knee-length skirts worn over the golf trousers.  Subsequent to the First World War, skiing suit models were influe...

  3. Hamp1 mRNA and plasma hepcidin levels are influenced by sex and strain but do not predict tissue iron levels in inbred mice.

    McLachlan, Stela; Page, Kathryn E; Lee, Seung-Min; Loguinov, Alex; Valore, Erika; Hui, Simon T; Jung, Grace; Zhou, Jie; Lusis, Aldons J; Fuqua, Brie; Ganz, Tomas; Nemeth, Elizabeta; Vulpe, Chris D

    2017-11-01

    Iron homeostasis is tightly regulated, and the peptide hormone hepcidin is considered to be a principal regulator of iron metabolism. Previous studies in a limited number of mouse strains found equivocal sex- and strain-dependent differences in mRNA and serum levels of hepcidin and reported conflicting data on the relationship between hepcidin ( Hamp1 ) mRNA levels and iron status. Our aim was to clarify the relationships between strain, sex, and hepcidin expression by examining multiple tissues and the effects of different dietary conditions in multiple inbred strains. Two studies were done: first, Hamp1 mRNA, liver iron, and plasma diferric transferrin levels were measured in 14 inbred strains on a control diet; and second, Hamp1 mRNA and plasma hepcidin levels in both sexes and iron levels in the heart, kidneys, liver, pancreas, and spleen in males were measured in nine inbred/recombinant inbred strains raised on an iron-sufficient or high-iron diet. Both sex and strain have a significant effect on both hepcidin mRNA (primarily a sex effect) and plasma hepcidin levels (primarily a strain effect). However, liver iron and diferric transferrin levels are not predictors of Hamp1 mRNA levels in mice fed iron-sufficient or high-iron diets, nor are the Hamp1 mRNA and plasma hepcidin levels good predictors of tissue iron levels, at least in males. We also measured plasma erythroferrone, performed RNA-sequencing analysis of liver samples from six inbred strains fed the iron-sufficient, low-iron, or high-iron diets, and explored differences in gene expression between the strains with the highest and lowest hepcidin levels. NEW & NOTEWORTHY Both sex and strain have a significant effect on both hepcidin mRNA (primarily a sex effect) and plasma hepcidin levels (primarily a strain effect). Liver iron and diferric transferrin levels are not predictors of Hamp1 mRNA levels in mice, nor are the Hamp1 mRNA and plasma hepcidin levels good predictors of tissue iron levels, at least

  4. Durable Suit Bladder with Improved Water Permeability for Pressure and Environment Suits

    Bue, Grant C.; Kuznetz, Larry; Orndoff, Evelyne; Tang, Henry; Aitchison, Lindsay; Ross, Amy

    2009-01-01

    Water vapor permeability is shown to be useful in rejecting heat and managing moisture accumulation in launch-and-entry pressure suits. Currently this is accomplished through a porous Gortex layer in the Advanced Crew and Escape Suit (ACES) and in the baseline design of the Constellation Suit System Element (CSSE) Suit 1. Non-porous dense monolithic membranes (DMM) that are available offer potential improvements for water vapor permeability with reduced gas leak. Accordingly, three different pressure bladder materials were investigated for water vapor permeability and oxygen leak: ElasthaneTM 80A (thermoplastic polyether urethane) provided from stock polymer material and two custom thermoplastic polyether urethanes. Water vapor, carbon dioxide and oxygen permeability of the DMM's was measured in a 0.13 mm thick stand-alone layer, a 0.08 mm and 0.05 mm thick layer each bonded to two different nylon and polyester woven reinforcing materials. Additional water vapor permeability and mechanical compression measurements were made with the reinforced 0.05 mm thick layers, further bonded with a polyester wicking and overlaid with moistened polyester fleece thermal underwear .This simulated the pressure from a supine crew person. The 0.05 mm thick nylon reinforced sample with polyester wicking layer was further mechanically tested for wear and abrasion. Concepts for incorporating these materials in launch/entry and Extravehicular Activity pressure suits are presented.

  5. Integrated Instrument Simulator Suites for Earth Science

    Tanelli, Simone; Tao, Wei-Kuo; Matsui, Toshihisa; Hostetler, Chris; Hair, John; Butler, Carolyn; Kuo, Kwo-Sen; Niamsuwan, Noppasin; Johnson, Michael P.; Jacob, Joseph C.; hide

    2012-01-01

    The NASA Earth Observing System Simulators Suite (NEOS3) is a modular framework of forward simulations tools for remote sensing of Earth's Atmosphere from space. It was initiated as the Instrument Simulator Suite for Atmospheric Remote Sensing (ISSARS) under the NASA Advanced Information Systems Technology (AIST) program of the Earth Science Technology Office (ESTO) to enable science users to perform simulations based on advanced atmospheric and simple land surface models, and to rapidly integrate in a broad framework any experimental or innovative tools that they may have developed in this context. The name was changed to NEOS3 when the project was expanded to include more advanced modeling tools for the surface contributions, accounting for scattering and emission properties of layered surface (e.g., soil moisture, vegetation, snow and ice, subsurface layers). NEOS3 relies on a web-based graphic user interface, and a three-stage processing strategy to generate simulated measurements. The user has full control over a wide range of customizations both in terms of a priori assumptions and in terms of specific solvers or models used to calculate the measured signals.This presentation will demonstrate the general architecture, the configuration procedures and illustrate some sample products and the fundamental interface requirements for modules candidate for integration.

  6. Freiburg RNA Tools: a web server integrating INTARNA, EXPARNA and LOCARNA.

    Smith, Cameron; Heyne, Steffen; Richter, Andreas S; Will, Sebastian; Backofen, Rolf

    2010-07-01

    The Freiburg RNA tools web server integrates three tools for the advanced analysis of RNA in a common web-based user interface. The tools IntaRNA, ExpaRNA and LocARNA support the prediction of RNA-RNA interaction, exact RNA matching and alignment of RNA, respectively. The Freiburg RNA tools web server and the software packages of the stand-alone tools are freely accessible at http://rna.informatik.uni-freiburg.de.

  7. MODEL: A software suite for data acquisition

    Sendall, D M; Boissat, C; Bozzoli, W; Burkimsher, P; Jones, R; Matheys, J P; Mornacchi, G; Nguyen, T; Vyvre, P vande; Vascotto, A; Weaver, D [European Organization for Nuclear Research, Geneva (Switzerland). DD Div.

    1989-12-01

    MODEL is a new suite of modular data-acquisition software. It is aimed at the needs of LEP experiments, and is also general enough to be more widely used. It can accomodate a variety of users styles. It runs on a set of loosely coupled processors, and makes use of the remote procedure call technique. Implemented originally for the VAX family, some of its services have already been extended to other systems, including embedded microprocessors. The software modules available include facilities for data-flow management, a framework for monitoring programs, a window-oriented human interface, an error message utility, a process control utility and a run control scheme. It is already in use in a variety of experiments, and is still under development in the light of user experience. (orig.).

  8. UniPOPS: Unified data reduction suite

    Maddalena, Ronald J.; Garwood, Robert W.; Salter, Christopher J.; Stobie, Elizabeth B.; Cram, Thomas R.; Morgan, Lorrie; Vance, Bob; Hudson, Jerome

    2015-03-01

    UniPOPS, a suite of programs and utilities developed at the National Radio Astronomy Observatory (NRAO), reduced data from the observatory's single-dish telescopes: the Tucson 12-m, the Green Bank 140-ft, and archived data from the Green Bank 300-ft. The primary reduction programs, 'line' (for spectral-line reduction) and 'condar' (for continuum reduction), used the People-Oriented Parsing Service (POPS) as the command line interpreter. UniPOPS unified previous analysis packages and provided new capabilities; development of UniPOPS continued within the NRAO until 2004 when the 12-m was turned over to the Arizona Radio Observatory (ARO). The submitted code is version 3.5 from 2004, the last supported by the NRAO.

  9. Vadose zone flow convergence test suite

    Butcher, B. T. [Savannah River Site (SRS), Aiken, SC (United States). Savannah River National Lab. (SRNL)

    2017-06-05

    Performance Assessment (PA) simulations for engineered disposal systems at the Savannah River Site involve highly contrasting materials and moisture conditions at and near saturation. These conditions cause severe convergence difficulties that typically result in unacceptable convergence or long simulation times or excessive analyst effort. Adequate convergence is usually achieved in a trial-anderror manner by applying under-relaxation to the Saturation or Pressure variable, in a series of everdecreasing RELAxation values. SRNL would like a more efficient scheme implemented inside PORFLOW to achieve flow convergence in a more reliable and efficient manner. To this end, a suite of test problems that illustrate these convergence problems is provided to facilitate diagnosis and development of an improved convergence strategy. The attached files are being transmitted to you describing the test problem and proposed resolution.

  10. Metallogenic aspects of Itu intrusive suite

    Amaral, G.; Pascholati, E.M.

    1990-01-01

    The integrated use of geological, geochemical, geophysical and remote sensing data is providing interesting new information on the metallogenic characteristics of the Itu Intrusive Suite. During World War II, up to 1959, a wolframite deposit was mined near the border of the northernmost body (Itupeva Granite). This deposit is formed by greisen veins associated with cassiterite and topaz, clearly linked with later phases of magmatic differentiation. Generally those veins are related to hydrothermal alteration of the granites and the above mentioned shear zone. U, Th and K determinations by field and laboratory gammaspectrometry were used for regional distribution analysis of those elements and its ratios and calculation of radioactivity heat production. In this aspects, the Itupeva Granite is the hottest and presents several anomalies in the Th/U ratio, indicative of late or post magmatic oxidation processes. (author)

  11. Specification for the VERA Depletion Benchmark Suite

    Kim, Kang Seog [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)

    2015-12-17

    CASL-X-2015-1014-000 iii Consortium for Advanced Simulation of LWRs EXECUTIVE SUMMARY The CASL neutronics simulator MPACT is under development for the neutronics and T-H coupled simulation for the pressurized water reactor. MPACT includes the ORIGEN-API and internal depletion module to perform depletion calculations based upon neutron-material reaction and radioactive decay. It is a challenge to validate the depletion capability because of the insufficient measured data. One of the detoured methods to validate it is to perform a code-to-code comparison for benchmark problems. In this study a depletion benchmark suite has been developed and a detailed guideline has been provided to obtain meaningful computational outcomes which can be used in the validation of the MPACT depletion capability.

  12. Downregulation of miR-99a/let-7c/miR-125b miRNA cluster predicts clinical outcome in patients with unresected malignant pleural mesothelioma.

    Truini, Anna; Coco, Simona; Nadal, Ernest; Genova, Carlo; Mora, Marco; Dal Bello, Maria Giovanna; Vanni, Irene; Alama, Angela; Rijavec, Erika; Biello, Federica; Barletta, Giulia; Merlo, Domenico Franco; Valentino, Alessandro; Ferro, Paola; Ravetti, Gian Luigi; Stigliani, Sara; Vigani, Antonella; Fedeli, Franco; Beer, David G; Roncella, Silvio; Grossi, Francesco

    2017-09-15

    Malignant pleural mesothelioma (MPM) is an aggressive tumor with a dismal overall survival (OS) and to date no molecular markers are available to guide patient management. This study aimed to identify a prognostic miRNA signature in MPM patients who did not undergo tumor resection. Whole miRNA profiling using a microarray platform was performed using biopsies on 27 unresected MPM patients with distinct clinical outcome: 15 patients had short survival (OS36 months). Three prognostic miRNAs (mir-99a, let-7c, and miR-125b) encoded at the same cluster (21q21) were selected for further validation and tested on publicly available miRNA sequencing data from 72 MPM patients with survival data. A risk model was built based on these 3 miRNAs that was validated by quantitative PCR in an independent set of 30 MPM patients. High-risk patients had shorter median OS (7.6 months) as compared with low-risk patients (median not reached). In the multivariate Cox model, a high-risk score was independently associated with shorter OS (HR=3.14; 95% CI, 1.18-8.34; P=0.022). Our study identified that the downregulation of the miR-99a/let-7/miR-125b miRNA cluster predicts poor outcome in unresected MPM.

  13. Analyzing the interactions of mRNAs, miRNAs, lncRNAs and circRNAs to predict competing endogenous RNA networks in glioblastoma.

    Yuan, Yang; Jiaoming, Li; Xiang, Wang; Yanhui, Liu; Shu, Jiang; Maling, Gou; Qing, Mao

    2018-05-01

    Cross-talk between competitive endogenous RNAs (ceRNAs) may play a critical role in revealing potential mechanisms of tumor development and physiology. Glioblastoma is the most common type of malignant primary brain tumor, and the mechanisms of tumor genesis and development in glioblastoma are unclear. Here, to investigate the role of non-coding RNAs and the ceRNA network in glioblastoma, we performed paired-end RNA sequencing and microarray analyses to obtain the expression profiles of mRNAs, lncRNAs, circRNAs and miRNAs. We identified that the expression of 501 lncRNAs, 1999 mRNAs, 2038 circRNAs and 143 miRNAs were often altered between glioblastoma and matched normal brain tissue. Gene ontology and Kyoto Encyclopedia of Genes and Genomes pathway analyses were performed on these differentially expressed mRNAs and miRNA-mediated target genes of lncRNAs and circRNAs. Furthermore, we used a multi-step computational framework and several bioinformatics methods to construct a ceRNA network combining mRNAs, miRNAs, lncRNAs and circRNA, based on co-expression analysis between the differentially expressed RNAs. We identified that plenty of lncRNAs, CircRNAs and their downstream target genes in the ceRNA network are related to glutamatergic synapse, suggesting that glutamate metabolism is involved in glioma biological functions. Our results will accelerate the understanding of tumorigenesis, cancer progression and even therapeutic targeting in glioblastoma.

  14. Instrumented Suit Hard Upper Torso (HUT) for Ergonomic Assessment

    National Aeronautics and Space Administration — It is well known that the EVA suit (EMU) has the potential to cause crew injury and decreased performance. Engineering data on the suit interaction of the human...

  15. Variable Vector Countermeasure Suit for Space Habitation and Exploration

    National Aeronautics and Space Administration — The "Variable Vector Countermeasure Suit (V2Suit) for Space Habitation and Exploration" is a visionary system concept that will revolutionize space missions by...

  16. Carbon Dioxide Washout Testing Using Various Inlet Vent Configurations in the Mark-III Space Suit

    Korona, F. Adam; Norcross, Jason; Conger, Bruce; Navarro, Moses

    2014-01-01

    Requirements for using a space suit during ground testing include providing adequate carbon dioxide (CO2) washout for the suited subject. Acute CO2 exposure can lead to symptoms including headache, dyspnea, lethargy, and eventually unconsciousness or even death. Symptoms depend on several factors including inspired partial pressure of CO2 (ppCO2), duration of exposure, metabolic rate of the subject, and physiological differences between subjects. Computational Fluid Dynamics (CFD) analysis has predicted that the configuration of the suit inlet vent has a significant effect on oronasal CO2 concentrations. The main objective of this test was to characterize inspired oronasal ppCO2 for a variety of inlet vent configurations in the Mark-III suit across a range of workload and flow rates. Data and trends observed during testing along with refined CFD models will be used to help design an inlet vent configuration for the Z-2 space suit. The testing methodology used in this test builds upon past CO2 washout testing performed on the Z-1 suit, Rear Entry I-Suit, and the Enhanced Mobility Advanced Crew Escape Suit. Three subjects performed two test sessions each in the Mark-III suit to allow for comparison between tests. Six different helmet inlet vent configurations were evaluated during each test session. Suit pressure was maintained at 4.3 psid. Suited test subjects walked on a treadmill to generate metabolic workloads of approximately 2000 and 3000 BTU/hr. Supply airflow rates of 6 and 4 actual cubic feet per minute were tested at each workload. Subjects wore an oronasal mask with an open port in front of the mouth and were allowed to breathe freely. Oronasal ppCO2 was monitored real-time via gas analyzers with sampling tubes connected to the oronasal mask. Metabolic rate was calculated from the CO2 production measured by an additional gas analyzer at the air outlet from the suit. Real-time metabolic rate measurements were used to adjust the treadmill workload to meet

  17. Circulating Tyrosinase and MART-1 mRNA does not Independently Predict Relapse or Survival in Patients with AJCC Stage I–II Melanoma

    Schmidt, Henrik; Sørensen, Boe S; Sjoegren, Pia

    2006-01-01

    The detection of melanoma cells in peripheral blood has been proposed to select patients with a high risk of relapse. In this study, tyrosinase and melanoma antigen recognized by T cells 1 (MART-1) mRNA expression was evaluated in serial samples obtained before definitive surgery and during follow......-up in patients with American Joint Committee on Cancer stage I-II melanoma. Serial samples (n=2,262) were collected from 236 patients from 1997 to 2002. Analyses of the RNA samples were performed with a calibrated reverse transcriptase-PCR assay. Gender, age, primary tumor site, ulceration, thickness, Clark...

  18. Infinity: An In-Silico Tool for Genome-Wide Prediction of Specific DNA Matrices in miRNA Genomic Loci.

    Falcone, Emmanuela; Grandoni, Luca; Garibaldi, Francesca; Manni, Isabella; Filligoi, Giancarlo; Piaggio, Giulia; Gurtner, Aymone

    2016-01-01

    miRNAs are potent regulators of gene expression and modulate multiple cellular processes in physiology and pathology. Deregulation of miRNAs expression has been found in various cancer types, thus, miRNAs may be potential targets for cancer therapy. However, the mechanisms through which miRNAs are regulated in cancer remain unclear. Therefore, the identification of transcriptional factor-miRNA crosstalk is one of the most update aspects of the study of miRNAs regulation. In the present study we describe the development of a fast and user-friendly software, named infinity, able to find the presence of DNA matrices, such as binding sequences for transcriptional factors, on ~65kb (kilobase) of 939 human miRNA genomic sequences, simultaneously. Of note, the power of this software has been validated in vivo by performing chromatin immunoprecipitation assays on a subset of new in silico identified target sequences (CCAAT) for the transcription factor NF-Y on colon cancer deregulated miRNA loci. Moreover, for the first time, we have demonstrated that NF-Y, through its CCAAT binding activity, regulates the expression of miRNA-181a, -181b, -21, -17, -130b, -301b in colon cancer cells. The infinity software that we have developed is a powerful tool to underscore new TF/miRNA regulatory networks. Infinity was implemented in pure Java using Eclipse framework, and runs on Linux and MS Windows machine, with MySQL database. The software is freely available on the web at https://github.com/bio-devel/infinity. The website is implemented in JavaScript, PHP and HTML with all major browsers supported.

  19. Infinity: An In-Silico Tool for Genome-Wide Prediction of Specific DNA Matrices in miRNA Genomic Loci.

    Emmanuela Falcone

    Full Text Available miRNAs are potent regulators of gene expression and modulate multiple cellular processes in physiology and pathology. Deregulation of miRNAs expression has been found in various cancer types, thus, miRNAs may be potential targets for cancer therapy. However, the mechanisms through which miRNAs are regulated in cancer remain unclear. Therefore, the identification of transcriptional factor-miRNA crosstalk is one of the most update aspects of the study of miRNAs regulation.In the present study we describe the development of a fast and user-friendly software, named infinity, able to find the presence of DNA matrices, such as binding sequences for transcriptional factors, on ~65kb (kilobase of 939 human miRNA genomic sequences, simultaneously. Of note, the power of this software has been validated in vivo by performing chromatin immunoprecipitation assays on a subset of new in silico identified target sequences (CCAAT for the transcription factor NF-Y on colon cancer deregulated miRNA loci. Moreover, for the first time, we have demonstrated that NF-Y, through its CCAAT binding activity, regulates the expression of miRNA-181a, -181b, -21, -17, -130b, -301b in colon cancer cells.The infinity software that we have developed is a powerful tool to underscore new TF/miRNA regulatory networks.Infinity was implemented in pure Java using Eclipse framework, and runs on Linux and MS Windows machine, with MySQL database. The software is freely available on the web at https://github.com/bio-devel/infinity. The website is implemented in JavaScript, PHP and HTML with all major browsers supported.

  20. Improved airline-type supplied-air plastic suit

    Jolley, L. Jr.; Zippler, D.B.; Cofer, C.H.; Harper, J.A.

    1978-06-01

    Two piece supplied-air plastic suits are used extensively at the Savannah River Plant for personnel protection against inhalation of airborne plutonium and tritium. Worker comfort and noise level problems gave impetus to development of an improved suit and aid distribution system. The resulting plastic suit and development work are discussed. The plastic suit unit cost is less than $20, the hearing zone noise level is less than 75 dBA, protection factors exceed 10,000, and user comfort is approved. This suit is expected to meet performance requirements for unrestricted use

  1. [Antigravity suit used for neurosurgical operations in sitting position].

    Szpiro-Zurkowska, A; Milczarek, Z; Marchel, A; Jagielski, J

    1996-01-01

    The aviator's antigravity suit (G-suit) was used for 40 operations on neurosurgical patients operated on in sitting position. The G-suit was filled with air to 0.2 atmosphere (20 kPa) pressure in 26 cases, and 0.3 atm. (30 kPa) in 14 cases. In all cases G-suit filling was followed by central venous pressure rise and mean arterial pressure rise. Venous air embolism was found in 5 (12.5%) patients. No other complications connected with the use of G-suit were observed.

  2. The Inelastic Instrument suite at the SNS

    Granroth, Garrett E; Abernathy, Douglas L; Ehlers, Georg; Hagen, Mark E; Herwig, Kenneth W; Mamontov, Eugene; Ohl, Michael E; Wildgruber, Christoph U

    2008-01-01

    The instruments in the extensive suite of spectrometers at the SNS are in various stages of installation and commissioning. The Back Scattering Spectrometer (BASIS) is installed and is in commissioning. It's near backscattering analyzer crystals provide the 3 eV resolution as expected. BASIS will enter the user program in the fall of 2007. The ARCS wide angular-range thermal to epithermal neutron spectrometer will come on line in the fall of 2007 followed shortly by the Cold Neutron Chopper Spectrometer. These two direct geometry instruments provide moderate resolution and the ability to trade resolution for flux. In addition both instruments have detector coverage out to 140o to provide a large Q range. The SEQUOIA spectrometer, complete in 2008, is the direct geometry instrument that will provide fine resolution in the thermal to epithermal range. The Spin-Echo spectrometer, to be completed on a similar time scale, will provide the finest energy resolution worldwide. The HYSPEC spectrometer, available no later than 2011, will provide polarized capabilities and optimized flux in the thermal energy range. Finally, the Vision chemical spectrometer will use crystal analyzers to study energy transfers into the epithermal range

  3. Automated Structure Solution with the PHENIX Suite

    Zwart, Peter H.; Zwart, Peter H.; Afonine, Pavel; Grosse-Kunstleve, Ralf W.; Hung, Li-Wei; Ioerger, Tom R.; McCoy, A.J.; McKee, Eric; Moriarty, Nigel; Read, Randy J.; Sacchettini, James C.; Sauter, Nicholas K.; Storoni, L.C.; Terwilliger, Tomas C.; Adams, Paul D.

    2008-06-09

    Significant time and effort are often required to solve and complete a macromolecular crystal structure. The development of automated computational methods for the analysis, solution and completion of crystallographic structures has the potential to produce minimally biased models in a short time without the need for manual intervention. The PHENIX software suite is a highly automated system for macromolecular structure determination that can rapidly arrive at an initial partial model of a structure without significant human intervention, given moderate resolution and good quality data. This achievement has been made possible by the development of new algorithms for structure determination, maximum-likelihood molecular replacement (PHASER), heavy-atom search (HySS), template and pattern-based automated model-building (RESOLVE, TEXTAL), automated macromolecular refinement (phenix.refine), and iterative model-building, density modification and refinement that can operate at moderate resolution (RESOLVE, AutoBuild). These algorithms are based on a highly integrated and comprehensive set of crystallographic libraries that have been built and made available to the community. The algorithms are tightly linked and made easily accessible to users through the PHENIX Wizards and the PHENIX GUI.

  4. Automated structure solution with the PHENIX suite

    Terwilliger, Thomas C [Los Alamos National Laboratory; Zwart, Peter H [LBNL; Afonine, Pavel V [LBNL; Grosse - Kunstleve, Ralf W [LBNL

    2008-01-01

    Significant time and effort are often required to solve and complete a macromolecular crystal structure. The development of automated computational methods for the analysis, solution, and completion of crystallographic structures has the potential to produce minimally biased models in a short time without the need for manual intervention. The PHENIX software suite is a highly automated system for macromolecular structure determination that can rapidly arrive at an initial partial model of a structure without significant human intervention, given moderate resolution, and good quality data. This achievement has been made possible by the development of new algorithms for structure determination, maximum-likelihood molecular replacement (PHASER), heavy-atom search (HySS), template- and pattern-based automated model-building (RESOLVE, TEXTAL), automated macromolecular refinement (phenix. refine), and iterative model-building, density modification and refinement that can operate at moderate resolution (RESOLVE, AutoBuild). These algorithms are based on a highly integrated and comprehensive set of crystallographic libraries that have been built and made available to the community. The algorithms are tightly linked and made easily accessible to users through the PHENIX Wizards and the PHENIX GUI.

  5. The Variable Vector Countermeasure Suit (V2Suit for Space Habitation and Exploration

    Kevin R Duda

    2015-04-01

    Full Text Available The Variable Vector Countermeasure Suit (V2Suit for Space Habitation and Exploration is a novel system concept that provides a platform for integrating sensors and actuators with daily astronaut intravehicular activities to improve health and performance, while reducing the mass and volume of the physiologic adaptation countermeasure systems, as well as the required exercise time during long-duration space exploration missions. The V2Suit system leverages wearable kinematic monitoring technology and uses inertial measurement units (IMUs and control moment gyroscopes (CMGs within miniaturized modules placed on body segments to provide a viscous resistance during movements against a specified direction of down – initially as a countermeasure to the sensorimotor adaptation performance decrements that manifest themselves while living and working in microgravity and during gravitational transitions during long-duration spaceflight, including post-flight recovery and rehabilitation. Several aspects of the V2Suit system concept were explored and simulated prior to developing a brassboard prototype for technology demonstration. This included a system architecture for identifying the key components and their interconnects, initial identification of key human-system integration challenges, development of a simulation architecture for CMG selection and parameter sizing, and the detailed mechanical design and fabrication of a module. The brassboard prototype demonstrates closed-loop control from down initialization through CMG actuation, and provides a research platform for human performance evaluations to mitigate sensorimotor adaptation, as well as a tool for determining the performance requirements when used as a musculoskeletal deconditioning countermeasure. This type of countermeasure system also has Earth benefits, particularly in gait or movement stabilization and rehabilitation.

  6. Intracellular human papillomavirus E6, E7 mRNA quantification predicts CIN 2+ in cervical biopsies better than Papanicolaou screening for women regardless of age.

    Pierry, Deirdre; Weiss, Gerald; Lack, Benjamin; Chen, Victor; Fusco, Judy

    2012-08-01

    Cervical cancer screening in women younger than 30 years relies on cervical cytology because of the poor performance of human papillomavirus (HPV) DNA testing in this age group. To determine the performance of in-cell HPV E6, E7 mRNA quantification (HPV OncoTect) for the detection of high-grade cervical intraepithelial neoplasia in women younger than 30 years. We analyzed 3133 cytology specimens from a screening population of women aged 19-75 years investigate HPV OncoTect as a triage/secondary screening test for atypical squamous cells of undetermined significance (ASCUS) and low-grade squamous intraepithelial lesion (LSIL) cytology in women younger than 30 years. Test results were compared to histology in 246 cases. The sensitivity of E6, E7 mRNA was 89% for CIN 2+ and 100% for CIN 3+ lesions in women 30 years and older. In women younger than 30 years, the sensitivity of E6, E7 mRNA for CIN 2+ lesions was 88% for CIN 2+ and 92% for CIN 3+ lesions. Abnormal cytology (≥ASCUS) exhibited a sensitivity of 89% for CIN 2+ and 100% for CIN 3+ in women 30 years and older and 96% sensitivity for CIN 2+ and 93% sensitivity for CIN 3+ in women younger than 30. The specificity of E6, E7 mRNA was >80% for CIN 2+ and CIN 3+ in both groups of women compared to a specificity of abnormal cytology of ASCUS/LSIL triage in women including those younger than 30 years.

  7. Automated integration of lidar into the LANDFIRE product suite

    Peterson, Birgit; Nelson, Kurtis; Seielstad, Carl; Stoker, Jason M.; Jolly, W. Matt; Parsons, Russell

    2015-01-01

    Accurate information about three-dimensional canopy structure and wildland fuel across the landscape is necessary for fire behaviour modelling system predictions. Remotely sensed data are invaluable for assessing these canopy characteristics over large areas; lidar data, in particular, are uniquely suited for quantifying three-dimensional canopy structure. Although lidar data are increasingly available, they have rarely been applied to wildland fuels mapping efforts, mostly due to two issues. First, the Landscape Fire and Resource Planning Tools (LANDFIRE) program, which has become the default source of large-scale fire behaviour modelling inputs for the US, does not currently incorporate lidar data into the vegetation and fuel mapping process because spatially continuous lidar data are not available at the national scale. Second, while lidar data are available for many land management units across the US, these data are underutilized for fire behaviour applications. This is partly due to a lack of local personnel trained to process and analyse lidar data. This investigation addresses these issues by developing the Creating Hybrid Structure from LANDFIRE/lidar Combinations (CHISLIC) tool. CHISLIC allows individuals to automatically generate a suite of vegetation structure and wildland fuel parameters from lidar data and infuse them into existing LANDFIRE data sets. CHISLIC will become available for wider distribution to the public through a partnership with the U.S. Forest Service’s Wildland Fire Assessment System (WFAS) and may be incorporated into the Wildland Fire Decision Support System (WFDSS) with additional design and testing. WFAS and WFDSS are the primary systems used to support tactical and strategic wildland fire management decisions.

  8. The ESA's Space Trajectory Analysis software suite

    Ortega, Guillermo

    The European Space Agency (ESA) initiated in 2005 an internal activity to develop an open source software suite involving university science departments and research institutions all over the world. This project is called the "Space Trajectory Analysis" or STA. This article describes the birth of STA and its present configuration. One of the STA aims is to promote the exchange of technical ideas, and raise knowledge and competence in the areas of applied mathematics, space engineering, and informatics at University level. Conceived as a research and education tool to support the analysis phase of a space mission, STA is able to visualize a wide range of space trajectories. These include among others ascent, re-entry, descent and landing trajectories, orbits around planets and moons, interplanetary trajectories, rendezvous trajectories, etc. The article explains that STA project is an original idea of the Technical Directorate of ESA. It was born in August 2005 to provide a framework in astrodynamics research at University level. As research and education software applicable to Academia, a number of Universities support this development by joining ESA in leading the development. ESA and Universities partnership are expressed in the STA Steering Board. Together with ESA, each University has a chair in the board whose tasks are develop, control, promote, maintain, and expand the software suite. The article describes that STA provides calculations in the fields of spacecraft tracking, attitude analysis, coverage and visibility analysis, orbit determination, position and velocity of solar system bodies, etc. STA implements the concept of "space scenario" composed of Solar system bodies, spacecraft, ground stations, pads, etc. It is able to propagate the orbit of a spacecraft where orbital propagators are included. STA is able to compute communication links between objects of a scenario (coverage, line of sight), and to represent the trajectory computations and

  9. OCAMS: The OSIRIS-REx Camera Suite

    Rizk, B.; Drouet d'Aubigny, C.; Golish, D.; Fellows, C.; Merrill, C.; Smith, P.; Walker, M. S.; Hendershot, J. E.; Hancock, J.; Bailey, S. H.; DellaGiustina, D. N.; Lauretta, D. S.; Tanner, R.; Williams, M.; Harshman, K.; Fitzgibbon, M.; Verts, W.; Chen, J.; Connors, T.; Hamara, D.; Dowd, A.; Lowman, A.; Dubin, M.; Burt, R.; Whiteley, M.; Watson, M.; McMahon, T.; Ward, M.; Booher, D.; Read, M.; Williams, B.; Hunten, M.; Little, E.; Saltzman, T.; Alfred, D.; O'Dougherty, S.; Walthall, M.; Kenagy, K.; Peterson, S.; Crowther, B.; Perry, M. L.; See, C.; Selznick, S.; Sauve, C.; Beiser, M.; Black, W.; Pfisterer, R. N.; Lancaster, A.; Oliver, S.; Oquest, C.; Crowley, D.; Morgan, C.; Castle, C.; Dominguez, R.; Sullivan, M.

    2018-02-01

    The OSIRIS-REx Camera Suite (OCAMS) will acquire images essential to collecting a sample from the surface of Bennu. During proximity operations, these images will document the presence of satellites and plumes, record spin state, enable an accurate model of the asteroid's shape, and identify any surface hazards. They will confirm the presence of sampleable regolith on the surface, observe the sampling event itself, and image the sample head in order to verify its readiness to be stowed. They will document Bennu's history as an example of early solar system material, as a microgravity body with a planetesimal size-scale, and as a carbonaceous object. OCAMS is fitted with three cameras. The MapCam will record color images of Bennu as a point source on approach to the asteroid in order to connect Bennu's ground-based point-source observational record to later higher-resolution surface spectral imaging. The SamCam will document the sample site before, during, and after it is disturbed by the sample mechanism. The PolyCam, using its focus mechanism, will observe the sample site at sub-centimeter resolutions, revealing surface texture and morphology. While their imaging requirements divide naturally between the three cameras, they preserve a strong degree of functional overlap. OCAMS and the other spacecraft instruments will allow the OSIRIS-REx mission to collect a sample from a microgravity body on the same visit during which it was first optically acquired from long range, a useful capability as humanity reaches out to explore near-Earth, Main-Belt and Jupiter Trojan asteroids.

  10. Vehicle-network defensive aids suite

    Rapanotti, John

    2005-05-01

    Defensive Aids Suites (DAS) developed for vehicles can be extended to the vehicle network level. The vehicle network, typically comprising four platoon vehicles, will benefit from improved communications and automation based on low latency response to threats from a flexible, dynamic, self-healing network environment. Improved DAS performance and reliability relies on four complementary sensor technologies including: acoustics, visible and infrared optics, laser detection and radar. Long-range passive threat detection and avoidance is based on dual-purpose optics, primarily designed for manoeuvring, targeting and surveillance, combined with dazzling, obscuration and countermanoeuvres. Short-range active armour is based on search and track radar and intercepting grenades to defeat the threat. Acoustic threat detection increases the overall robustness of the DAS and extends the detection range to include small calibers. Finally, detection of active targeting systems is carried out with laser and radar warning receivers. Synthetic scene generation will provide the integrated environment needed to investigate, develop and validate these new capabilities. Computer generated imagery, based on validated models and an acceptable set of benchmark vignettes, can be used to investigate and develop fieldable sensors driven by real-time algorithms and countermeasure strategies. The synthetic scene environment will be suitable for sensor and countermeasure development in hardware-in-the-loop simulation. The research effort focuses on two key technical areas: a) computing aspects of the synthetic scene generation and b) and development of adapted models and databases. OneSAF is being developed for research and development, in addition to the original requirement of Simulation and Modelling for Acquisition, Rehearsal, Requirements and Training (SMARRT), and is becoming useful as a means for transferring technology to other users, researchers and contractors. This procedure

  11. Advanced Sensor Platform to Evaluate Manloads For Exploration Suit Architectures

    McFarland, Shane; Pierce, Gregory

    2016-01-01

    Space suit manloads are defined as the outer bounds of force that the human occupant of a suit is able to exert onto the suit during motion. They are defined on a suit-component basis as a unit of maximum force that the suit component in question must withstand without failure. Existing legacy manloads requirements are specific to the suit architecture of the EMU and were developed in an iterative fashion; however, future exploration needs dictate a new suit architecture with bearings, load paths, and entry capability not previously used in any flight suit. No capability currently exists to easily evaluate manloads imparted by a suited occupant, which would be required to develop requirements for a flight-rated design. However, sensor technology has now progressed to the point where an easily-deployable, repeatable and flexible manloads measuring technique could be developed leveraging recent advances in sensor technology. INNOVATION: This development positively impacts schedule, cost and safety risk associated with new suit exploration architectures. For a final flight design, a comprehensive and accurate man loads requirements set must be communicated to the contractor; failing that, a suit design which does not meet necessary manloads limits is prone to failure during testing or worse, during an EVA, which could cause catastrophic failure of the pressure garment posing risk to the crew. This work facilitates a viable means of developing manloads requirements using a range of human sizes & strengths. OUTCOME / RESULTS: Performed sensor market research. Highlighted three viable options (primary, secondary, and flexible packaging option). Designed/fabricated custom bracket to evaluate primary option on a single suit axial. Manned suited manload testing completed and general approach verified.

  12. RNA oxidation

    Kjaer, L. K.; Cejvanovic, V.; Henriken, T.

    2015-01-01

    .9 significant hazard ratio for death compared with the quartile with the lowest 8oxoGuo excretion when adjusted for age, sex, BMI, smoker status, s-HbA1c, urine protein excretion and s-cholesterol. We conclude that it is now established that RNA oxidation is an independent risk factor for death in type 2...

  13. An overview of recent projects to study thermal protection in life rafts, lifeboats and immersion suits

    Mak, L.; DuCharme, M. B.; Farnworth, B.; Wissler, E. H.; Brown, R.; Kuczora, A. [Maritime and Arctic Survival Scientific and Engineering Ressearch Team (Canada)

    2011-07-01

    Survival during a marine evacuation in cold regions is very challenging. However international regulations do not require specific thermal protection or ventilation performance criteria for lifeboats. In the same way, the testing methods for approval testing of immersion suits are not standardised. This paper investigated recent projects completed or on-going to study thermal protection in life rafts, lifeboats and immersion suits. An overview of several projects from the Maritime and Arctic Survival Scientific and Engineering Research Team (MASSERT) was conducted. This review provided the necessary knowledge to advance international standards and develop the thermal protection requirements for survival in the Arctic. The results showed the MASSERT correlated thermal insulation values between human subjects and thermal manikins in life rafts and in immersion suits. It was found that the manikins are a valuable evaluation tool, as well as the computerised models used as prediction tools.

  14. Overexpression of long non-coding RNA TUG1 predicts poor prognosis and promotes cancer cell proliferation and migration in high-grade muscle-invasive bladder cancer.

    Iliev, Robert; Kleinova, Renata; Juracek, Jaroslav; Dolezel, Jan; Ozanova, Zuzana; Fedorko, Michal; Pacik, Dalibor; Svoboda, Marek; Stanik, Michal; Slaby, Ondrej

    2016-10-01

    Long non-coding RNA TUG1 is involved in the development and progression of a variety of tumors. Little is known about TUG1 function in high-grade muscle-invasive bladder cancer (MIBC). The aims of our study were to determine expression levels of long non-coding RNA TUG1 in tumor tissue, to evaluate its relationship with clinico-pathological features of high-grade MIBC, and to describe its function in MIBC cells in vitro. TUG1 expression levels were determined in paired tumor and adjacent non-tumor bladder tissues of 47 patients with high-grade MIBC using real-time PCR. Cell line T-24 and siRNA silencing were used to study the TUG1 function in vitro. We observed significantly increased levels of TUG1 in tumor tissue in comparison to adjacent non-tumor bladder tissue (P TUG1 levels were significantly increased in metastatic tumors (P = 0.0147) and were associated with shorter overall survival of MIBC patients (P = 0.0241). TUG1 silencing in vitro led to 34 % decrease in cancer cell proliferation (P = 0.0004) and 23 % reduction in migration capacity of cancer cells (P TUG1 silencing on cell cycle distribution and number of apoptotic cells. Our study confirmed overexpression of TUG1 in MIBC tumor tissue and described its association with worse overall survival in high-grade MIBC patients. Together with in vitro observations, these data suggest an oncogenic role of TUG1 and its potential usage as biomarker or therapeutic target in MIBC.

  15. Innovative technology summary report: Sealed-seam sack suits

    1998-09-01

    Sealed-seam sack suits are an improved/innovative safety and industrial hygiene technology designed to protect workers from dermal exposure to contamination. Most of these disposable, synthetic-fabric suits are more protective than cotton suits, and are also water-resistant and gas permeable. Some fabrics provide a filter to aerosols, which is important to protection against contamination, while allowing air to pass, increasing comfort level of workers. It is easier to detect body-moisture breakthrough with the disposable suits than with cotton, which is also important to protecting workers from contamination. These suits present a safe and cost-effective (6% to 17% less expensive than the baseline) alternative to traditional protective clothing. This report covers the period from October 1996 to August 1997. During that time, sealed-seam sack suits were demonstrated during daily activities under normal working conditions at the C Reactor and under environmentally controlled conditions at the Los Alamos National Laboratory (LANL)

  16. Alterations in MAST suit pressure with changes in ambient temperature.

    Sanders, A B; Meislin, H W; Daub, E

    1983-01-01

    A study was undertaken to test the hypothesis that change in ambient air temperature has an effect on MAST suit pressure according to the ideal gas law. Two different MAST suits were tested on Resusci-Annie dummies. The MAST suits were applied in a cold room at 4.4 degrees C and warmed to 44 degrees C. Positive linear correlations were found in nine trials, but the two suits differed in their rate of increase in pressure. Three trials using humans were conducted showing increased pressure with temperature but at a lesser rate than with dummies. A correlation of 0.5 to 1.0 mm Hg increase in MAST suit pressure for each 1.0 degrees C increase in ambient temperature was found. Implications are discussed for the use of the MAST suit in environmental conditions where the temperature changes.

  17. Problem of Office Suite Training at the University

    Natalia A. Nastashchuk

    2013-01-01

    Full Text Available Te paper considers the problem of office suite applications training, caused by a rapid change of their versions, variety of software developers and a rapid development of software and hardware platforms. The content of office suite applications training, based on the system of office suite notions, its basic functional and standards of information technologies development (OpenDocument Format Standard, ISO 26300-200Х is presented.

  18. Do circulating long non-coding RNAs (lncRNAs) (LincRNA-p21, GAS 5, HOTAIR) predict the treatment response in patients with head and neck cancer treated with chemoradiotherapy?

    Fayda, Merdan; Isin, Mustafa; Tambas, Makbule; Guveli, Murat; Meral, Rasim; Altun, Musa; Sahin, Dilek; Ozkan, Gozde; Sanli, Yasemin; Isin, Husniye; Ozgur, Emre; Gezer, Ugur

    2016-03-01

    Long non-coding RNAs (lncRNAs) have been shown to be aberrantly expressed in head and neck cancer (HNC). The aim of the present study was to evaluate plasma levels of three lncRNA molecules (lincRNA-p21, GAS5, and HOTAIR) in the treatment response in HNC patients treated with radical chemoradiotherapy (CRT). Forty-one patients with HNC were enrolled in the study. Most of the patients had nasopharyngeal carcinoma (n = 27, 65.9 %) and locally advanced disease. Blood was drawn at baseline and treatment evaluation 4.5 months after therapy. lncRNAs in plasma were measured by semiquantitative PCR. Treatment response was evaluated according to clinical examination, RECIST and PERCIST criteria based on magnetic resonance imaging (MRI), and positron emission tomography with computed tomography (PET/CT) findings. Complete response (CR) rates were 73.2, 36.6, and 50 % for clinical investigation, PET/CT-, or MRI-based response evaluation, respectively. Predictive value of lncRNAs was investigated in patients with CR vs. those with partial response (PR)/progressive disease (PD). We found that post-treatment GAS5 levels in patients with PR/PD were significantly higher compared with patients with CR based on clinical investigation (p = 0.01). Receiver operator characteristic (ROC) analysis showed that at a cutoff value of 0.3 of GAS5, sensitivity and specificity for clinical tumor response were 82 and 77 %, respectively. Interestingly, pretreatment GAS5 levels were significantly increased in patients with PR/PD compared to those with CR upon MRI-based response evaluation (p = 0.042). In contrast to GAS5, pretreatment or post-treatment lincRNA-p21 and HOTAIR levels were not informative for treatment response. Our results suggest that circulating GAS5 could be a biomarker in predicting treatment response in HNC patients.

  19. Miniature Flexible Humidity Sensitive Patches for Space Suits, Phase I

    National Aeronautics and Space Administration — Advanced space suit technologies demand improved, simplified, long-life regenerative sensing technologies, including humidity sensors, that exceed the performance of...

  20. Leveraging Active Knit Technologies for Aerospace Pressure Suit Applications

    National Aeronautics and Space Administration — Anti-Gravity Suits (AGS) are garments used in astronautics to prevent crew from experiencing orthostatic intolerance (OI) and consequential blackouts while...

  1. Pyrite footprinting of RNA

    Schlatterer, Jörg C.; Wieder, Matthew S.; Jones, Christopher D.; Pollack, Lois; Brenowitz, Michael

    2012-01-01

    Highlights: ► RNA structure is mapped by pyrite mediated · OH footprinting. ► Repetitive experiments can be done in a powdered pyrite filled cartridge. ► High · OH reactivity of nucleotides imply dynamic role in Diels–Alderase catalysis. -- Abstract: In RNA, function follows form. Mapping the surface of RNA molecules with chemical and enzymatic probes has revealed invaluable information about structure and folding. Hydroxyl radicals ( · OH) map the surface of nucleic acids by cutting the backbone where it is accessible to solvent. Recent studies showed that a microfluidic chip containing pyrite (FeS 2 ) can produce sufficient · OH to footprint DNA. The 49-nt Diels–Alder RNA enzyme catalyzes the C–C bond formation between a diene and a dienophile. A crystal structure, molecular dynamics simulation and atomic mutagenesis studies suggest that nucleotides of an asymmetric bulge participate in the dynamic architecture of the ribozyme’s active center. Of note is that residue U42 directly interacts with the product in the crystallized RNA/product complex. Here, we use powdered pyrite held in a commercially available cartridge to footprint the Diels–Alderase ribozyme with single nucleotide resolution. Residues C39 to U42 are more reactive to · OH than predicted by the solvent accessibility calculated from the crystal structure suggesting that this loop is dynamic in solution. The loop’s flexibility may contribute to substrate recruitment and product release. Our implementation of pyrite-mediated · OH footprinting is a readily accessible approach to gleaning information about the architecture of small RNA molecules.

  2. Predicting HIV RNA virologic outcome at 52-weeks follow-up in antiretroviral clinical trials. The INCAS and AVANTI Study Groups.

    Raboud, J M; Rae, S; Montaner, J S

    2000-08-15

    To determine the ability of intermediate plasma viral load (pVL) measurements to predict virologic outcome at 52 weeks of follow-up in clinical trials of antiretroviral therapy. Individual patient data from three clinical trials (INCAS, AVANTI-2 and AVANTI-3) were combined into a single database. Virologic success was defined to be plasma viral load (pVL) <500 copies/ml at week 52. The sensitivity and specificity of intermediate pVL measurements below the limit of detection, 100, 500, 1000, and 5000 copies/ml to predict virologic success were calculated. The sensitivity, specificity, and positive and negative predictive values of a pVL measurement <1000 copies/ml at week 16 to predict virologic outcome at week 52 were 74%, 74%, 48%, and 90%, respectively, for patients on double therapy. For patients on triple therapy, the sensitivity, specificity, and positive and negative predictive values of a pVL measurement <50 copies/ml at week 16 to predict virologic outcome were 68%, 68%, 80%, and 47%, respectively. For patients receiving double therapy, a poor virologic result at an intermediate week of follow-up is a strong indicator of virologic failure at 52 weeks whereas intermediate virologic success is no guarantee of success at 1 year. For patients on triple therapy, disappointing intermediate results do not preclude virologic success at 1 year and intermediate successes are more likely to be sustained.

  3. An analytical platform for mass spectrometry-based identification and chemical analysis of RNA in ribonucleoprotein complexes.

    Taoka, Masato; Yamauchi, Yoshio; Nobe, Yuko; Masaki, Shunpei; Nakayama, Hiroshi; Ishikawa, Hideaki; Takahashi, Nobuhiro; Isobe, Toshiaki

    2009-11-01

    We describe here a mass spectrometry (MS)-based analytical platform of RNA, which combines direct nano-flow reversed-phase liquid chromatography (RPLC) on a spray tip column and a high-resolution LTQ-Orbitrap mass spectrometer. Operating RPLC under a very low flow rate with volatile solvents and MS in the negative mode, we could estimate highly accurate mass values sufficient to predict the nucleotide composition of a approximately 21-nucleotide small interfering RNA, detect post-transcriptional modifications in yeast tRNA, and perform collision-induced dissociation/tandem MS-based structural analysis of nucleolytic fragments of RNA at a sub-femtomole level. Importantly, the method allowed the identification and chemical analysis of small RNAs in ribonucleoprotein (RNP) complex, such as the pre-spliceosomal RNP complex, which was pulled down from cultured cells with a tagged protein cofactor as bait. We have recently developed a unique genome-oriented database search engine, Ariadne, which allows tandem MS-based identification of RNAs in biological samples. Thus, the method presented here has broad potential for automated analysis of RNA; it complements conventional molecular biology-based techniques and is particularly suited for simultaneous analysis of the composition, structure, interaction, and dynamics of RNA and protein components in various cellular RNP complexes.

  4. Use MACES IVA Suit for EVA Mobility Evaluations

    Watson, Richard D.

    2014-01-01

    The use of an Intra-Vehicular Activity (IVA) suit for a spacewalk or Extra-Vehicular Activity (EVA) was evaluated for mobility and usability in the Neutral Buoyancy Lab (NBL) environment. The Space Shuttle Advanced Crew Escape Suit (ACES) has been modified (MACES) to integrate with the Orion spacecraft. The first several missions of the Orion MPCV spacecraft will not have mass available to carry an EVA specific suit so any EVA required will have to be performed by the MACES. Since the MACES was not designed with EVA in mind, it was unknown what mobility the suit would be able to provide for an EVA or if a person could perform useful tasks for an extended time inside the pressurized suit. The suit was evaluated in multiple NBL runs by a variety of subjects including crewmembers with significant EVA experience. Various functional mobility tasks performed included: translation, body positioning, carrying tools, body stabilization, equipment handling, and use of tools. Hardware configurations included with and without TMG, suit with IVA gloves and suit with EVA gloves. Most tasks were completed on ISS mockups with existing EVA tools. Some limited tasks were completed with prototype tools on a simulated rocky surface. Major findings include: demonstration of the ability to weigh-out the suit, understanding the need to have subjects perform multiple runs prior to getting feedback, determination of critical sizing factors, and need for adjustment of suit work envelop. The early testing has demonstrated the feasibility of EVA's limited duration and limited scope. Further testing is required with more flight like tasking and constraints to validate these early results. If the suit is used for EVA, it will require mission specific modifications for umbilical management or PLSS integration, safety tether attachment, and tool interfaces. These evaluations are continuing through calendar year 2014.

  5. Morphing: A Novel Approach to Astronaut Suit Sizing

    Margerum, Sarah; Clowers, Kurt; Rajulu, Sudhakar

    2006-01-01

    The fitting of a spacesuit to an astronaut is an iterative process consisting of two parts. The first uses anthropometric data to provide an approximation of the suit components that will fit the astronaut. The second part is the subjective fitting, where small adjustments are made based on the astronaut s preference. By providing a better approximation of the correct suit components, the entire fit process time can be reduced significantly. The goals of this project are twofold: (1) To evaluate the effectiveness of the existing sizing algorithm for the Mark III Hybrid suit and (2) to determine what additional components are needed in order to provide adequate sizing for the existing astronaut population. A single subject was scanned using a 3D whole-body scanner (VITUS 3D) in the Mark III suit in eight different poses and four subjects in minimal clothing were also scanned in similar poses. The 3D external body scans of the suit and the subject are overlaid and visually aligned in a customized MATLAB program. The suit components were contracted or expanded linearly along the subjects limbs to match the subjects segmental lengths. Two independent measures were obtained from the morphing program on four subjects and compared with the existing sizing information. Two of the four subjects were in correspondence with the sizing algorithm and morphing results. The morphing outcome for a third subject, incompatible with the suit, suggested that an additional arm element at least 6 inches smaller than the existing smallest suit component would need to be acquired. The morphing result of the fourth subject, deemed incompatible with the suit using the sizing algorithm, indicated a different suit configuration which would be compatible. This configuration matched with the existing suit fit check data.

  6. Long noncoding RNA CASC2 predicts the prognosis of glioma patients and functions as a suppressor for gliomas by suppressing Wnt/β-catenin signaling pathway

    Wang R

    2017-07-01

    Full Text Available Ronglin Wang,1,* Yuqian Li,1,* Gang Zhu,1,* Bo Tian,1 Wen Zeng,1 Yang Yang,2 Zhihong Li1 1Department of Neurosurgery, Tangdu Hospital, The Fourth Military Medical University, 2Department of Neurosurgery, The 451th hospital of PLA, Xi’an, Shaanxi, People’s Republic of China *These authors contributed equally to this work Background: Previous studies have demonstrated that long noncoding RNA cancer susceptibility candidate 2 (lncRNA CASC2 is frequently downregulated in several types of tumors and functions as a tumor-suppressive factor. However, the clinical significance and function of CASC2 in human glioma remain largely unknown. The purpose of this study was to identify the clinical values of CASC2, as well as investigate the potential molecular mechanisms in glioma. Methods: This retrospective study first analyzed the expression levels of CASC2 using quantitative real-time polymerase chain reaction. Then, CASC2 expression levels were associated with various clinicopathologic characteristics and the survival rate of patients with glioma. Finally, the function and underlying molecular mechanisms of CASC2 in human glioma were investigated in U251 cell line. Results: By quantitative real-time polymerase chain reaction analysis, our data showed that CASC2 expression was significantly downregulated in glioma tissues and cell lines (U87 and U251 compared to adjacent normal brain tissues or normal human astrocytes. Moreover, its expression negatively correlated with tumor grade in glioma patients. Furthermore, Kaplan–Meier curves with log-rank analysis revealed a close correlation between downregulated CASC2 and shorter survival time in glioma patients. In addition, Cox regression analysis indicated that CASC2 could be considered as an independent risk factor for poor prognosis. Finally, in vitro experiment demonstrated that CASC2 overexpression remarkably suppressed glioma cell proliferation, migration, and invasion through suppressing Wnt

  7. MysiRNA-designer: a workflow for efficient siRNA design.

    Mohamed Mysara

    Full Text Available The design of small interfering RNA (siRNA is a multi factorial problem that has gained the attention of many researchers in the area of therapeutic and functional genomics. MysiRNA score was previously introduced that improves the correlation of siRNA activity prediction considering state of the art algorithms. In this paper, a new program, MysiRNA-Designer, is described which integrates several factors in an automated work-flow considering mRNA transcripts variations, siRNA and mRNA target accessibility, and both near-perfect and partial off-target matches. It also features the MysiRNA score, a highly ranked correlated siRNA efficacy prediction score for ranking the designed siRNAs, in addition to top scoring models Biopredsi, DISR, Thermocomposition21 and i-Score, and integrates them in a unique siRNA score-filtration technique. This multi-score filtration layer filters siRNA that passes the 90% thresholds calculated from experimental dataset features. MysiRNA-Designer takes an accession, finds conserved regions among its transcript space, finds accessible regions within the mRNA, designs all possible siRNAs for these regions, filters them based on multi-scores thresholds, and then performs SNP and off-target filtration. These strict selection criteria were tested against human genes in which at least one active siRNA was designed from 95.7% of total genes. In addition, when tested against an experimental dataset, MysiRNA-Designer was found capable of rejecting 98% of the false positive siRNAs, showing superiority over three state of the art siRNA design programs. MysiRNA is a freely accessible (Microsoft Windows based desktop application that can be used to design siRNA with a high accuracy and specificity. We believe that MysiRNA-Designer has the potential to play an important role in this area.

  8. Sulfur-inhibited Thermosphaera aggregans sp. nov., a new genus of hyperthermophilic archaea isolated after its prediction from environmentally derived 16S rRNA sequences.

    Huber, R; Dyba, D; Huber, H; Burggraf, S; Rachel, R

    1998-01-01

    Recently, a new procedure was developed which allowed for the first time the isolation of a hyperthermophilic archaeum tracked by 165 rRNA analysis from a terrestrial hot solfataric spring ('Obsidian Pool', Yellowstone National Park, WY, USA). This novel isolate is characterized here. Cells are round cocci with a diameter of 0.2-0.8 micron, occurring singly, in pairs, short chains and in grape-like aggregates. The aggregates exhibit a weak bluish-green fluorescence under UV radiation at 420 nm. The new isolate is an anaerobic obligate heterotroph, using preferentially yeast extract for growth. The metabolic products include CO2, H2, acetate and isovalerate. Growth is observed between 65 and 90 degrees C (optimum: 85 degrees C), from pH 5.0 to 7.0 (optimum: 6.5) and up to 0.7% NaCl. The apparent activation energy for growth is about 149 kJ mol-1. Elemental sulfur or hydrogen inhibits growth. The core lipids consist mainly of acyclic and cyclic glycerol diphytanyl tetraethers. The cell envelope contains a cytoplasmic membrane covered by an amorphous layer of unknown composition; there is no evidence for a regularly arrayed surface-layer protein. The G + C content is 46 mol%. On the basis of 165 rRNA sequence comparisons in combination with morphological, physiological and biochemical properties, the isolate represents a new genus within the Desulfurococcaceae, which has been named Thermosphaera. The type species is Thermosphaera aggregans, the type strain is isolate M11TLT (= DSM 11486T).

  9. Signatures of RNA binding proteins globally coupled to effective microRNA target sites

    Jacobsen, Anders; Wen, Jiayu; Marks, Debora S

    2010-01-01

    MicroRNAs (miRNAs) and small interfering RNAs (siRNAs), bound to Argonaute proteins (RISC), destabilize mRNAs through base-pairing with the mRNA. However, the gene expression changes after perturbations of these small RNAs are only partially explained by predicted miRNA/siRNA targeting. Targeting...

  10. STELLTRANS: A Transport Analysis Suite for Stellarators

    Mittelstaedt, Joseph; Lazerson, Samuel; Pablant, Novimir; Weir, Gavin; W7-X Team

    2016-10-01

    The stellarator transport code STELLTRANS allows us to better analyze the power balance in W7-X. Although profiles of temperature and density are measured experimentally, geometrical factors are needed in conjunction with these measurements to properly analyze heat flux densities in stellarators. The STELLTRANS code interfaces with VMEC to find an equilibrium flux surface configuration and with TRAVIS to determine the RF heating and current drive in the plasma. Stationary transport equations are then considered which are solved using a boundary value differential equation solver. The equations and quantities considered are averaged over flux surfaces to reduce the system to an essentially one dimensional problem. We have applied this code to data from W-7X and were able to calculate the heat flux coefficients. We will also present extensions of the code to a predictive capacity which would utilize DKES to find neoclassical transport coefficients to update the temperature and density profiles.

  11. The BRITNeY Suite: A Platfor for Experiments

    Westergaard, Michael

    2006-01-01

    This paper describes a platform, the BRITNeY Suite, for experimenting with Coloured Petri nets. The BRITNeY Suite provides access to data-structures and a simulator for Coloured Petri nets via a powerful scripting language and plug-in-mechanism, thereby making it easy to perform customized...

  12. Correction factors for assessing immersion suits under harsh conditions.

    Power, Jonathan; Tikuisis, Peter; Ré, António Simões; Barwood, Martin; Tipton, Michael

    2016-03-01

    Many immersion suit standards require testing of thermal protective properties in calm, circulating water while these suits are typically used in harsher environments where they often underperform. Yet it can be expensive and logistically challenging to test immersion suits in realistic conditions. The goal of this work was to develop a set of correction factors that would allow suits to be tested in calm water yet ensure they will offer sufficient protection in harsher conditions. Two immersion studies, one dry and the other with 500 mL of water within the suit, were conducted in wind and waves to measure the change in suit insulation. In both studies, wind and waves resulted in a significantly lower immersed insulation value compared to calm water. The minimum required thermal insulation for maintaining heat balance can be calculated for a given mean skin temperature, metabolic heat production, and water temperature. Combining the physiological limits of sustainable cold water immersion and actual suit insulation, correction factors can be deduced for harsh conditions compared to calm. The minimum in-situ suit insulation to maintain thermal balance is 1.553-0.0624·TW + 0.00018·TW(2) for a dry calm condition. Multiplicative correction factors to the above equation are 1.37, 1.25, and 1.72 for wind + waves, 500 mL suit wetness, and both combined, respectively. Calm water certification tests of suit insulation should meet or exceed the minimum in-situ requirements to maintain thermal balance, and correction factors should be applied for a more realistic determination of minimum insulation for harsh conditions. Crown Copyright © 2015. Published by Elsevier Ltd. All rights reserved.

  13. Genetic polymorphisms in the microRNA binding-sites of the thymidylate synthase gene predict risk and survival in gastric cancer.

    Shen, Rong; Liu, Hongliang; Wen, Juyi; Liu, Zhensheng; Wang, Li-E; Wang, Qiming; Tan, Dongfeng; Ajani, Jaffer A; Wei, Qingyi

    2015-09-01

    Thymidylate synthase (TYMS) plays a crucial role in folate metabolism as well as DNA synthesis and repair. We hypothesized that functional polymorphisms in the 3' UTR of TYMS are associated with gastric cancer risk and survival. In the present study, we tested our hypothesis by genotyping three potentially functional (at miRNA binding sites) TYMS SNPs (rs16430 6bp del/ins, rs2790 A>G and rs1059394 C>T) in 379 gastric cancer patients and 431 cancer-free controls. Compared with the rs16430 6bp/6bp + 6bp/0bp genotypes, the 0bp/0bp genotype was associated with significantly increased gastric cancer risk (adjusted OR = 1.72, 95% CI = 1.15-2.58). Similarly, rs2790 GG and rs1059394 TT genotypes were also associated with significantly increased risk (adjusted OR = 2.52, 95% CI = 1.25-5.10 and adjusted OR = 1.57, 95% CI = 1.04-2.35, respectively), compared with AA + AG and CC + CT genotypes, respectively. In the haplotype analysis, the T-G-0bp haplotype was associated with significantly increased gastric cancer risk, compared with the C-A-6bp haplotype (adjusted OR = 1.34, 95% CI = 1.05-1.72). Survival analysis revealed that rs16430 0bp/0bp and rs1059394 TT genotypes were also associated with poor survival in gastric cancer patients who received chemotherapy treatment (adjusted HR = 1.61, 95% CI = 1.05-2.48 and adjusted HR = 1.59, 95% CI = 1.02-2.48, respectively). These results suggest that these three variants in the miRNA binding sites of TYMS may be associated with cancer risk and survival of gastric cancer patients. Larger population studies are warranted to verify these findings. © 2014 Wiley Periodicals, Inc.

  14. High levels of microRNA-21 in the stroma of colorectal cancers predict short disease-free survival in stage II colon cancer patients

    Nielsen, Boye Schnack; Jørgensen, Stine; Fog, Jacob Ulrik

    2011-01-01

    Approximately 25% of all patients with stage II colorectal cancer will experience recurrent disease and subsequently die within 5 years. MicroRNA-21 (miR-21) is upregulated in several cancer types and has been associated with survival in colon cancer. In the present study we developed a robust...... in situ hybridization assay using high-affinity Locked Nucleic Acid (LNA) probes that specifically detect miR-21 in formalin-fixed paraffin embedded (FFPE) tissue samples. The expression of miR-21 was analyzed by in situ hybridization on 130 stage II colon and 67 stage II rectal cancer specimens. The mi...... relative to the nuclear density (TBR) obtained using a red nuclear stain. High TBR (and TB) estimates of miR-21 expression correlated significantly with shorter disease-free survival (p = 0.004, HR = 1.28, 95% CI: 1.06-1.55) in the stage II colon cancer patient group, whereas no significant correlation...

  15. Increased expression of long noncoding RNA TUG1 predicts a poor prognosis of gastric cancer and regulates cell proliferation by epigenetically silencing of p57.

    Zhang, E; He, X; Yin, D; Han, L; Qiu, M; Xu, T; Xia, R; Xu, L; Yin, R; De, W

    2016-02-25

    Recent evidence highlights long noncoding RNAs (lncRNAs) as crucial regulators of cancer biology that contribute to tumorigenesis. LncRNA TUG1 was initially detected in a genomic screen for genes upregulated in response to taurine treatment in developing mouse retinal cells. Our previous study showed that TUG1 could affect cell proliferation through epigenetically regulating HOXB7 in human non-small cell lung cancer. However, the clinical significance and potential role of TUG1 in GC remains unclear. In this study, we found that TUG1 is significantly increased and is correlated with outcomes in gastric cancer (GC). Further experiments revealed that knockdown of TUG1 repressed GC proliferation both in vitro and in vivo. Mechanistic investigations showed that TUG1 has a key role in G0/G1 arrest. We further demonstrated that TUG1 was associated with PRC2 and that this association was required for epigenetic repression of cyclin-dependent protein kinase inhibitors, including p15, p16, p21, p27 and p57, thus contributing to the regulation of GC cell cycle and proliferation. Together, our results suggest that TUG1, as a regulator of proliferation, may serve as a candidate prognostic biomarker and target for new therapies in human GC.

  16. The predictive value of 53BP1 and BRCA1 mRNA expression in advanced non-small-cell lung cancer patients treated with first-line platinum-based chemotherapy

    Bonanno, Laura; Costa, Carlota; Majem, Margarita; Sanchez, Jose Javier; Gimenez-Capitan, Ana; Rodriguez, Ignacio; Vergenegre, Alain; Massuti, Bartomeu; Favaretto, Adolfo; Rugge, Massimo; Pallares, Cinta; Taron, Miquel; Rosell, Rafael

    2013-01-01

    Platinum-based chemotherapy is the standard first-line treatment for non-oncogene-addicted non-small cell lung cancers (NSCLCs) and the analysis of multiple DNA repair genes could improve current models for predicting chemosensitivity. We investigated the potential predictive role of components of the 53BP1 pathway in conjunction with BRCA1. The mRNA expression of BRCA1, MDC1, CASPASE3, UBC13, RNF8, 53BP1, PIAS4, UBC9 and MMSET was analyzed by real-time PCR in 115 advanced NSCLC patients treated with first-line platinum-based chemotherapy. Patients expressing low levels of both BRCA1 and 53BP1 obtained a median progression-free survival of 10.3 months and overall survival of 19.3 months, while among those with low BRCA1 and high 53BP1 progression-free survival was 5.9 months (P <0.0001) and overall survival was 8.2 months (P=0.001). The expression of 53BP1 refines BRCA1-based predictive modeling to identify patients most likely to benefit from platinum-based chemotherapy. PMID:24197907

  17. Hybrid Enhanced Epidermal SpaceSuit Design Approaches

    Jessup, Joseph M.

    A Space suit that does not rely on gas pressurization is a multi-faceted problem that requires major stability controls to be incorporated during design and construction. The concept of Hybrid Epidermal Enhancement space suit integrates evolved human anthropomorphic and physiological adaptations into its functionality, using commercially available bio-medical technologies to address shortcomings of conventional gas pressure suits, and the impracticalities of MCP suits. The prototype HEE Space Suit explored integumentary homeostasis, thermal control and mobility using advanced bio-medical materials technology and construction concepts. The goal was a space suit that functions as an enhanced, multi-functional bio-mimic of the human epidermal layer that works in attunement with the wearer rather than as a separate system. In addressing human physiological requirements for design and construction of the HEE suit, testing regimes were devised and integrated into the prototype which was then subject to a series of detailed tests using both anatomical reproduction methods and human subject.

  18. Enabling interoperability in Geoscience with GI-suite

    Boldrini, Enrico; Papeschi, Fabrizio; Santoro, Mattia; Nativi, Stefano

    2015-04-01

    GI-suite is a brokering framework targeting interoperability of heterogeneous systems in the Geoscience domain. The framework is composed by different brokers each one focusing on a specific functionality: discovery, access and semantics (i.e. GI-cat, GI-axe, GI-sem). The brokering takes place between a set of heterogeneous publishing services and a set of heterogeneous consumer applications: the brokering target is represented by resources (e.g. coverages, features, or metadata information) required to seamlessly flow from the providers to the consumers. Different international and community standards are now supported by GI-suite, making possible the successful deployment of GI-suite in many international projects and initiatives (such as GEOSS, NSF BCube and several EU funded projects). As for the publisher side more than 40 standards and implementations are supported (e.g. Dublin Core, OAI-PMH, OGC W*S, Geonetwork, THREDDS Data Server, Hyrax Server, etc.). The support for each individual standard is provided by means of specific GI-suite components, called accessors. As for the consumer applications side more than 15 standards and implementations are supported (e.g. ESRI ArcGIS, Openlayers, OGC W*S, OAI-PMH clients, etc.). The support for each individual standard is provided by means of specific profiler components. The GI-suite can be used in different scenarios by different actors: - A data provider having a pre-existent data repository can deploy and configure GI-suite to broker it and making thus available its data resources through different protocols to many different users (e.g. for data discovery and/or data access) - A data consumer can use GI-suite to discover and/or access resources from a variety of publishing services that are already publishing data according to well-known standards. - A community can deploy and configure GI-suite to build a community (or project-specific) broker: GI-suite can broker a set of community related repositories and

  19. A Secure Communication Suite for Underwater Acoustic Sensor Networks

    Angelica Lo Duca

    2012-11-01

    Full Text Available In this paper we describe a security suite for Underwater Acoustic Sensor Networks comprising both fixed and mobile nodes. The security suite is composed of a secure routing protocol and a set of cryptographic primitives aimed at protecting the confidentiality and the integrity of underwater communication while taking into account the unique characteristics and constraints of the acoustic channel. By means of experiments and simulations based on real data, we show that the suite is suitable for an underwater networking environment as it introduces limited, and sometimes negligible, communication and power consumption overhead.

  20. Development on smart suit for dairy work assistance.

    Nara, Hiroyuki; Kusaka, Takashi; Tanaka, Takayuki; Yamagishi, Takayuki; Ogura, Shotaroh

    2013-01-01

    Our purpose in this study is to achieve an independent life and a social involvement for the elderly using KEIROKA Technology(fatigue-reduction) which makes it possible to improve the quality of chores and occupations by removing excessive strain and tiredness. The authors have developed power assist suits named "smart suit". The authors have evaluated the effect that the purpose of dairy work assistance, to measure EMG of the worker, compared to the potential of the surface of the non-wearing and wearing "smart suit".

  1. Inertial motion capture system for biomechanical analysis in pressure suits

    Di Capua, Massimiliano

    A non-invasive system has been developed at the University of Maryland Space System Laboratory with the goal of providing a new capability for quantifying the motion of the human inside a space suit. Based on an array of six microprocessors and eighteen microelectromechanical (MEMS) inertial measurement units (IMUs), the Body Pose Measurement System (BPMS) allows the monitoring of the kinematics of the suit occupant in an unobtrusive, self-contained, lightweight and compact fashion, without requiring any external equipment such as those necessary with modern optical motion capture systems. BPMS measures and stores the accelerations, angular rates and magnetic fields acting upon each IMU, which are mounted on the head, torso, and each segment of each limb. In order to convert the raw data into a more useful form, such as a set of body segment angles quantifying pose and motion, a series of geometrical models and a non-linear complimentary filter were implemented. The first portion of this works focuses on assessing system performance, which was measured by comparing the BPMS filtered data against rigid body angles measured through an external VICON optical motion capture system. This type of system is the industry standard, and is used here for independent measurement of body pose angles. By comparing the two sets of data, performance metrics such as BPMS system operational conditions, accuracy, and drift were evaluated and correlated against VICON data. After the system and models were verified and their capabilities and limitations assessed, a series of pressure suit evaluations were conducted. Three different pressure suits were used to identify the relationship between usable range of motion and internal suit pressure. In addition to addressing range of motion, a series of exploration tasks were also performed, recorded, and analysed in order to identify different motion patterns and trajectories as suit pressure is increased and overall suit mobility is reduced

  2. Effectiveness comparison of partially executed t-way test suite based generated by existing strategies

    Othman, Rozmie R.; Ahmad, Mohd Zamri Zahir; Ali, Mohd Shaiful Aziz Rashid; Zakaria, Hasneeza Liza; Rahman, Md. Mostafijur

    2015-05-01

    Consuming 40 to 50 percent of software development cost, software testing is one of the most resource consuming activities in software development lifecycle. To ensure an acceptable level of quality and reliability of a typical software product, it is desirable to test every possible combination of input data under various configurations. Due to combinatorial explosion problem, considering all exhaustive testing is practically impossible. Resource constraints, costing factors as well as strict time-to-market deadlines are amongst the main factors that inhibit such consideration. Earlier work suggests that sampling strategy (i.e. based on t-way parameter interaction or called as t-way testing) can be effective to reduce number of test cases without effecting the fault detection capability. However, for a very large system, even t-way strategy will produce a large test suite that need to be executed. In the end, only part of the planned test suite can be executed in order to meet the aforementioned constraints. Here, there is a need for test engineers to measure the effectiveness of partially executed test suite in order for them to assess the risk they have to take. Motivated by the abovementioned problem, this paper presents the effectiveness comparison of partially executed t-way test suite generated by existing strategies using tuples coverage method. Here, test engineers can predict the effectiveness of the testing process if only part of the original test cases is executed.

  3. Improvements to the APBS biomolecular solvation software suite: Improvements to the APBS Software Suite

    Jurrus, Elizabeth [Pacific Northwest National Laboratory, Richland Washington; Engel, Dave [Pacific Northwest National Laboratory, Richland Washington; Star, Keith [Pacific Northwest National Laboratory, Richland Washington; Monson, Kyle [Pacific Northwest National Laboratory, Richland Washington; Brandi, Juan [Pacific Northwest National Laboratory, Richland Washington; Felberg, Lisa E. [University of California, Berkeley California; Brookes, David H. [University of California, Berkeley California; Wilson, Leighton [University of Michigan, Ann Arbor Michigan; Chen, Jiahui [Southern Methodist University, Dallas Texas; Liles, Karina [Pacific Northwest National Laboratory, Richland Washington; Chun, Minju [Pacific Northwest National Laboratory, Richland Washington; Li, Peter [Pacific Northwest National Laboratory, Richland Washington; Gohara, David W. [St. Louis University, St. Louis Missouri; Dolinsky, Todd [FoodLogiQ, Durham North Carolina; Konecny, Robert [University of California San Diego, San Diego California; Koes, David R. [University of Pittsburgh, Pittsburgh Pennsylvania; Nielsen, Jens Erik [Protein Engineering, Novozymes A/S, Copenhagen Denmark; Head-Gordon, Teresa [University of California, Berkeley California; Geng, Weihua [Southern Methodist University, Dallas Texas; Krasny, Robert [University of Michigan, Ann Arbor Michigan; Wei, Guo-Wei [Michigan State University, East Lansing Michigan; Holst, Michael J. [University of California San Diego, San Diego California; McCammon, J. Andrew [University of California San Diego, San Diego California; Baker, Nathan A. [Pacific Northwest National Laboratory, Richland Washington; Brown University, Providence Rhode Island

    2017-10-24

    The Adaptive Poisson-Boltzmann Solver (APBS) software was developed to solve the equations of continuum electrostatics for large biomolecular assemblages that has provided impact in the study of a broad range of chemical, biological, and biomedical applications. APBS addresses three key technology challenges for understanding solvation and electrostatics in biomedical applications: accurate and efficient models for biomolecular solvation and electrostatics, robust and scalable software for applying those theories to biomolecular systems, and mechanisms for sharing and analyzing biomolecular electrostatics data in the scientific community. To address new research applications and advancing computational capabilities, we have continually updated APBS and its suite of accompanying software since its release in 2001. In this manuscript, we discuss the models and capabilities that have recently been implemented within the APBS software package including: a Poisson-Boltzmann analytical and a semi-analytical solver, an optimized boundary element solver, a geometry-based geometric flow solvation model, a graph theory based algorithm for determining pKa values, and an improved web-based visualization tool for viewing electrostatics.

  4. CAMEO (Computer-Aided Management of Emergency Operations) Software Suite

    National Oceanic and Atmospheric Administration, Department of Commerce — CAMEO is the umbrella name for a system of software applications used widely to plan for and respond to chemical emergencies. All of the programs in the suite work...

  5. Segane saksa-eesti kirjakeel ja eesti lauluraamat / Gustav Suits

    Suits, Gustav, 1883-1956

    1999-01-01

    Varem ilmunud: Suits, Gustav. Eesti kirjanduslugu I. Lund : Eesti Kirjanike Kooperatiiv, 1953. Heinrich Stahli käsiraamatu Hand-, Hausz- und Kirchenbuch (1654-1656) osana ilmunud lauluraamatust Neu Ehstnisches Gesangbuch (1656)

  6. Touring the Tomato: A Suite of Chemistry Laboratory Experiments

    Sarkar, Sayantani; Chatterjee, Subhasish; Medina, Nancy; Stark, Ruth E.

    2013-01-01

    An eight-session interdisciplinary laboratory curriculum has been designed using a suite of analytical chemistry techniques to study biomaterials derived from an inexpensive source such as the tomato fruit. A logical

  7. Arensky. Silhouettes (Suite N 2), Op. 23 / Jonathan Swain

    Swain, Jonathan

    1991-01-01

    Uuest heliplaadist "Arensky. Silhouettes (Suite N 2), Op. 23. Scrjabin. Symphony N 3 in C minor, Op. 43 "Le divin poeme". Danish National Radio Symphony Orchestra. Neeme Järvi. Chandos cassette ABTD 1509; CD CHAN 8898 (66 minutes)

  8. 33 CFR 144.20-5 - Exposure suits.

    2010-07-01

    ... light that is approved under 46 CFR 161.012. Each light must be securely attached to the front shoulder... lanyard coiled and stopped off. (f) No stowage container for exposure suits may be capable of being locked...

  9. EVA Physiology and Medical Considerations Working in the Suit

    Parazynski, Scott

    2012-01-01

    This "EVA Physiology and Medical Considerations Working in the Suit" presentation covers several topics related to the medical implications and physiological effects of suited operations in space from the perspective of a physician with considerable first-hand Extravehicular Activity (EVA) experience. Key themes include EVA physiology working in a pressure suit in the vacuum of space, basic EVA life support and work support, Thermal Protection System (TPS) inspections and repairs, and discussions of the physical challenges of an EVA. Parazynski covers the common injuries and significant risks during EVAs, as well as physical training required to prepare for EVAs. He also shares overall suit physiological and medical knowledge with the next generation of Extravehicular Mobility Unit (EMU) system designers.

  10. Advanced Gas Sensing Technology for Space Suits, Phase I

    National Aeronautics and Space Administration — Advanced space suits require lightweight, low-power, durable sensors for monitoring critical life support materials. No current compact sensors have the tolerance...

  11. Virtual Suit Fit Assessment Using Body Shape Model

    National Aeronautics and Space Administration — Shoulder injury is one of the most serious risks for crewmembers in long-duration spaceflight. While suboptimal suit fit and contact pressures between the shoulder...

  12. Tchaikovsky, P.: Orchestral Suite no. 3 op. 55 / Terry Williams

    Williams, Terry

    1996-01-01

    Uuest heliplaadist "Tchaikovsky, P.: Orchestral Suite no. 3 op. 55. Francesca di Rimini op. 32. Detroit Symphony Orchestra, Neeme Järvi". Chandos CHAN 9 419, distribution Media 7 (CD: 160F). TT: 1h 09'20"

  13. Prokofiev: War and Peace - Symphonic Suite (arr. Palmer) / Ivan March

    March, Ivan

    1993-01-01

    Uuest heliplaadist "Prokofiev: War and Peace - Symphonic Suite (arr. Palmer), Summer Night, Op. 123. Russian Overture, Op. 72. Philharmonia Orchestra / Neeme Järvi. Chandos ABTD 1598 CHAN9096 (64 minutes:DDD) Igor - Polovtsian Dances

  14. Prokofiev: Romeo and Juliet - Suite N1 / Ivan March

    March, Ivan

    1990-01-01

    Uuest heliplaadist "Prokofiev: Romeo and Juliet - Suite N1, Op.64b, N2, Op.64c. Philharmonia Orchestra, Barry Wordsworth" Collins Classics cassette 1116-4. CD. Võrreldud Neeme Järvi plaadistustega 1116-2

  15. Nonventing Thermal and Humidity Control for EVA Suits, Phase II

    National Aeronautics and Space Administration — Future manned space exploration missions will require space suits with capabilities beyond the current state of the art. Portable Life Support Systems for these...

  16. U.S. Climate Normals Product Suite (1981-2010)

    National Oceanic and Atmospheric Administration, Department of Commerce — The NOAA Climate Normals are a large suite of data products that provide users with many tools to understand typical climate conditions for thousands of locations...

  17. Assuring Condition and Inventory Accountability of Chemical Protective Suits

    2000-01-01

    .... As part of the Defense Logistics Agency's efforts to consolidate depot operations and improve inventory accuracy, chemical protective suits were transferred to the Defense Depot, Albany, Georgia, during FY 1991.

  18. A probabilistic model of RNA conformational space

    Frellsen, Jes; Moltke, Ida; Thiim, Martin

    2009-01-01

    efficient sampling of RNA conformations in continuous space, and with associated probabilities. We show that the model captures several key features of RNA structure, such as its rotameric nature and the distribution of the helix lengths. Furthermore, the model readily generates native-like 3-D......, the discrete nature of the fragments necessitates the use of carefully tuned, unphysical energy functions, and their non-probabilistic nature impairs unbiased sampling. We offer a solution to the sampling problem that removes these important limitations: a probabilistic model of RNA structure that allows......The increasing importance of non-coding RNA in biology and medicine has led to a growing interest in the problem of RNA 3-D structure prediction. As is the case for proteins, RNA 3-D structure prediction methods require two key ingredients: an accurate energy function and a conformational sampling...

  19. lncRNA H19 predicts poor prognosis in patients with melanoma and regulates cell growth, invasion, migration and epithelial–mesenchymal transition in melanoma cells

    Shi G

    2018-06-01

    Full Text Available Gaofeng Shi,1,2 Hu Li,2 Fengshan Gao,2 Qian Tan1 1Drum Tower Clinical Medical College of Nanjing Medical University, Nanjing, People’s Republic of China; 2Department of Plastic Surgery, the Affiliated Wuxi No 4 People’s Hospital of Jiangnan University, Wuxi, People’s Republic of China Introduction: Melanoma is a deadly malignancy and the poor prognosis of patients with advanced disease is relatively poor. Recent studies indicate that long non-coding RNAs are involved in the pathogenesis of malignant melanoma. This study aims to investigate the role of the long non-coding RNA H19 in melanoma and to explore the underlying molecular mechanisms. Materials and methods: The expression levels of H19 in clinical samples and melanoma cells were determined by quantitative real-time PCR. The cell growth and cell metastasis were assessed by Cell Counting Kit 8, cell invasion and wound healing assays. Cell apoptosis and cell cycle were determined by flow cytometry. Protein levels were determined by Western blotting assay. Results: H19 was highly expressed in melanoma tissues compared to normal adjacent skin tissues, and the tissue expression level of H19 from melanoma patients with metastasis was significantly higher than that from patients without distant metastasis. In addition, the high expression of H19 in melanoma tissues was associated with advanced tumor invasion and TNM stage, distal metastasis, lymph node metastasis and shorter overall survival in patients with melanoma. The in vitro functional assays showed that knockdown of H19 inhibited cell growth, invasion and migration and also induced cell apoptosis as well as G0/G1 arrest in melanoma cells. Further quantitative real-time PCR and Western blot experiments showed that knockdown of H19 differentially regulated the epithelial–mesenchymal transition (EMT-related gene expressions and reversed EMT in melanoma cell lines. Knockdown of H19 suppressed in vivo tumor growth and modulated the

  20. Corrections of the NIST Statistical Test Suite for Randomness

    Kim, Song-Ju; Umeno, Ken; Hasegawa, Akio

    2004-01-01

    It is well known that the NIST statistical test suite was used for the evaluation of AES candidate algorithms. We have found that the test setting of Discrete Fourier Transform test and Lempel-Ziv test of this test suite are wrong. We give four corrections of mistakes in the test settings. This suggests that re-evaluation of the test results should be needed.

  1. Cosmonaut Sergei Krikalev receives assistance from suit technician

    1994-01-01

    Sergei Krikalev, alternative mission specialist for STS-63, gets help from Dawn Mays, a Boeing suit technician. The cosmonaut was about to participate in a training session at JSC's Weightless Environment Training Facility (WETF). Wearing the training version of the extravehicular mobility unit (EMU) space suit, weighted to allow neutral buoyancy in the 25 feet deep WETF pool, Krikalev minutes later was underwater simulating a contingency spacewalk, or extravehicular activity (EVA).

  2. Results and Analysis from Space Suit Joint Torque Testing

    Matty, Jennifer

    2010-01-01

    This joint mobility KC lecture included information from two papers, "A Method for and Issues Associated with the Determination of Space Suit Joint Requirements" and "Results and Analysis from Space Suit Joint Torque Testing," as presented for the International Conference on Environmental Systems in 2009 and 2010, respectively. The first paper discusses historical joint torque testing methodologies and approaches that were tested in 2008 and 2009. The second paper discusses the testing that was completed in 2009 and 2010.

  3. STS-74 M.S. Jerry L. Ross suits up

    1995-01-01

    Spaceflight veteran Jerry L. Ross, Mission Specialist 2 on Shuttle Mission STS-74, is assisted by a suit technician as he finishes getting into his launch/entry suit in the Operations and Checkout Building. Ross and four fellow astronauts will depart shortly for Launch Pad 39A, where the Space Shuttle Atlantis awaits a second liftoff attempt during a seven-minute window scheduled to open at approximately 7:30 a.m. EST, Nov. 12.

  4. A Test Suite for Safety-Critical Java using JML

    Ravn, Anders Peter; Søndergaard, Hans

    2013-01-01

    Development techniques are presented for a test suite for the draft specification of the Java profile for Safety-Critical Systems. Distinguishing features are: specification of conformance constraints in the Java Modeling Language, encoding of infrastructure concepts without implementation bias......, and corresponding specifications of implicitly stated behavioral and real-time properties. The test programs are auto-generated from the specification, while concrete values for test parameters are selected manually. The suite is open source and publicly accessible....

  5. Comprehensive characterization of lncRNA-mRNA related ceRNA network across 12 major cancers

    Feng, Li; Li, Feng; Sun, Zeguo; Wu, Tan; Shi, Xinrui; Li, Jing; Li, Xia

    2016-01-01

    Recent studies indicate that long noncoding RNAs (lncRNAs) can act as competing endogenous RNAs (ceRNAs) to indirectly regulate mRNAs through shared microRNAs, which represents a novel layer of RNA crosstalk and plays critical roles in the development of tumor. However, the global regulation landscape and characterization of these lncRNA related ceRNA crosstalk in cancers is still largely unknown. Here, we systematically characterized the lncRNA related ceRNA interactions across 12 major cancers and the normal physiological states by integrating multidimensional molecule profiles of more than 5000 samples. Our study suggest the large difference of ceRNA regulation between normal and tumor states and the higher similarity across similar tissue origin of tumors. The ceRNA related molecules have more conserved features in tumor networks and they play critical roles in both the normal and tumorigenesis processes. Besides, lncRNAs in the pan-cancer ceRNA network may be potential biomarkers of tumor. By exploring hub lncRNAs, we found that these conserved key lncRNAs dominate variable tumor hallmark processes across pan-cancers. Network dynamic analysis highlights the critical roles of ceRNA regulation in tumorigenesis. By analyzing conserved ceRNA interactions, we found that miRNA mediate ceRNA regulation showed different patterns across pan-cancer; while analyzing the cancer specific ceRNA interactions reveal that lncRNAs synergistically regulated tumor driver genes of cancer hallmarks. Finally, we found that ceRNA modules have the potential to predict patient survival. Overall, our study systematically dissected the lncRNA related ceRNA networks in pan-cancer that shed new light on understanding the molecular mechanism of tumorigenesis. PMID:27580177

  6. Automated and fast building of three-dimensional RNA structures.

    Zhao, Yunjie; Huang, Yangyu; Gong, Zhou; Wang, Yanjie; Man, Jianfen; Xiao, Yi

    2012-01-01

    Building tertiary structures of non-coding RNA is required to understand their functions and design new molecules. Current algorithms of RNA tertiary structure prediction give satisfactory accuracy only for small size and simple topology and many of them need manual manipulation. Here, we present an automated and fast program, 3dRNA, for RNA tertiary structure prediction with reasonable accuracy for RNAs of larger size and complex topology.

  7. A probabilistic model of RNA conformational space

    Frellsen, Jes; Moltke, Ida; Thiim, Martin

    2009-01-01

    , the discrete nature of the fragments necessitates the use of carefully tuned, unphysical energy functions, and their non-probabilistic nature impairs unbiased sampling. We offer a solution to the sampling problem that removes these important limitations: a probabilistic model of RNA structure that allows...... conformations for 9 out of 10 test structures, solely using coarse-grained base-pairing information. In conclusion, the method provides a theoretical and practical solution for a major bottleneck on the way to routine prediction and simulation of RNA structure and dynamics in atomic detail.......The increasing importance of non-coding RNA in biology and medicine has led to a growing interest in the problem of RNA 3-D structure prediction. As is the case for proteins, RNA 3-D structure prediction methods require two key ingredients: an accurate energy function and a conformational sampling...

  8. MicroRNA-target binding structures mimic microRNA duplex structures in humans.

    Xi Chen

    Full Text Available Traditionally, researchers match a microRNA guide strand to mRNA sequences using sequence comparisons to predict its potential target genes. However, many of the predictions can be false positives due to limitations in sequence comparison alone. In this work, we consider the association of two related RNA structures that share a common guide strand: the microRNA duplex and the microRNA-target binding structure. We have analyzed thousands of such structure pairs and found many of them share high structural similarity. Therefore, we conclude that when predicting microRNA target genes, considering just the microRNA guide strand matches to gene sequences may not be sufficient--the microRNA duplex structure formed by the guide strand and its companion passenger strand must also be considered. We have developed software to translate RNA binding structure into encoded representations, and we have also created novel automatic comparison methods utilizing such encoded representations to determine RNA structure similarity. Our software and methods can be utilized in the other RNA secondary structure comparisons as well.

  9. Species-independent MicroRNA Gene Discovery

    Kamanu, Timothy K.

    2012-12-01

    MicroRNA (miRNA) are a class of small endogenous non-coding RNA that are mainly negative transcriptional and post-transcriptional regulators in both plants and animals. Recent studies have shown that miRNA are involved in different types of cancer and other incurable diseases such as autism and Alzheimer’s. Functional miRNAs are excised from hairpin-like sequences that are known as miRNA genes. There are about 21,000 known miRNA genes, most of which have been determined using experimental methods. miRNA genes are classified into different groups (miRNA families). This study reports about 19,000 unknown miRNA genes in nine species whereby approximately 15,300 predictions were computationally validated to contain at least one experimentally verified functional miRNA product. The predictions are based on a novel computational strategy which relies on miRNA family groupings and exploits the physics and geometry of miRNA genes to unveil the hidden palindromic signals and symmetries in miRNA gene sequences. Unlike conventional computational miRNA gene discovery methods, the algorithm developed here is species-independent: it allows prediction at higher accuracy and resolution from arbitrary RNA/DNA sequences in any species and thus enables examination of repeat-prone genomic regions which are thought to be non-informative or ’junk’ sequences. The information non-redundancy of uni-directional RNA sequences compared to information redundancy of bi-directional DNA is demonstrated, a fact that is overlooked by most pattern discovery algorithms. A novel method for computing upstream and downstream miRNA gene boundaries based on mathematical/statistical functions is suggested, as well as cutoffs for annotation of miRNA genes in different miRNA families. Another tool is proposed to allow hypotheses generation and visualization of data matrices, intra- and inter-species chromosomal distribution of miRNA genes or miRNA families. Our results indicate that: miRNA and miRNA

  10. Je, a versatile suite to handle multiplexed NGS libraries with unique molecular identifiers.

    Girardot, Charles; Scholtalbers, Jelle; Sauer, Sajoscha; Su, Shu-Yi; Furlong, Eileen E M

    2016-10-08

    The yield obtained from next generation sequencers has increased almost exponentially in recent years, making sample multiplexing common practice. While barcodes (known sequences of fixed length) primarily encode the sample identity of sequenced DNA fragments, barcodes made of random sequences (Unique Molecular Identifier or UMIs) are often used to distinguish between PCR duplicates and transcript abundance in, for example, single-cell RNA sequencing (scRNA-seq). In paired-end sequencing, different barcodes can be inserted at each fragment end to either increase the number of multiplexed samples in the library or to use one of the barcodes as UMI. Alternatively, UMIs can be combined with the sample barcodes into composite barcodes, or with standard Illumina® indexing. Subsequent analysis must take read duplicates and sample identity into account, by identifying UMIs. Existing tools do not support these complex barcoding configurations and custom code development is frequently required. Here, we present Je, a suite of tools that accommodates complex barcoding strategies, extracts UMIs and filters read duplicates taking UMIs into account. Using Je on publicly available scRNA-seq and iCLIP data containing UMIs, the number of unique reads increased by up to 36 %, compared to when UMIs are ignored. Je is implemented in JAVA and uses the Picard API. Code, executables and documentation are freely available at http://gbcs.embl.de/Je . Je can also be easily installed in Galaxy through the Galaxy toolshed.

  11. Extracellular RNA Communication (ExRNA)

    Federal Laboratory Consortium — Until recently, scientists believed RNA worked mostly inside the cell that produced it. Some types of RNA help translate genes into proteins that are necessary for...

  12. Molecular cloning, expression analysis and miRNA prediction of vascular endothelial growth factor A (VEGFAa and VEGFAb) in pond loach Misgurnus anguillicaudatus, an air-breathing fish.

    Luo, Weiwei; Liang, Xiao; Huang, Songqian; Cao, Xiaojuan

    2016-12-01

    Vascular endothelial growth factor A (VEGFA) is the most studied and the best characterized member of the VEGF family and is a key regulator of angiogenesis via its ability to affect the proliferation, migration, and differentiation of endothelial cells. In this study, the full-length cDNAs encoding VEGFAa and VEGFAb from pond loach, Misgurnus anguillicaudatus, were isolated. The VEGFAa is constituted by an open reading frame (ORF) of 570bp encoding for a peptide of 189 amino acid residues, a 639bp 5'-untranslated region (UTR) and a 2383bp 3' UTR. The VEGFAb is constituted by an ORF of 687bp encoding for a peptide of 228 amino acid residues, a 560bp 5' UTR and a 1268bp 3' UTR. Phylogenetic analysis indicated that the VEGFAa and VEGFAb of pond loach were conserved in vertebrates. Expression levels of VEGFAa and VEGFAb were detected by RT-qPCR at different development stages of pond loach and in different tissues of 6-month-old, 12-month-old and 24-month-old pond loach. Moreover, eight predicted miRNAs (miR-200, miR-29, miR-218, miR-338, miR-103, miR-15, miR-17 and miR-223) targeting VEGFAa and VEGFAb were validated by an intestinal air-breathing inhibition experiment. This study will be of value for further studies into the function of VEGFA and its corresponding miRNAs, which will shed a light on the vascularization and accessory air-breathing process in pond loach. Copyright © 2016 Elsevier Inc. All rights reserved.

  13. Functional characterization of the Drosophila MRP (mitochondrial RNA processing) RNA gene.

    Schneider, Mary D; Bains, Anupinder K; Rajendra, T K; Dominski, Zbigniew; Matera, A Gregory; Simmonds, Andrew J

    2010-11-01

    MRP RNA is a noncoding RNA component of RNase mitochondrial RNA processing (MRP), a multi-protein eukaryotic endoribonuclease reported to function in multiple cellular processes, including ribosomal RNA processing, mitochondrial DNA replication, and cell cycle regulation. A recent study predicted a potential Drosophila ortholog of MRP RNA (CR33682) by computer-based genome analysis. We have confirmed the expression of this gene and characterized the phenotype associated with this locus. Flies with mutations that specifically affect MRP RNA show defects in growth and development that begin in the early larval period and end in larval death during the second instar stage. We present several lines of evidence demonstrating a role for Drosophila MRP RNA in rRNA processing. The nuclear fraction of Drosophila MRP RNA localizes to the nucleolus. Further, a mutant strain shows defects in rRNA processing that include a defect in 5.8S rRNA processing, typical of MRP RNA mutants in other species, as well as defects in early stages of rRNA processing.

  14. Improved crystallization of the coxsackievirus B3 RNA-dependent RNA polymerase

    Jabafi, Ilham; Selisko, Barbara; Coutard, Bruno; De Palma, Armando M.; Neyts, Johan; Egloff, Marie-Pierre; Grisel, Sacha; Dalle, Karen; Campanacci, Valerie; Spinelli, Silvia; Cambillau, Christian; Canard, Bruno; Gruez, Arnaud, E-mail: arnaud.gruez@maem.uhp-nancy.fr [Centre National de la Recherche Scientifique and Universités d’Aix-Marseille I et II, UMR 6098, Architecture et Fonction des Macromolécules Biologiques, Ecole Supérieure d’Ingénieurs de Luminy-Case 925, 163 Avenue de Luminy, 13288 Marseille CEDEX 9 (France)

    2007-06-01

    The first crystal of a coxsackievirus RNA-dependent RNA polymerase is reported. The Picornaviridae virus family contains a large number of human pathogens such as poliovirus, hepatitis A virus and rhinoviruses. Amongst the viruses belonging to the genus Enterovirus, several serotypes of coxsackievirus coexist for which neither vaccine nor therapy is available. Coxsackievirus B3 is involved in the development of acute myocarditis and dilated cardiomyopathy and is thought to be an important cause of sudden death in young adults. Here, the first crystal of a coxsackievirus RNA-dependent RNA polymerase is reported. Standard crystallization methods yielded crystals that were poorly suited to X-ray diffraction studies, with one axis being completely disordered. Crystallization was improved by testing crystallization solutions from commercial screens as additives. This approach yielded crystals that diffracted to 2.1 Å resolution and that were suitable for structure determination.

  15. Improved crystallization of the coxsackievirus B3 RNA-dependent RNA polymerase

    Jabafi, Ilham; Selisko, Barbara; Coutard, Bruno; De Palma, Armando M.; Neyts, Johan; Egloff, Marie-Pierre; Grisel, Sacha; Dalle, Karen; Campanacci, Valerie; Spinelli, Silvia; Cambillau, Christian; Canard, Bruno; Gruez, Arnaud

    2007-01-01

    The first crystal of a coxsackievirus RNA-dependent RNA polymerase is reported. The Picornaviridae virus family contains a large number of human pathogens such as poliovirus, hepatitis A virus and rhinoviruses. Amongst the viruses belonging to the genus Enterovirus, several serotypes of coxsackievirus coexist for which neither vaccine nor therapy is available. Coxsackievirus B3 is involved in the development of acute myocarditis and dilated cardiomyopathy and is thought to be an important cause of sudden death in young adults. Here, the first crystal of a coxsackievirus RNA-dependent RNA polymerase is reported. Standard crystallization methods yielded crystals that were poorly suited to X-ray diffraction studies, with one axis being completely disordered. Crystallization was improved by testing crystallization solutions from commercial screens as additives. This approach yielded crystals that diffracted to 2.1 Å resolution and that were suitable for structure determination

  16. Reliability performance testing of totally encapsulating chemical protective suits

    Johnson, J.S.; Swearengen, P.M.

    1991-01-01

    The need to assure a high degree of reliability for totally encapsulating chemical protective (TECP) suits has been recognized by Lawrence Livermore National Laboratory's (LLNL) Hazards Control Department for some time. The following four tests were proposed as necessary to provide complete evaluation of TECP suit performance: 1. Quantitative leak test (ASTM draft), 2. Worst-case chemical exposure test (conceptual), 3. Pressure leak-rate test (complete, ASTM F1057-87), and 4. Chemical leak-rate test (ASTM draft). This paper reports on these tests which should be applied to measuring TECP suit performance in two stages: design qualification tests and field use tests. Test 1, 2, and 3 are used as design qualification tests, and tests 3 and 4 are used as field use tests

  17. NetSuite OneWorld Implementation 2011 R2

    Foydel, Thomas

    2011-01-01

    This book is a focused, step-by step tutorial that shows you how to successfully implement NetSuite OneWorld into your organization. It is written in an easy-to-read style, with a strong emphasis on real-world, practical examples with step-by-step explanations. The book focuses on NetSuite OneWorld 2011 R1. If you are an application administrator, business analyst, project team member or business process owner who wants to implement NetSuite OneWorld into your organization, then this book is for you. This book might also be useful if you are a business manager considering a new system for your

  18. Ultraviolet Testing of Space Suit Materials for Mars

    Larson, Kristine; Fries, Marc

    2017-01-01

    Human missions to Mars may require radical changes in the approach to extra-vehicular (EVA) suit design. A major challenge is the balance of building a suit robust enough to complete multiple EVAs under intense ultraviolet (UV) light exposure without losing mechanical strength or compromising the suit's mobility. To study how the materials degrade on Mars in-situ, the Jet Propulsion Laboratory (JPL) invited the Advanced Space Suit team at NASA's Johnson Space Center (JSC) to place space suit materials on the Scanning Habitable Environments with Raman & Luminescence for Organics and Chemicals (SHERLOC) instrument's calibration target of the Mars 2020 rover. In order to select materials for the rover and understand the effects from Mars equivalent UV exposure, JSC conducted ground testing on both current and new space suit materials when exposed to 2500 hours of Mars mission equivalent UV. To complete this testing, JSC partnered with NASA's Marshall Space Flight Center to utilize their UV vacuum chambers. Materials tested were Orthofabric, polycarbonate, Teflon, Dacron, Vectran, spectra, bladder, nGimat coated Teflon, and nGimat coated Orthofabric. All samples were measured for mass, tensile strength, and chemical composition before and after radiation. Mass loss was insignificant (less than 0.5%) among the materials. Most materials loss tensile strength after radiation and became more brittle with a loss of elongation. Changes in chemical composition were seen in all radiated materials through Spectral Analysis. Results from this testing helped select the materials that will fly on the Mars 2020 rover. In addition, JSC can use this data to create a correlation to the chemical changes after radiation-which is what the rover will send back while on Mars-to the mechanical changes, such as tensile strength.

  19. Designing a suite of measurements to understand the critical zone

    Brantley, Susan L.; DiBiase, Roman A.; Russo, Tess A.; Shi, Yuning; Lin, Henry; Davis, Kenneth J.; Kaye, Margot; Hill, Lillian; Kaye, Jason; Eissenstat, David M.; Hoagland, Beth; Dere, Ashlee L.; Neal, Andrew L.; Brubaker, Kristen M.; Arthur, Dan K.

    2016-03-01

    Many scientists have begun to refer to the earth surface environment from the upper canopy to the depths of bedrock as the critical zone (CZ). Identification of the CZ as an integral object worthy of study implicitly posits that the study of the whole earth surface will provide benefits that do not arise when studying the individual parts. To study the CZ, however, requires prioritizing among the measurements that can be made - and we do not generally agree on the priorities. Currently, the Susquehanna Shale Hills Critical Zone Observatory (SSHCZO) is expanding from a small original focus area (0.08 km2, Shale Hills catchment), to a larger watershed (164 km2, Shavers Creek watershed) and is grappling with the prioritization. This effort is an expansion from a monolithologic first-order forested catchment to a watershed that encompasses several lithologies (shale, sandstone, limestone) and land use types (forest, agriculture). The goal of the project remains the same: to understand water, energy, gas, solute, and sediment (WEGSS) fluxes that are occurring today in the context of the record of those fluxes over geologic time as recorded in soil profiles, the sedimentary record, and landscape morphology. Given the small size of the Shale Hills catchment, the original design incorporated measurement of as many parameters as possible at high temporal and spatial density. In the larger Shavers Creek watershed, however, we must focus the measurements. We describe a strategy of data collection and modeling based on a geomorphological and land use framework that builds on the hillslope as the basic unit. Interpolation and extrapolation beyond specific sites relies on geophysical surveying, remote sensing, geomorphic analysis, the study of natural integrators such as streams, groundwaters or air, and application of a suite of CZ models. We hypothesize that measurements of a few important variables at strategic locations within a geomorphological framework will allow

  20. STS-82 Pilot Scott J. 'Doc' Horowitz Suit Up

    1997-01-01

    STS-82 Pilot Scott J. 'Doc' Horowitz puts on a glove of his launch and entry suit with assistance from a suit technician in the Operations and Checkout Building. This is Horowitz''';s second space flight. He and the six other crew members will depart shortly for Launch Pad 39A, where the Space Shuttle Discovery awaits liftoff on a 10-day mission to service the orbiting Hubble Space Telescope (HST). This will be the second HST servicing mission. Four back-to-back spacewalks are planned.

  1. STS-87 Mission Specialist Winston E. Scott suits up

    1997-01-01

    STS-87 Mission Specialist Winston Scott dons his launch and entry suit with the assistance of a suit technician in the Operations and Checkout Building. This is Scotts second space flight. He and the five other crew members will depart shortly for Launch Pad 39B, where the Space Shuttle Columbia awaits liftoff on a 16-day mission to perform microgravity and solar research. Scott is scheduled to perform an extravehicular activity spacewalk with Mission Specialist Takao Doi, Ph.D., of the National Space Development Agency of Japan, during STS-87. He also performed a spacewalk on STS-72.

  2. Extending the GI Brokering Suite to Support New Interoperability Specifications

    Boldrini, E.; Papeschi, F.; Santoro, M.; Nativi, S.

    2014-12-01

    The GI brokering suite provides the discovery, access, and semantic Brokers (i.e. GI-cat, GI-axe, GI-sem) that empower a Brokering framework for multi-disciplinary and multi-organizational interoperability. GI suite has been successfully deployed in the framework of several programmes and initiatives, such as European Union funded projects, NSF BCube, and the intergovernmental coordinated effort Global Earth Observation System of Systems (GEOSS). Each GI suite Broker facilitates interoperability for a particular functionality (i.e. discovery, access, semantic extension) among a set of brokered resources published by autonomous providers (e.g. data repositories, web services, semantic assets) and a set of heterogeneous consumers (e.g. client applications, portals, apps). A wide set of data models, encoding formats, and service protocols are already supported by the GI suite, such as the ones defined by international standardizing organizations like OGC and ISO (e.g. WxS, CSW, SWE, GML, netCDF) and by Community specifications (e.g. THREDDS, OpenSearch, OPeNDAP, ESRI APIs). Using GI suite, resources published by a particular Community or organization through their specific technology (e.g. OPeNDAP/netCDF) can be transparently discovered, accessed, and used by different Communities utilizing their preferred tools (e.g. a GIS visualizing WMS layers). Since Information Technology is a moving target, new standards and technologies continuously emerge and are adopted in the Earth Science context too. Therefore, GI Brokering suite was conceived to be flexible and accommodate new interoperability protocols and data models. For example, GI suite has recently added support to well-used specifications, introduced to implement Linked data, Semantic Web and precise community needs. Amongst the others, they included: DCAT: a RDF vocabulary designed to facilitate interoperability between Web data catalogs. CKAN: a data management system for data distribution, particularly used by

  3. Results from Carbon Dioxide Washout Testing Using a Suited Manikin Test Apparatus with a Space Suit Ventilation Test Loop

    Chullen, Cinda; Conger, Bruce; McMillin, Summer; Vonau, Walt; Kanne, Bryan; Korona, Adam; Swickrath, Mike

    2016-01-01

    NASA is developing an advanced portable life support system (PLSS) to meet the needs of a new NASA advanced space suit. The PLSS is one of the most critical aspects of the space suit providing the necessary oxygen, ventilation, and thermal protection for an astronaut performing a spacewalk. The ventilation subsystem in the PLSS must provide sufficient carbon dioxide (CO2) removal and ensure that the CO2 is washed away from the oronasal region of the astronaut. CO2 washout is a term used to describe the mechanism by which CO2 levels are controlled within the helmet to limit the concentration of CO2 inhaled by the astronaut. Accumulation of CO2 in the helmet or throughout the ventilation loop could cause the suited astronaut to experience hypercapnia (excessive carbon dioxide in the blood). A suited manikin test apparatus (SMTA) integrated with a space suit ventilation test loop was designed, developed, and assembled at NASA in order to experimentally validate adequate CO2 removal throughout the PLSS ventilation subsystem and to quantify CO2 washout performance under various conditions. The test results from this integrated system will be used to validate analytical models and augment human testing. This paper presents the system integration of the PLSS ventilation test loop with the SMTA including the newly developed regenerative Rapid Cycle Amine component used for CO2 removal and tidal breathing capability to emulate the human. The testing and analytical results of the integrated system are presented along with future work.

  4. Allele-Specific Alternative mRNA processing (ASARP) | Informatics Technology for Cancer Research (ITCR)

    A software pipeline for prediction of allele-specific alternative RNA processing events using single RNA-seq data. The current version focuses on prediction of alternative splicing and alternative polyadenylation modulated by genetic variants.

  5. Principles of mRNA transport in yeast.

    Heym, Roland Gerhard; Niessing, Dierk

    2012-06-01

    mRNA localization and localized translation is a common mechanism by which cellular asymmetry is achieved. In higher eukaryotes the mRNA transport machinery is required for such diverse processes as stem cell division and neuronal plasticity. Because mRNA localization in metazoans is highly complex, studies at the molecular level have proven to be cumbersome. However, active mRNA transport has also been reported in fungi including Saccharomyces cerevisiae, Ustilago maydis and Candida albicans, in which these events are less difficult to study. Amongst them, budding yeast S. cerevisiae has yielded mechanistic insights that exceed our understanding of other mRNA localization events to date. In contrast to most reviews, we refrain here from summarizing mRNA localization events from different organisms. Instead we give an in-depth account of ASH1 mRNA localization in budding yeast. This approach is particularly suited to providing a more holistic view of the interconnection between the individual steps of mRNA localization, from transcriptional events to cytoplasmic mRNA transport and localized translation. Because of our advanced mechanistic understanding of mRNA localization in yeast, the present review may also be informative for scientists working, for example, on mRNA localization in embryogenesis or in neurons.

  6. Designing synthetic RNA for delivery by nanoparticles

    Jedrzejczyk, Dominika; Pawlowska, Roza; Chworos, Arkadiusz; Gendaszewska-Darmach, Edyta

    2017-01-01

    The rapid development of synthetic biology and nanobiotechnology has led to the construction of various synthetic RNA nanoparticles of different functionalities and potential applications. As they occur naturally, nucleic acids are an attractive construction material for biocompatible nanoscaffold and nanomachine design. In this review, we provide an overview of the types of RNA and nucleic acid’s nanoparticle design, with the focus on relevant nanostructures utilized for gene-expression regulation in cellular models. Structural analysis and modeling is addressed along with the tools available for RNA structural prediction. The functionalization of RNA-based nanoparticles leading to prospective applications of such constructs in potential therapies is shown. The route from the nanoparticle design and modeling through synthesis and functionalization to cellular application is also described. For a better understanding of the fate of targeted RNA after delivery, an overview of RNA processing inside the cell is also provided. (topical review)

  7. Automated identification of RNA 3D modules with discriminative power in RNA structural alignments

    Theis, Corinna; Höner zu Siederdissen, Christian; Hofacker, Ivo L.

    2013-01-01

    Recent progress in predicting RNA structure is moving towards filling the 'gap' in 2D RNA structure prediction where, for example, predicted internal loops often form non-canonical base pairs. This is increasingly recognized with the steady increase of known RNA 3D modules. There is a general...... comparative evidence. Subsequently, the modules, initially represented by a graph, are turned into models for the RMDetect program, which allows to test their discriminative power using real and randomized Rfam alignments. An initial extraction of 22495 3D modules in all PDB files results in 977 internal loop...

  8. PLEASE: The Python Low-energy Electron Analysis SuitE – Enabling Rapid Analysis of LEEM and LEED Data

    Maxwell Grady

    2018-02-01

    Full Text Available PLEASE, the Python Low-energy Electron Analysis SuitE, provides an open source and cross-platform graphical user interface (GUI for rapid analysis and visualization of low energy electron microscopy (LEEM data sets. LEEM and the associated technique, selected area micro-spot low energy electron diffraction (μ-LEED, are powerful tools for analysis of the surface structure for many novel materials. Specifically, these tools are uniquely suited for the characterization of two-dimensional materials. PLEASE offers a user-friendly point-and-click method for extracting intensity-voltage curves from LEEM and LEED data sets. Analysis of these curves provides insight into the atomic structure of the target material surface with unparalleled resolution.

  9. Myocardial gene expression of microRNA-133a and myosin heavy and light chains, in conjunction with clinical parameters, predict regression of left ventricular hypertrophy after valve replacement in patients with aortic stenosis.

    Villar, Ana V; Merino, David; Wenner, Mareike; Llano, Miguel; Cobo, Manuel; Montalvo, Cecilia; García, Raquel; Martín-Durán, Rafael; Hurlé, Juan M; Hurlé, María A; Nistal, J Francisco

    2011-07-01

    Left ventricular (LV) reverse remodelling after valve replacement in aortic stenosis (AS) has been classically linked to the hydraulic performance of the replacement device, but myocardial status at the time of surgery has received little attention. To establish predictors of LV mass (LVM) regression 1 year after valve replacement in a surgical cohort of patients with AS based on preoperative clinical and echocardiographic parameters and the myocardial gene expression profile at surgery. Transcript levels of remodelling-related proteins and regulators were determined in LV intraoperative biopsies from 46 patients with AS by RT-PCR. Using multiple linear regression analysis, an equation was developed (adjusted R²=0.73; pregression analysis identified microRNA-133a as a significant positive predictor of LVM normalisation, whereas β-myosin heavy chain and BMI constituted negative predictors. Hypertrophy regression 1 year after pressure overload release is related to the preoperative myocardial expression of remodelling-related genes, in conjunction with the patient's clinical background. In this scenario, miR-133 emerges as a key element of the reverse remodelling process. Postoperative improvement of valve haemodynamics does not predict the degree of hypertrophy regression or LVM normalisation. These results led us to reconsider the current reverse remodelling paradigm and (1) to include criteria of hypertrophy reversibility in the decision algorithm used to decide timing for the operation; and (2) to modify other prevailing factors (overweight, diabetes, etc) known to maintain LV hypertrophy.

  10. HumanViCe: Host ceRNA network in virus infected cells in human

    Suman eGhosal

    2014-07-01

    Full Text Available Host-virus interaction via host cellular components has been an important field of research in recent times. RNA interference mediated by short interfering RNAs and microRNAs (miRNA, is a widespread anti-viral defence strategy. Importantly, viruses also encode their own miRNAs. In recent times miRNAs were identified as key players in host-virus interaction. Furthermore, viruses were shown to exploit the host miRNA networks to suite their own need. The complex cross-talk between host and viral miRNAs and their cellular and viral targets forms the environment for viral pathogenesis. Apart from protein-coding mRNAs, non-coding RNAs may also be targeted by host or viral miRNAs in virus infected cells, and viruses can exploit the host miRNA mediated gene regulatory network via the competing endogenous RNA effect. A recent report showed that viral U-rich non-coding RNAs called HSUR, expressed in primate virus herpesvirus saimiri (HVS infected T cells, were able to bind to three host miRNAs, causing significant alteration in cellular level for one of the miRNAs. We have predicted protein coding and non protein-coding targets for viral and human miRNAs in virus infected cells. We identified viral miRNA targets within host non-coding RNA loci from AGO interacting regions in three different virus infected cells. Gene ontology (GO and pathway enrichment analysis of the genes comprising the ceRNA networks in the virus infected cells revealed enrichment of key cellular signalling pathways related to cell fate decisions and gene transcription, like Notch and Wnt signalling pathways, as well as pathways related to viral entry, replication and virulence. We identified a vast number of non-coding transcripts playing as potential ceRNAs to the immune response associated genes; e.g. APOBEC family genes, in some virus infected cells. All these information are compiled in HumanViCe, a comprehensive database that provides the potential ceRNA networks in virus

  11. Measuring Test Case Similarity to Support Test Suite Understanding

    Greiler, M.S.; Van Deursen, A.; Zaidman, A.E.

    2012-01-01

    Preprint of paper published in: TOOLS 2012 - Proceedings of the 50th International Conference, Prague, Czech Republic, May 29-31, 2012; doi:10.1007/978-3-642-30561-0_8 In order to support test suite understanding, we investigate whether we can automatically derive relations between test cases. In

  12. Knowledge Architect : A Tool Suite for Managing Software Architecture Knowledge

    Liang, Peng; Jansen, Anton; Avgeriou, Paris

    2009-01-01

    Management of software architecture knowledge (AK) is vital for improving an organization’s architectural capabilities. To support the architecting process within our industrial partner: Astron, the Dutch radio astronomy institute, we implemented the Knowledge Architect (KA): a tool suite for

  13. The Zoot Suit Riots: Exploring Social Issues in American History

    Chiodo, John J.

    2013-01-01

    The Zoot Suit Riots provide students with a case study of social unrest in American history. The influx of Latinos into the Los Angeles area prior to World War II created high levels of social unrest between Mexican Americans, military servicemen, and local residences. With large numbers of soldiers stationed in the area during the Second World…

  14. 28 CFR 36.503 - Suit by the Attorney General.

    2010-07-01

    ... 28 Judicial Administration 1 2010-07-01 2010-07-01 false Suit by the Attorney General. 36.503... discretion, the Attorney General may commence a civil action in any appropriate United States district court if the Attorney General has reasonable cause to believe that— (a) Any person or group of persons is...

  15. DYNA3D/ParaDyn Regression Test Suite Inventory

    Lin, Jerry I. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)

    2016-09-01

    The following table constitutes an initial assessment of feature coverage across the regression test suite used for DYNA3D and ParaDyn. It documents the regression test suite at the time of preliminary release 16.1 in September 2016. The columns of the table represent groupings of functionalities, e.g., material models. Each problem in the test suite is represented by a row in the table. All features exercised by the problem are denoted by a check mark (√) in the corresponding column. The definition of “feature” has not been subdivided to its smallest unit of user input, e.g., algorithmic parameters specific to a particular type of contact surface. This represents a judgment to provide code developers and users a reasonable impression of feature coverage without expanding the width of the table by several multiples. All regression testing is run in parallel, typically with eight processors, except problems involving features only available in serial mode. Many are strictly regression tests acting as a check that the codes continue to produce adequately repeatable results as development unfolds; compilers change and platforms are replaced. A subset of the tests represents true verification problems that have been checked against analytical or other benchmark solutions. Users are welcomed to submit documented problems for inclusion in the test suite, especially if they are heavily exercising, and dependent upon, features that are currently underrepresented.

  16. Safety Tips: Avoiding Negligence Suits in Chemistry Teaching.

    Gerlovich, Jack A.

    1983-01-01

    Discusses various aspects related to negligence on the part of chemistry teachers. Areas addressed include negligence in tort law, avoiding negligence suits, proper instructions, proper supervision, equipment maintenance, and other considerations such as sovereign immunity, and contributory versus comparative negligence. (JN)

  17. ASIM - an Instrument Suite for the International Space Station

    Neubert, Torsten; Crosby, B.; Huang, T.-Y.

    2009-01-01

    ASIM (Atmosphere-Space Interactions Monitor) is an instrument suite for studies of severe thunderstorms and their effects on the atmosphere and ionosphere. The instruments are designed to observe transient luminous events (TLEs)—sprites, blue jets and elves—and terrestrial gamma-ray flashes (TGFs...

  18. Rimsky-Korsakov: Symphony N2 (Symphonic Suite) / Warrack, John

    Warrack, John

    1990-01-01

    Uuest heliplaadist "Rimsky-Korsakov: Symphony N2 (Symphonic Suite), Op. 9, "Antar" Russian Easter Festival Overture, Op.36. Philharmonia Orchestra, Evgeni Svetlanov. Hyperion KA 66399. CDA 66399. Teise sümfoonia esitust võrreldud Neeme Järvi plaadistusega

  19. Tailoring Vantage 5 (fuel) to suit each operator's need

    Chapin, D L; Secker, J R [Westinghouse Electric Corp., Philadelphia, PA (USA)

    1990-03-01

    By the end of 1989, Westinghouse Vantage 5 fuel had been reloaded into 36 nuclear power plants. The fuel offers a number of features operators can choose from to suit their own particular needs. Experience so far has shown the fuel to have performed well, with coolant activity levels remaining low. (author).

  20. Shielding the messenger (RNA): microRNA-based anticancer therapies

    Sotillo, Elena; Thomas-Tikhonenko, Andrei

    2011-01-01

    It has been a decade since scientists realized that microRNAs (miRNAs) are not an oddity invented by worms to regulate gene expression at post-transcriptional levels. Rather, many of these 21–22-nucleotide-short RNAs exist in invertebrates and vertebrates alike and some of them are in fact highly conserved. miRNAs are now recognized as an important class of non-coding small RNAs that inhibit gene expression by targeting mRNA stability and translation. In the last ten years, our knowledge of the miRNAs world was expanding at vertiginous speed, propelled by the development of computational engines for miRNA identification and target prediction, biochemical tools and techniques to modulate miRNA activity, and last but not least, the emergence of miRNA-centric animal models. One important conclusion that has emerged from this effort is that many microRNAs and their cognate targets are strongly implicated in cancer, either as oncogenes or tumor and metastasis suppressors. In this review we will discuss the diverse role that miRNAs play in cancer initiation and progression and also the tools with which miRNA expression could be corrected in vivo. While the idea of targeting microRNAs towards therapeutic ends is getting considerable traction, basic, translational, and clinical research done in the next few years will tell whether this promise is well-founded. PMID:21514318

  1. Exploration Space Suit Architecture: Destination Environmental-Based Technology Development

    Hill, Terry R.

    2010-01-01

    This paper picks up where EVA Space Suit Architecture: Low Earth Orbit Vs. Moon Vs. Mars (Hill, Johnson, IEEEAC paper #1209) left off in the development of a space suit architecture that is modular in design and interfaces and could be reconfigured to meet the mission or during any given mission depending on the tasks or destination. This paper will walk though the continued development of a space suit system architecture, and how it should evolve to meeting the future exploration EVA needs of the United States space program. In looking forward to future US space exploration and determining how the work performed to date in the CxP and how this would map to a future space suit architecture with maximum re-use of technology and functionality, a series of thought exercises and analysis have provided a strong indication that the CxP space suit architecture is well postured to provide a viable solution for future exploration missions. Through the destination environmental analysis that is presented in this paper, the modular architecture approach provides the lowest mass, lowest mission cost for the protection of the crew given any human mission outside of low Earth orbit. Some of the studies presented here provide a look and validation of the non-environmental design drivers that will become every-increasingly important the further away from Earth humans venture and the longer they are away. Additionally, the analysis demonstrates a logical clustering of design environments that allows a very focused approach to technology prioritization, development and design that will maximize the return on investment independent of any particular program and provide architecture and design solutions for space suit systems in time or ahead of being required for any particular manned flight program in the future. The new approach to space suit design and interface definition the discussion will show how the architecture is very adaptable to programmatic and funding changes with

  2. A path-based measurement for human miRNA functional similarities using miRNA-disease associations

    Ding, Pingjian; Luo, Jiawei; Xiao, Qiu; Chen, Xiangtao

    2016-09-01

    Compared with the sequence and expression similarity, miRNA functional similarity is so important for biology researches and many applications such as miRNA clustering, miRNA function prediction, miRNA synergism identification and disease miRNA prioritization. However, the existing methods always utilized the predicted miRNA target which has high false positive and false negative to calculate the miRNA functional similarity. Meanwhile, it is difficult to achieve high reliability of miRNA functional similarity with miRNA-disease associations. Therefore, it is increasingly needed to improve the measurement of miRNA functional similarity. In this study, we develop a novel path-based calculation method of miRNA functional similarity based on miRNA-disease associations, called MFSP. Compared with other methods, our method obtains higher average functional similarity of intra-family and intra-cluster selected groups. Meanwhile, the lower average functional similarity of inter-family and inter-cluster miRNA pair is obtained. In addition, the smaller p-value is achieved, while applying Wilcoxon rank-sum test and Kruskal-Wallis test to different miRNA groups. The relationship between miRNA functional similarity and other information sources is exhibited. Furthermore, the constructed miRNA functional network based on MFSP is a scale-free and small-world network. Moreover, the higher AUC for miRNA-disease prediction indicates the ability of MFSP uncovering miRNA functional similarity.

  3. A folding algorithm for extended RNA secondary structures.

    Höner zu Siederdissen, Christian; Bernhart, Stephan H; Stadler, Peter F; Hofacker, Ivo L

    2011-07-01

    RNA secondary structure contains many non-canonical base pairs of different pair families. Successful prediction of these structural features leads to improved secondary structures with applications in tertiary structure prediction and simultaneous folding and alignment. We present a theoretical model capturing both RNA pair families and extended secondary structure motifs with shared nucleotides using 2-diagrams. We accompany this model with a number of programs for parameter optimization and structure prediction. All sources (optimization routines, RNA folding, RNA evaluation, extended secondary structure visualization) are published under the GPLv3 and available at www.tbi.univie.ac.at/software/rnawolf/.

  4. Prokofieff: Krieg und Frieden (Sinfonische Suite), Die Verlobung im Kloster (Sommernacht-Suite), Russische Overtüre. Philharmonia Orchestra, Neeme Järvi / G. W.

    G. W.

    1993-01-01

    Uuest heliplaadist "Prokofieff: Krieg und Frieden (Sinfonische Suite), Die Verlobung im Kloster (Sommernacht-Suite), Russische Overtüre. Philharmonia Orchestra, Neeme Järvi. (AD: 1991). Chandos/Koch CD 9096

  5. Human Enterovirus Nonstructural Protein 2CATPase Functions as Both an RNA Helicase and ATP-Independent RNA Chaperone

    Xia, Hongjie; Wang, Peipei; Wang, Guang-Chuan; Yang, Jie; Sun, Xianlin; Wu, Wenzhe; Qiu, Yang; Shu, Ting; Zhao, Xiaolu; Yin, Lei; Qin, Cheng-Feng; Hu, Yuanyang; Zhou, Xi

    2015-01-01

    RNA helicases and chaperones are the two major classes of RNA remodeling proteins, which function to remodel RNA structures and/or RNA-protein interactions, and are required for all aspects of RNA metabolism. Although some virus-encoded RNA helicases/chaperones have been predicted or identified, their RNA remodeling activities in vitro and functions in the viral life cycle remain largely elusive. Enteroviruses are a large group of positive-stranded RNA viruses in the Picornaviridae family, which includes numerous important human pathogens. Herein, we report that the nonstructural protein 2CATPase of enterovirus 71 (EV71), which is the major causative pathogen of hand-foot-and-mouth disease and has been regarded as the most important neurotropic enterovirus after poliovirus eradication, functions not only as an RNA helicase that 3′-to-5′ unwinds RNA helices in an adenosine triphosphate (ATP)-dependent manner, but also as an RNA chaperone that destabilizes helices bidirectionally and facilitates strand annealing and complex RNA structure formation independently of ATP. We also determined that the helicase activity is based on the EV71 2CATPase middle domain, whereas the C-terminus is indispensable for its RNA chaperoning activity. By promoting RNA template recycling, 2CATPase facilitated EV71 RNA synthesis in vitro; when 2CATPase helicase activity was impaired, EV71 RNA replication and virion production were mostly abolished in cells, indicating that 2CATPase-mediated RNA remodeling plays a critical role in the enteroviral life cycle. Furthermore, the RNA helicase and chaperoning activities of 2CATPase are also conserved in coxsackie A virus 16 (CAV16), another important enterovirus. Altogether, our findings are the first to demonstrate the RNA helicase and chaperoning activities associated with enterovirus 2CATPase, and our study provides both in vitro and cellular evidence for their potential roles during viral RNA replication. These findings increase our

  6. Conformational Selection and Induced Fit for RNA Polymerase and RNA/DNA Hybrid Backtracked Recognition

    Haifeng eChen

    2015-11-01

    Full Text Available RNA polymerase catalyzes transcription with a high fidelity. If DNA/RNA mismatch or DNA damage occurs downstream, a backtracked RNA polymerase can proofread this situation. However, the backtracked mechanism is still poorly understood. Here we have performed multiple explicit-solvent molecular dynamics (MD simulations on bound and apo DNA/RNA hybrid to study backtracked recognition. MD simulations at room temperature suggest that specific electrostatic interactions play key roles in the backtracked recognition between the polymerase and DNA/RNA hybrid. Kinetics analysis at high temperature shows that bound and apo DNA/RNA hybrid unfold via a two-state process. Both kinetics and free energy landscape analyses indicate that bound DNA/RNA hybrid folds in the order of DNA/RNA contracting, the tertiary folding and polymerase binding. The predicted Φ-values suggest that C7, G9, dC12, dC15 and dT16 are key bases for the backtracked recognition of DNA/RNA hybrid. The average RMSD values between the bound structures and the corresponding apo ones and Kolmogorov-Smirnov (KS P test analyses indicate that the recognition between DNA/RNA hybrid and polymerase might follow an induced fit mechanism for DNA/RNA hybrid and conformation selection for polymerase. Furthermore, this method could be used to relative studies of specific recognition between nucleic acid and protein.

  7. STS-95 Mission Specialist Pedro Duque suits up for launch

    1998-01-01

    STS-95 Mission Specialist Pedro Duque of Spain, with the European Space Agency, is helped with his flight suit by suit tech Tommy McDonald in the Operations and Checkout Building. The final fitting takes place prior to the crew walkout and transport to Launch Pad 39B. Targeted for launch at 2 p.m. EST on Oct. 29, the mission is expected to last 8 days, 21 hours and 49 minutes, and return to KSC at 11:49 a.m. EST on Nov. 7. The STS-95 mission includes research payloads such as the Spartan solar-observing deployable spacecraft, the Hubble Space Telescope Orbital Systems Test Platform, the International Extreme Ultraviolet Hitchhiker, as well as the SPACEHAB single module with experiments on space flight and the aging process.

  8. Failure to exercise due diligence costs plaintiff her suit.

    1997-11-28

    The Mississippi State Supreme Court affirmed a lower court ruling dismissing a last-minute suit filed by a plaintiff against United Blood Services of Mississippi and the American Association of Blood Banks. A woman known as D. Doe was a recipient of a tainted transfusion. She contracted HIV in 1983 and died of AIDS-related causes in 1991. Her daughter, the plaintiff, filed a contaminated blood transfusion lawsuit just five days before the statute of limitations ran out but failed to ascertain the correct identity of the blood bank. She named two blood banks in her suit because she was unable to determine the source of the blood. The Supreme Court ruled that waiting until five days before the statute elapsed indicated that the plaintiff did not exercise reasonable diligence within a specific time frame.

  9. STS-90 Pilot Scott Altman is suited up for launch

    1998-01-01

    STS-90 Pilot Scott Altman is assisted during suit-up activities by Lockheed Suit Technician Valerie McNeil from Johnson Space Center in KSC's Operations and Checkout Building. Altman and the rest of the STS-90 crew will shortly depart for Launch Pad 39B, where the Space Shuttle Columbia awaits a second liftoff attempt at 2:19 p.m. EDT. His first trip into space, Altman is participating in a life sciences research flight that will focus on the most complex and least understood part of the human body - - the nervous system. Neurolab will examine the effects of spaceflight on the brain, spinal cord, peripheral nerves and sensory organs in the human body.

  10. Mission Specialist Scott Parazynski checks his flight suit

    1998-01-01

    STS-95 Mission Specialist Scott E. Parazynski gets help with his flight suit in the Operations and Checkout Building from a suit technician George Brittingham. The final fitting takes place prior to the crew walkout and transport to Launch Pad 39B. Targeted for launch at 2 p.m. EST on Oct. 29, the mission is expected to last 8 days, 21 hours and 49 minutes, and return to KSC at 11:49 a.m. EST on Nov. 7. The STS-95 mission includes research payloads such as the Spartan solar-observing deployable spacecraft, the Hubble Space Telescope Orbital Systems Test Platform, the International Extreme Ultraviolet Hitchhiker, as well as the SPACEHAB single module with experiments on space flight and the aging process.

  11. STS-76 Payload Cmdr Ronald Sega suits up

    1996-01-01

    STS-76 Payload Commander Ronald M. Sega is donning his launch/entry suit in the Operations and Checkout Building with assistance from a suit technician. The third docking between the Russian Space Station Mir and the U.S. Space Shuttle marks the second trip into space for Sega, who recently served a five-month assignment in Russia as operations director for NASA activities there. Once suitup activities are completed the six-member STS-76 flight crew will depart for Launch Pad 39B, where the Space Shuttle Atlantis is undergoing final preparations for liftoff during an approximately seven-minute launch window opening around 3:13 a.m. EST, March 22.

  12. The IMBA suite: integrated modules for bioassay analysis

    Birchall, A.; Jarvis, N.S.; Peace, M.S.; Riddell, A.E.; Battersby, W.P

    1998-07-01

    The increasing complexity of models representing the biokinetic behaviour of radionuclides in the body following intake poses problems for people who are required to implement these models. The problem is exacerbated by the current paucity of suitable software. In order to remedy this situation, a collaboration between British Nuclear Fuels, Westlakes Research Institute and the National Radiological Protection Board has started with the aim of producing a suite of modules for estimating intakes and doses from bioassay measurements using the new ICRP models. Each module will have a single purpose (e.g. to calculate respiratory tract deposition) and will interface with other software using data files. The elements to be implemented initially are plutonium, uranium, caesium, iodine and tritium. It is intended to make the software available to other parties under terms yet to be decided. This paper describes the proposed suite of integrated modules for bioassay analysis, IMBA. (author)

  13. Profiled support vector machines for antisense oligonucleotide efficacy prediction

    Martín-Guerrero José D

    2004-09-01

    Full Text Available Abstract Background This paper presents the use of Support Vector Machines (SVMs for prediction and analysis of antisense oligonucleotide (AO efficacy. The collected database comprises 315 AO molecules including 68 features each, inducing a problem well-suited to SVMs. The task of feature selection is crucial given the presence of noisy or redundant features, and the well-known problem of the curse of dimensionality. We propose a two-stage strategy to develop an optimal model: (1 feature selection using correlation analysis, mutual information, and SVM-based recursive feature elimination (SVM-RFE, and (2 AO prediction using standard and profiled SVM formulations. A profiled SVM gives different weights to different parts of the training data to focus the training on the most important regions. Results In the first stage, the SVM-RFE technique was most efficient and robust in the presence of low number of samples and high input space dimension. This method yielded an optimal subset of 14 representative features, which were all related to energy and sequence motifs. The second stage evaluated the performance of the predictors (overall correlation coefficient between observed and predicted efficacy, r; mean error, ME; and root-mean-square-error, RMSE using 8-fold and minus-one-RNA cross-validation methods. The profiled SVM produced the best results (r = 0.44, ME = 0.022, and RMSE= 0.278 and predicted high (>75% inhibition of gene expression and low efficacy (http://aosvm.cgb.ki.se/. Conclusions The SVM approach is well suited to the AO prediction problem, and yields a prediction accuracy superior to previous methods. The profiled SVM was found to perform better than the standard SVM, suggesting that it could lead to improvements in other prediction problems as well.

  14. ARMOUR – A Rice miRNA: mRNA Interaction Resource

    Neeti Sanan-Mishra; Anita Tripathi; Kavita Goswami; Rohit N. Shukla; Madavan Vasudevan; Hitesh Goswami

    2018-01-01

    ARMOUR was developed as ARice miRNA:mRNA interaction resource. This informative and interactive database includes the experimentally validated expression profiles of miRNAs under different developmental and abiotic stress conditions across seven Indian rice cultivars. This comprehensive database covers 689 known and 1664 predicted novel miRNAs and their expression profiles in more than 38 different tissues or conditions along with their predicted/known target transcripts. The understanding of...

  15. Enhanced verification test suite for physics simulation codes

    Kamm, James R.; Brock, Jerry S.; Brandon, Scott T.; Cotrell, David L.; Johnson, Bryan; Knupp, Patrick; Rider, William J.; Trucano, Timothy G.; Weirs, V. Gregory

    2008-09-01

    This document discusses problems with which to augment, in quantity and in quality, the existing tri-laboratory suite of verification problems used by Los Alamos National Laboratory (LANL), Lawrence Livermore National Laboratory (LLNL), and Sandia National Laboratories (SNL). The purpose of verification analysis is demonstrate whether the numerical results of the discretization algorithms in physics and engineering simulation codes provide correct solutions of the corresponding continuum equations.

  16. Non-Venting Thermal and Humidity Control for EVA Suits

    Izenson, Mike; Chen, Weibo; Bue, Grant

    2011-01-01

    Future EVA suits need processes and systems to control internal temperature and humidity without venting water to the environment. This paper describes an absorption-based cooling and dehumidification system as well as laboratory demonstrations of the key processes. There are two main components in the system: an evaporation cooling and dehumidification garment (ECDG) that removes both sensible heat and latent heat from the pressure garment, and an absorber radiator that absorbs moisture and rejects heat to space by thermal radiation. This paper discusses the overall design of both components, and presents recent data demonstrating their operation. We developed a design and fabrication approach to produce prototypical heat/water absorbing elements for the ECDG, and demonstrated by test that these elements could absorb heat and moisture at a high flux. Proof-of-concept tests showed that an ECDG prototype absorbs heat and moisture at a rate of 85 W/ft under conditions that simulate operation in an EVA suit. The heat absorption was primarily due to direct absorption of water vapor. It is possible to construct large, flexible, durable cooling patches that can be incorporated into a cooling garment with this system. The proof-of-concept test data was scaled to calculate area needed for full metabolic loads, thus showing that it is feasible to use this technology in an EVA suit. Full-scale, lightweight absorber/radiator modules have also been built and tested. They can reject heat at a flux of 33 W/ft while maintaining ECDG operation at conditions that will provide a cool and dry environment inside the EVA suit.

  17. Compression under a mechanical counter pressure space suit glove

    Waldie, James M A.; Tanaka, Kunihiko; Tourbier, Dietmar; Webb, Paul; Jarvis, Christine W.; Hargens, Alan R.

    2002-01-01

    Background: Current gas-pressurized space suits are bulky stiff shells severely limiting astronaut function and capability. A mechanical counter pressure (MCP) space suit in the form of a tight elastic garment could dramatically improve extravehicular activity (EVA) dexterity, but also be advantageous in safety, cost, mass and volume. The purpose of this study was to verify that a prototype MCP glove exerts the design compression of 200 mmHg, a pressure similar to the current NASA EVA suit. Methods: Seven male subjects donned a pressure measurement array and MCP glove on the right hand, which was placed into a partial vacuum chamber. Average compression was recorded on the palm, the bottom of the middle finger, the top of the middle finger and the dorsum of the hand at pressures of 760 (ambient), 660 and 580 mmHg. The vacuum chamber was used to simulate the pressure difference between the low breathing pressure of the current NASA space suits (approximately 200 mmHg) and an unprotected hand in space. Results: At ambient conditions, the MCP glove compressed the dorsum of the hand at 203.5 +/- 22.7 mmHg, the bottom of the middle finger at 179.4 +/- 16.0 mmHg, and the top of the middle finger at 183.8 +/- 22.6 mmHg. The palm compression was significantly lower (59.6 +/- 18.8 mmHg, pglove compression with the chamber pressure reductions. Conclusions: The MCP glove compressed the dorsum of the hand and middle finger at the design pressure.

  18. Astronaut Ronald Evans is suited up for EVA training

    1972-01-01

    Astronaut Ronald E. Evans, command module pilot of the Apollo 17 lunar landing mission, is assisted by technicians in suiting up for extravehicular activity (EVA) training in a water tank in bldg 5 at the Manned Spacecraft Center (49970); Evans participates in EVA training in a water tank in bldg 5 at the Manned Spacecraft Center. The structure in the picture simulates the Scientific Instrument Module (SIM) bay of the Apollo 17 Service Module (49971).

  19. Apollo 11 astronaut Neil Armstrong suits up before launch

    1969-01-01

    Apollo 11 Commander Neil Armstrong prepares to put on his helmet with the assistance of a spacesuit technician during suiting operations in the Manned Spacecraft Operations Building (MSOB) prior to the astronauts' departure to Launch Pad 39A. The three astronauts, Edwin E. Aldrin Jr., Neil A Armstrong and Michael Collins, will then board the Saturn V launch vehicle, scheduled for a 9:32 a.m. EDT liftoff, for the first manned lunar landing mission.

  20. The Sample Analysis at Mars Investigation and Instrument Suite

    Mahaffy, Paul; Webster, Christopher R.; Conrad, Pamela G.; Arvey, Robert; Bleacher, Lora; Brinckerhoff, William B.; Eigenbrode, Jennifer L.; Chalmers, Robert A.; Dworkin, Jason P.; Errigo, Therese; hide

    2012-01-01

    The Sample Analysis at Mars (SAM) investigation of the Mars Science Laboratory (MSL) addresses the chemical and isotopic composition of the atmosphere and volatiles extracted from solid samples. The SAM investigation is designed to contribute substantially to the mission goal of quantitatively assessing the habitability of Mars as an essential step in the search for past or present life on Mars. SAM is a 40 kg instrument suite located in the interior of MSL's Curiosity rover. The SAM instruments are a quadrupole mass spectrometer, a tunable laser spectrometer, and a 6-column gas chromatograph all coupled through solid and gas processing systems to provide complementary information on the same samples. The SAM suite is able to measure a suite of light isotopes and to analyze volatiles directly from the atmosphere or thermally released from solid samples. In addition to measurements of simple inorganic compounds and noble gases SAM will conduct a sensitive search for organic compounds with either thermal or chemical extraction from sieved samples delivered by the sample processing system on the Curiosity rover's robotic arm,

  1. Statutes of limitations: the special problem of DES suits

    Feigin, C.A.

    1981-01-01

    In 1971, medical studies determined that DES causes a rare type of vaginal cancer in a small number of daughters of mothers who took DES during pregnancy. Subsequently, medical studies determined that exposure to DES can cause other vaginal abnormalities in the daughters, some of which may be precancerous. As a result of these discoveries, many lawsuits have been filed by these daughters against DES manufacturers. Many DES suits may be barred by statutes of limitations, both because the number of years between the daughters' exposure to DES in utero and the discovery that DES can cause injuries exceeds the statutory period, and because the cancer or other injuries caused by DES may not develop for many additional years. This Note discusses two methods that DES plaintiffs may be able to use to overcome the potential statutes of limitations bar: the discovery rule, and state provisions which toll the statute of limitations for minors. The Note contends that courts should apply an expanded discovery rule to DES suits to avoid the unfair result of barring a claim before the plaintiff could have known that she had a cause of action. In addition, the Note argues that the injury which causes the statute of limitations to begin to run in DES suits should not be rigidly defined. Finally, the Note urges that courts allow eligible DES plaintiffs to take advantage of applicable state provisions that toll the statute of limitations for minors

  2. Perfectionism, selected demographic and job characteristics as predictors of burnout in operating suite nurses

    Dorota Włodarczyk

    2013-12-01

    Full Text Available Background: The study was aimed at verifying the predictive power of perfectionism for professional burnout among nurses exposed to distress resulting from work in an operating suite and testing whether this effect exists after controlling for selected demographic and job characteristics. Material and Methods: The study group consisted of 100 nurses (93 women; mean age: 38.67 years. The majority in the group worked in public facilities (68%, in duty system (62%, as operating (75% or anesthesiology (25% nurses. To test perfectionism The Polish Adaptive and Maladaptive Perfectionism Questionnaire (AMPQ (Perfekcjonizm Adaptacyjny i Dezadaptacyjny - PAD, developed by Szczucka, was used. To examine burnout the Oldenburg Burnout Inventory (OLBI by Demerouti et al. was adopted. The effects of selected demographic and job characteristics were controlled. Results: The results of hierarchical regression analyses revealed that after controlling for selected demographic and job characteristics maladaptive perfectionism was a significant predictor of disengagement and exhaustion whereas adaptive perfectionism predicted a better work engagement. Significant predictors were also: education, number of workplaces, duty system and marital status. Conclusions: The study allowed to confirm the hypothesis on a harmful role of maladaptive perfectionism in shaping burnout among operating suite nurses. The hypothesis on protective function of adaptive perfectionism was confirmed only partially, with regard to disengagement. The results of the study also highlighted some risk factors of burnout which may exist in this occupational group. This confirms the need to continue research in this area. Med Pr 2013;64(6:761–773

  3. 46 CFR 199.214 - Immersion suits and thermal protective aids.

    2010-10-01

    ... 46 Shipping 7 2010-10-01 2010-10-01 false Immersion suits and thermal protective aids. 199.214... Passenger Vessels § 199.214 Immersion suits and thermal protective aids. (a) Each passenger vessel must... an immersion suit. (c) The immersion suits and thermal protective aids required under paragraphs (a...

  4. 33 CFR 150.518 - What are the inspection requirements for work vests and immersion suits?

    2010-07-01

    ... requirements for work vests and immersion suits? 150.518 Section 150.518 Navigation and Navigable Waters COAST... vests and immersion suits? (a) All work vests and immersion suits must be inspected by the owner or... a work vest or immersion suit is inspected and is in serviceable condition, then it may remain in...

  5. RNA modifications by oxidation

    Poulsen, Henrik E; Specht, Elisabeth; Broedbaek, Kasper

    2012-01-01

    to encompass various classes of novel regulatory RNAs, including, e.g., microRNAs. It is well known that DNA is constantly oxidized and repaired by complex genome maintenance mechanisms. Analogously, RNA also undergoes significant oxidation, and there are now convincing data suggesting that oxidation......The past decade has provided exciting insights into a novel class of central (small) RNA molecules intimately involved in gene regulation. Only a small percentage of our DNA is translated into proteins by mRNA, yet 80% or more of the DNA is transcribed into RNA, and this RNA has been found......, and the consequent loss of integrity of RNA, is a mechanism for disease development. Oxidized RNA is found in a large variety of diseases, and interest has been especially devoted to degenerative brain diseases such as Alzheimer disease, in which up to 50-70% of specific mRNA molecules are reported oxidized, whereas...

  6. SRD: a Staphylococcus regulatory RNA database.

    Sassi, Mohamed; Augagneur, Yoann; Mauro, Tony; Ivain, Lorraine; Chabelskaya, Svetlana; Hallier, Marc; Sallou, Olivier; Felden, Brice

    2015-05-01

    An overflow of regulatory RNAs (sRNAs) was identified in a wide range of bacteria. We designed and implemented a new resource for the hundreds of sRNAs identified in Staphylococci, with primary focus on the human pathogen Staphylococcus aureus. The "Staphylococcal Regulatory RNA Database" (SRD, http://srd.genouest.org/) compiled all published data in a single interface including genetic locations, sequences and other features. SRD proposes novel and simplified identifiers for Staphylococcal regulatory RNAs (srn) based on the sRNA's genetic location in S. aureus strain N315 which served as a reference. From a set of 894 sequences and after an in-depth cleaning, SRD provides a list of 575 srn exempt of redundant sequences. For each sRNA, their experimental support(s) is provided, allowing the user to individually assess their validity and significance. RNA-seq analysis performed on strains N315, NCTC8325, and Newman allowed us to provide further details, upgrade the initial annotation, and identified 159 RNA-seq independent transcribed sRNAs. The lists of 575 and 159 sRNAs sequences were used to predict the number and location of srns in 18 S. aureus strains and 10 other Staphylococci. A comparison of the srn contents within 32 Staphylococcal genomes revealed a poor conservation between species. In addition, sRNA structure predictions obtained with MFold are accessible. A BLAST server and the intaRNA program, which is dedicated to target prediction, were implemented. SRD is the first sRNA database centered on a genus; it is a user-friendly and scalable device with the possibility to submit new sequences that should spread in the literature. © 2015 Sassi et al.; Published by Cold Spring Harbor Laboratory Press for the RNA Society.

  7. Suited versus unsuited analog astronaut performance using the Aouda.X space suit simulator: the DELTA experiment of MARS2013.

    Soucek, Alexander; Ostkamp, Lutz; Paternesi, Roberta

    2015-04-01

    Space suit simulators are used for extravehicular activities (EVAs) during Mars analog missions. Flight planning and EVA productivity require accurate time estimates of activities to be performed with such simulators, such as experiment execution or traverse walking. We present a benchmarking methodology for the Aouda.X space suit simulator of the Austrian Space Forum. By measuring and comparing the times needed to perform a set of 10 test activities with and without Aouda.X, an average time delay was derived in the form of a multiplicative factor. This statistical value (a second-over-second time ratio) is 1.30 and shows that operations in Aouda.X take on average a third longer than the same operations without the suit. We also show that activities predominantly requiring fine motor skills are associated with larger time delays (between 1.17 and 1.59) than those requiring short-distance locomotion or short-term muscle strain (between 1.10 and 1.16). The results of the DELTA experiment performed during the MARS2013 field mission increase analog mission planning reliability and thus EVA efficiency and productivity when using Aouda.X.

  8. FRHAM-TEX trademark cool suit - OST reference No. 1854. Deactivation and decommissioning focus area

    1998-02-01

    This paper describes a demonstration project for the FRHAM-TEX Cool Suit trademark manufactured by FRHAM Safety Products. It is a one-piece, disposable, breathable, waterproof coverall designed to permit moisture generated by the wearer to be transmitted outside the suit. The performance of this suit was compared to a Tyvek reg-sign suit as a baseline. The suit is proposed as safety ware for workers at decontamination and decommissioning projects

  9. Working with RNA

    Nielsen, Henrik

    2011-01-01

    Working with RNA is not a special discipline in molecular biology. However, RNA is chemically and structurally different from DNA and a few simple work rules have to be implemented to maintain the integrity of the RNA. Alkaline pH, high temperatures, and heavy metal ions should be avoided when po...

  10. Combining miRNA and mRNA Expression Profiles in Wilms Tumor Subtypes

    Nicole Ludwig

    2016-03-01

    Full Text Available Wilms tumor (WT is the most common childhood renal cancer. Recent findings of mutations in microRNA (miRNA processing proteins suggest a pivotal role of miRNAs in WT genesis. We performed miRNA expression profiling of 36 WTs of different subtypes and four normal kidney tissues using microarrays. Additionally, we determined the gene expression profile of 28 of these tumors to identify potentially correlated target genes and affected pathways. We identified 85 miRNAs and 2107 messenger RNAs (mRNA differentially expressed in blastemal WT, and 266 miRNAs and 1267 mRNAs differentially expressed in regressive subtype. The hierarchical clustering of the samples, using either the miRNA or mRNA profile, showed the clear separation of WT from normal kidney samples, but the miRNA pattern yielded better separation of WT subtypes. A correlation analysis of the deregulated miRNA and mRNAs identified 13,026 miRNA/mRNA pairs with inversely correlated expression, of which 2844 are potential interactions of miRNA and their predicted mRNA targets. We found significant upregulation of miRNAs-183, -301a/b and -335 for the blastemal subtype, and miRNAs-181b, -223 and -630 for the regressive subtype. We found marked deregulation of miRNAs regulating epithelial to mesenchymal transition, especially in the blastemal subtype, and miRNAs influencing chemosensitivity, especially in regressive subtypes. Further research is needed to assess the influence of preoperative chemotherapy and tumor infiltrating lymphocytes on the miRNA and mRNA patterns in WT.

  11. Determination of an effective scoring function for RNA-RNA interactions with a physics-based double-iterative method.

    Yan, Yumeng; Wen, Zeyu; Zhang, Di; Huang, Sheng-You

    2018-05-18

    RNA-RNA interactions play fundamental roles in gene and cell regulation. Therefore, accurate prediction of RNA-RNA interactions is critical to determine their complex structures and understand the molecular mechanism of the interactions. Here, we have developed a physics-based double-iterative strategy to determine the effective potentials for RNA-RNA interactions based on a training set of 97 diverse RNA-RNA complexes. The double-iterative strategy circumvented the reference state problem in knowledge-based scoring functions by updating the potentials through iteration and also overcame the decoy-dependent limitation in previous iterative methods by constructing the decoys iteratively. The derived scoring function, which is referred to as DITScoreRR, was evaluated on an RNA-RNA docking benchmark of 60 test cases and compared with three other scoring functions. It was shown that for bound docking, our scoring function DITScoreRR obtained the excellent success rates of 90% and 98.3% in binding mode predictions when the top 1 and 10 predictions were considered, compared to 63.3% and 71.7% for van der Waals interactions, 45.0% and 65.0% for ITScorePP, and 11.7% and 26.7% for ZDOCK 2.1, respectively. For unbound docking, DITScoreRR achieved the good success rates of 53.3% and 71.7% in binding mode predictions when the top 1 and 10 predictions were considered, compared to 13.3% and 28.3% for van der Waals interactions, 11.7% and 26.7% for our ITScorePP, and 3.3% and 6.7% for ZDOCK 2.1, respectively. DITScoreRR also performed significantly better in ranking decoys and obtained significantly higher score-RMSD correlations than the other three scoring functions. DITScoreRR will be of great value for the prediction and design of RNA structures and RNA-RNA complexes.

  12. Methods for RNA Analysis

    Olivarius, Signe

    of the transcriptome, 5’ end capture of RNA is combined with next-generation sequencing for high-throughput quantitative assessment of transcription start sites by two different methods. The methods presented here allow for functional investigation of coding as well as noncoding RNA and contribute to future...... RNAs rely on interactions with proteins, the establishment of protein-binding profiles is essential for the characterization of RNAs. Aiming to facilitate RNA analysis, this thesis introduces proteomics- as well as transcriptomics-based methods for the functional characterization of RNA. First, RNA...

  13. Microbiome Data Accurately Predicts the Postmortem Interval Using Random Forest Regression Models

    Aeriel Belk

    2018-02-01

    Full Text Available Death investigations often include an effort to establish the postmortem interval (PMI in cases in which the time of death is uncertain. The postmortem interval can lead to the identification of the deceased and the validation of witness statements and suspect alibis. Recent research has demonstrated that microbes provide an accurate clock that starts at death and relies on ecological change in the microbial communities that normally inhabit a body and its surrounding environment. Here, we explore how to build the most robust Random Forest regression models for prediction of PMI by testing models built on different sample types (gravesoil, skin of the torso, skin of the head, gene markers (16S ribosomal RNA (rRNA, 18S rRNA, internal transcribed spacer regions (ITS, and taxonomic levels (sequence variants, species, genus, etc.. We also tested whether particular suites of indicator microbes were informative across different datasets. Generally, results indicate that the most accurate models for predicting PMI were built using gravesoil and skin data using the 16S rRNA genetic marker at the taxonomic level of phyla. Additionally, several phyla consistently contributed highly to model accuracy and may be candidate indicators of PMI.

  14. The PAUL Suit(©) : an experience of ageing.

    Bennett, Paul; Moore, Malcolm; Wenham, John

    2016-04-01

    An ageing population worldwide makes it increasingly important that health students understand issues that elderly people face and can provide empathic care to them. This teaching department in an isolated rural setting developed an interprofessional learning session to assist health students to understand issues of functional loss and social isolation that can affect elderly people. The Premature Ageing Unisex Leisure (PAUL) Suit(©) was developed as part of a 1-day learning session for undergraduate health students - including students of medicine, nursing and allied health - attending clinical placement in far-west New South Wales. The suit was developed locally and can be adjusted to simulate a wide range of functional losses in the wearer. Students undertake a range of daily tasks in the community while wearing the suit in the company of a student 'carer'. Over the past 4 years, approximately 140 students have participated in the simulation. Post-simulation evaluations report that students gain a greater understanding of some functional issues associated with ageing, and of the social isolation that can be associated with these. The experiential nature of the activity leads to some powerful insights. This activity is an innovative, experiential tool to deepen students understanding of issues related to ageing This activity is an innovative, experiential tool to deepen students understanding of issues relating to ageing. The interprofessional nature of the activity is an important factor in the success of the day, and produces a wide range of shared insights. The activity also enhances the partnerships between the university, the health service and the local community. Our experience supports the value of simulation in providing a deep learning opportunity in the area of ageing and disability. © 2015 John Wiley & Sons Ltd.

  15. pcircle - A Suite of Scalable Parallel File System Tools

    2015-10-01

    Most of the software related to file system are written for conventional local file system, they are serialized and can't take advantage of the benefit of a large scale parallel file system. "pcircle" software builds on top of ubiquitous MPI in cluster computing environment and "work-stealing" pattern to provide a scalable, high-performance suite of file system tools. In particular - it implemented parallel data copy and parallel data checksumming, with advanced features such as async progress report, checkpoint and restart, as well as integrity checking.

  16. The Chernobyl cloud: comments on a non-suit

    2011-01-01

    This article comments the non-suit decision taken by a Paris court at the benefit of Pierre Pellerin after a trial about his declarations concerning the Chernobyl cloud. It recalls the great number of controls of radioactive contamination levels performed in France at this time by the SCRPI with Mr Pellerin at its head. It states that French authorities behaved like other European authorities with respect to the contamination brought by the cloud, that no epidemiological study has ever revealed pathologies which could be due to the cloud, and that the increase of cancers in Corsica is not proved

  17. OpenMP 4.5 Validation and Verification Suite

    2017-12-15

    OpenMP, a directive-based programming API, introduce directives for accelerator devices that programmers are starting to use more frequently in production codes. To make sure OpenMP directives work correctly across architectures, it is critical to have a mechanism that tests for an implementation's conformance to the OpenMP standard. This testing process can uncover ambiguities in the OpenMP specification, which helps compiler developers and users make a better use of the standard. We fill this gap through our validation and verification test suite that focuses on the offload directives available in OpenMP 4.5.

  18. Cytoplasmic Z-RNA

    Zarling, D.A.; Calhoun, C.J.; Hardin, C.C.; Zarling, A.H.

    1987-01-01

    Specific immunochemical probes for Z-RNA were generated and characterized to search for possible Z-RNA-like double helices in cells. Z-RNA was detected in the cytoplasm of fixed protozoan cells by immunofluorescence microscopy using these anti-Z-RNA IgCs. In contrast, autoimmune or experimentally elicited anti-DNA antibodies, specifically reactive with B-DNA or Z-DNA, stained the nuclei. Pre-or nonimmune IgGs did not bind to the cells. RNase A or T1 digestion eliminated anti-Z-RNA IgG binding to cytoplasmic determinants; however, DNase I or mung bean nuclease had no effect. Doxorubicin and ethidium bromide prevented anti-Z-RNA antibody binding; however, actinomycin D, which does not bind double-stranded RNA, did not. Anti-Z-RNA immunofluorescence was specifically blocked in competition assays by synthetic Z-RNA but not Z-DNA, A-RNA, or single-stranded RNAs. Thus, some cytoplasmic sequences in fixed cells exist in the left-handed Z-RNA conformation

  19. Non-coding RNA in Deinococcus radiodurans

    Chen Zhongzhong; Wang Liangyan; Lin Jun; Tian Bing; Hua Yuejin

    2006-01-01

    Researches on DNA damage and repair pathways of Deinococcus radiodurans show its extreme resistance to ionizing radiation, ultraviolet radiation and reactive oxygen species. Non-coding (ncRNA) RNAs are involved in a variety of processes such as transcriptional regulations, RNA processing and modification, mRNA translation, protein transportation and stability. The conserved secondary structures of intergenic regions of Deinococcus radiodurans R1 were predicted using Stochastic Context Free Grammar (SCFG) scan strategy. Results showed that 28 ncRNA families were present in the non-coding regions of the genome of Deinococcus radiodurans R1. Among these families, IRE is the largest family, followed by Histone3, tRNA, SECIS. DicF, ctRNA-pGA1 and tmRNA are one discovered in bacteria. Results from the comparison with other organisms showed that these ncRNA can be applied to the study of biological function of Deinococcus radiodurans and supply reference for the further study of DNA damage and repair mechanisms of this bacterium. (authors)

  20. Anesthesia and the pediatric cardiac catheterization suite: a review.

    Lam, Jennifer E; Lin, Erica P; Alexy, Ryan; Aronson, Lori A

    2015-02-01

    Advances in technology over the last couple of decades have caused a shift in pediatric cardiac catheterization from a primary focus on diagnostics to innovative therapeutic interventions. These improvements allow patients a wider range of nonsurgical options for treatment of congenital heart disease. However, these therapeutic modalities can entail higher risk in an already complex patient population, compounded by the added challenges inherent to the environment of the cardiac catheterization suite. Anesthesiologists caring for children with congenital heart disease must understand not only the pathophysiology of the disease but also the effects the anesthetics and interventions have on the patient in order to provide a safe perioperative course. It is the aim of this article to review the latest catheterization modalities offered to patients with congenital heart disease, describe the unique challenges presented in the cardiac catheterization suite, list the most common complications encountered during catheterization and finally, to review the literature regarding different anesthetic drugs used in the catheterization lab. © 2014 John Wiley & Sons Ltd.

  1. SSAGES: Software Suite for Advanced General Ensemble Simulations

    Sidky, Hythem; Colón, Yamil J.; Helfferich, Julian; Sikora, Benjamin J.; Bezik, Cody; Chu, Weiwei; Giberti, Federico; Guo, Ashley Z.; Jiang, Xikai; Lequieu, Joshua; Li, Jiyuan; Moller, Joshua; Quevillon, Michael J.; Rahimi, Mohammad; Ramezani-Dakhel, Hadi; Rathee, Vikramjit S.; Reid, Daniel R.; Sevgen, Emre; Thapar, Vikram; Webb, Michael A.; Whitmer, Jonathan K.; de Pablo, Juan J.

    2018-01-01

    Molecular simulation has emerged as an essential tool for modern-day research, but obtaining proper results and making reliable conclusions from simulations requires adequate sampling of the system under consideration. To this end, a variety of methods exist in the literature that can enhance sampling considerably, and increasingly sophisticated, effective algorithms continue to be developed at a rapid pace. Implementation of these techniques, however, can be challenging for experts and non-experts alike. There is a clear need for software that provides rapid, reliable, and easy access to a wide range of advanced sampling methods and that facilitates implementation of new techniques as they emerge. Here we present SSAGES, a publicly available Software Suite for Advanced General Ensemble Simulations designed to interface with multiple widely used molecular dynamics simulations packages. SSAGES allows facile application of a variety of enhanced sampling techniques—including adaptive biasing force, string methods, and forward flux sampling—that extract meaningful free energy and transition path data from all-atom and coarse-grained simulations. A noteworthy feature of SSAGES is a user-friendly framework that facilitates further development and implementation of new methods and collective variables. In this work, the use of SSAGES is illustrated in the context of simple representative applications involving distinct methods and different collective variables that are available in the current release of the suite. The code may be found at: https://github.com/MICCoM/SSAGES-public.

  2. STS-93 Pilot Ashby suits up before launch

    1999-01-01

    In the Operations and Checkout Building during final launch preparations for the second time, STS-93 Pilot Jeffrey S. Ashby waves after donning his launch and entry suit while a suit tech adjusts his boot. After Space Shuttle Columbia's July 20 launch attempt was scrubbed at the T-7 second mark in the countdown, the launch was rescheduled for Thursday, July 22, at 12:28 a.m. EDT. The target landing date is July 26, 1999, at 11:24 p.m. EDT. STS- 93 is a five-day mission primarily to release the Chandra X-ray Observatory, which will allow scientists from around the world to study some of the most distant, powerful and dynamic objects in the universe. The new telescope is 20 to 50 times more sensitive than any previous X-ray telescope and is expected unlock the secrets of supernovae, quasars and black holes. The STS-93 crew numbers five: Commander Eileen M. Collins, Ashby, and Mission Specialists Stephen A. Hawley (Ph.D.), Catherine G. Coleman (Ph.D.) and Michel Tognini of France, with the Centre National d'Etudes Spatiales (CNES). Collins is the first woman to serve as commander of a shuttle mission.

  3. STS-93 M.S. Hawley suits up for launch

    1999-01-01

    During final launch preparations in the Operations and Checkout Building, STS-93 Mission Specialist Steven A. Hawley (Ph.D.)gets help donning his launch and entry suit from a suit tech. After Space Shuttle Columbia's July 20 launch attempt was scrubbed at the T-7 second mark in the countdown, the launch was rescheduled for Thursday, July 22, at 12:28 a.m. EDT. The target landing date is July 26, 1999, at 11:24 p.m. EDT. STS-93 is a five-day mission primarily to release the Chandra X-ray Observatory, which will allow scientists from around the world to study some of the most distant, powerful and dynamic objects in the universe. The new telescope is 20 to 50 times more sensitive than any previous X- ray telescope and is expected unlock the secrets of supernovae, quasars and black holes. The STS-93 crew numbers five: Commander Eileen M. Collins, Pilot Jeffrey S. Ashby, and Mission Specialists Hawley, Catherine G. Coleman (Ph.D.) and Michel Tognini of France, with the Centre National d'Etudes Spatiales (CNES). Collins is the first woman to serve as commander of a shuttle mission.

  4. SSAGES: Software Suite for Advanced General Ensemble Simulations

    Sidky, Hythem [Department of Chemical and Biomolecular Engineering, University of Notre Dame, Notre Dame, Indiana 46556, USA; Colón, Yamil J. [Institute for Molecular Engineering, University of Chicago, Chicago, Illinois 60637, USA; Institute for Molecular Engineering and Materials Science Division, Argonne National Laboratory, Lemont, Illinois 60439, USA; Helfferich, Julian [Institute for Molecular Engineering, University of Chicago, Chicago, Illinois 60637, USA; Steinbuch Center for Computing, Karlsruhe Institute of Technology, Hermann-von-Helmholtz-Platz 1, 76344 Eggenstein-Leopoldshafen, Germany; Sikora, Benjamin J. [Department of Chemical and Biomolecular Engineering, University of Notre Dame, Notre Dame, Indiana 46556, USA; Bezik, Cody [Institute for Molecular Engineering, University of Chicago, Chicago, Illinois 60637, USA; Chu, Weiwei [Institute for Molecular Engineering, University of Chicago, Chicago, Illinois 60637, USA; Giberti, Federico [Institute for Molecular Engineering, University of Chicago, Chicago, Illinois 60637, USA; Guo, Ashley Z. [Institute for Molecular Engineering, University of Chicago, Chicago, Illinois 60637, USA; Jiang, Xikai [Institute for Molecular Engineering, University of Chicago, Chicago, Illinois 60637, USA; Lequieu, Joshua [Institute for Molecular Engineering, University of Chicago, Chicago, Illinois 60637, USA; Li, Jiyuan [Institute for Molecular Engineering, University of Chicago, Chicago, Illinois 60637, USA; Moller, Joshua [Institute for Molecular Engineering, University of Chicago, Chicago, Illinois 60637, USA; Quevillon, Michael J. [Department of Chemical and Biomolecular Engineering, University of Notre Dame, Notre Dame, Indiana 46556, USA; Rahimi, Mohammad [Institute for Molecular Engineering, University of Chicago, Chicago, Illinois 60637, USA; Ramezani-Dakhel, Hadi [Institute for Molecular Engineering, University of Chicago, Chicago, Illinois 60637, USA; Department of Biochemistry and Molecular Biology, University of Chicago, Chicago, Illinois 60637, USA; Rathee, Vikramjit S. [Department of Chemical and Biomolecular Engineering, University of Notre Dame, Notre Dame, Indiana 46556, USA; Reid, Daniel R. [Institute for Molecular Engineering, University of Chicago, Chicago, Illinois 60637, USA; Sevgen, Emre [Institute for Molecular Engineering, University of Chicago, Chicago, Illinois 60637, USA; Thapar, Vikram [Institute for Molecular Engineering, University of Chicago, Chicago, Illinois 60637, USA; Webb, Michael A. [Institute for Molecular Engineering, University of Chicago, Chicago, Illinois 60637, USA; Institute for Molecular Engineering and Materials Science Division, Argonne National Laboratory, Lemont, Illinois 60439, USA; Whitmer, Jonathan K. [Department of Chemical and Biomolecular Engineering, University of Notre Dame, Notre Dame, Indiana 46556, USA; de Pablo, Juan J. [Institute for Molecular Engineering, University of Chicago, Chicago, Illinois 60637, USA; Institute for Molecular Engineering and Materials Science Division, Argonne National Laboratory, Lemont, Illinois 60439, USA

    2018-01-28

    Molecular simulation has emerged as an essential tool for modern-day research, but obtaining proper results and making reliable conclusions from simulations requires adequate sampling of the system under consideration. To this end, a variety of methods exist in the literature that can enhance sampling considerably, and increasingly sophisticated, effective algorithms continue to be developed at a rapid pace. Implementation of these techniques, however, can be challenging for experts and non-experts alike. There is a clear need for software that provides rapid, reliable, and easy access to a wide range of advanced sampling methods, and that facilitates implementation of new techniques as they emerge. Here we present SSAGES, a publicly available Software Suite for Advanced General Ensemble Simulations designed to interface with multiple widely used molecular dynamics simulations packages. SSAGES allows facile application of a variety of enhanced sampling techniques—including adaptive biasing force, string methods, and forward flux sampling—that extract meaningful free energy and transition path data from all-atom and coarse grained simulations. A noteworthy feature of SSAGES is a user-friendly framework that facilitates further development and implementation of new methods and collective variables. In this work, the use of SSAGES is illustrated in the context of simple representative applications involving distinct methods and different collective variables that are available in the current release of the suite.

  5. Tier-3 Monitoring Software Suite (T3MON) proposal

    Andreeva, J; The ATLAS collaboration; Klimentov, A; Korenkov, V; Oleynik, D; Panitkin, S; Petrosyan, A

    2011-01-01

    The ATLAS Distributed Computing activities concentrated so far in the “central” part of the computing system of the experiment, namely the first 3 tiers (CERN Tier0, the 10 Tier1s centres and the 60+ Tier2s). This is a coherent system to perform data processing and management on a global scale and host (re)processing, simulation activities down to group and user analysis. Many ATLAS Institutes and National Communities built (or have plans to build) Tier-3 facilities. The definition of Tier-3 concept has been outlined (REFERENCE). Tier-3 centres consist of non-pledged resources mostly dedicated for the data analysis by the geographically close or local scientific groups. Tier-3 sites comprise a range of architectures and many do not possess Grid middleware, which would render application of Tier-2 monitoring systems useless. This document describes a strategy to develop a software suite for monitoring of the Tier3 sites. This software suite will enable local monitoring of the Tier3 sites and the global vie...

  6. Wireless hydrotherapy smart suit for monitoring handicapped people

    Correia, Jose H.; Mendes, Paulo M.

    2005-02-01

    This paper presents a smart suit, water impermeable, containing sensors and electronics for monitoring handicapped people at hydrotherapy sessions in swimming-pools. For integration into textiles, electronic components should be designed in a functional, robust and inexpensive way. Therefore, small-size electronics microsystems are a promising approach. The smart suit allows the monitoring of individual biometric data, such as heart rate, temperature and movement of the body. Two solutions for transmitting the data wirelessly are presented: through a low-voltage (3.0 V), low-power, CMOS RF IC (1.6 mm x 1.5 mm size dimensions) operating at 433 MHz, with ASK modulation and a patch antenna built on lossy substrates compatible with integrated circuits fabrication. Two different substrates were used for antenna implementation: high-resistivity silicon (HRS) and Corning Pyrex #7740 glass. The antenna prototypes were built to operate close to the 5 GHz ISM band. They operate at a center frequency of 5.705 GHz (HRS) and 5.995 GHz (Pyrex). The studied parameters were: substrate thickness, substrate losses, oxide thickness, metal conductivity and thickness. The antenna on HRS uses an area of 8 mm2, providing a 90 MHz bandwidth and ~0.3 dBi of gain. On a glass substrate, the antenna uses 12 mm2, provides 100 MHz bandwidth and ~3 dBi of gain.

  7. RNA Structural Alignments, Part I

    Havgaard, Jakob Hull; Gorodkin, Jan

    2014-01-01

    Simultaneous alignment and secondary structure prediction of RNA sequences is often referred to as "RNA structural alignment." A class of the methods for structural alignment is based on the principles proposed by Sankoff more than 25 years ago. The Sankoff algorithm simultaneously folds and aligns...... is so high that it took more than a decade before the first implementation of a Sankoff style algorithm was published. However, with the faster computers available today and the improved heuristics used in the implementations the Sankoff-based methods have become practical. This chapter describes...... the methods based on the Sankoff algorithm. All the practical implementations of the algorithm use heuristics to make them run in reasonable time and memory. These heuristics are also described in this chapter....

  8. A conceptual precipitation-runoff modeling suite: Model selection, calibration and predictive uncertainty assessment

    Tyler Jon Smith

    2008-01-01

    In Montana and much of the Rocky Mountain West, the single most important parameter in forecasting the controls on regional water resources is snowpack. Despite the heightened importance of snowpack, few studies have considered the representation of uncertainty in coupled snowmelt/hydrologic conceptual models. Uncertainty estimation provides a direct interpretation of...

  9. On Predicting the Leeway and Drift of A Survival Suit Clad Person In-Water

    1997-10-01

    1977; Morgan 1978, Scobie and Thompson, 1979; Osmer, Edwards, and Breitler, 1982; and Nash and Willcox, 1985) on drifting objects. Leeway is defined...34, Woods Hole Oceanographic Institution, 26 PP. Scobie , R.W., and D.L. Thompson, 1979. "Life Raft Study", U.S. Coast Guard, Oceanographic Unit Technical

  10. Modeling the Impact of Space Suit Components and Anthropometry on the Center of Mass of a Seated Crewmember

    Rajulu, Sudhakar; Blackledge, Christopher; Ferrer, Mike; Margerum, Sarah

    2009-01-01

    The designers of the Orion Crew Exploration Vehicle (CEV) utilize an intensive simulation program in order to predict the launch and landing characteristics of the Crew Impact Attenuation System (CIAS). The CIAS is the energy absorbing strut concept that dampens loads to levels sustainable by the crew during landing and consists of the crew module seat pallet that accommodates four to six seated astronauts. An important parameter required for proper dynamic modeling of the CIAS is knowledge of the suited center of mass (COM) variations within the crew population. Significant center of mass variations across suited crew configurations would amplify the inertial effects of the pallet and potentially create unacceptable crew loading during launch and landing. Established suited, whole-body, and posture-based mass properties were not available due to the uncertainty of the final CEV seat posture and suit hardware configurations. While unsuited segmental center of mass values can be obtained via regression equations from previous studies, building them into a model that was posture dependent with custom anthropometry and integrated suit components proved cumbersome and time consuming. Therefore, the objective of this study was to quantify the effects of posture, suit components, and the expected range of anthropometry on the center of mass of a seated individual. Several elements are required for the COM calculation of a suited human in a seated position: anthropometry; body segment mass; suit component mass; suit component location relative to the body; and joint angles defining the seated posture. Anthropometry and body segment masses used in this study were taken from a selection of three-dimensional human body models, called boundary manikins, which were developed in a previous project. These boundary manikins represent the critical anthropometric dimension extremes for the anticipated astronaut population. Six male manikins and 6 female manikins, representing a

  11. A comparison of two Shuttle launch and entry suits - Reach envelope, isokinetic strength, and treadmill tests

    Schafer, Lauren E.; Rajulu, Sudhakar L.; Klute, Glenn K.

    1992-01-01

    A quantification has been conducted of any existing differences between the performance, in operational conditions, of the Space Shuttle crew Launch Entry Suit (LES) and the new Advanced Crew Escape Suit (ACES). While LES is a partial-pressure suit, the ACES system which is being considered as a replacement for LES is a full-pressure suit. Three tests have been conducted with six subjects to ascertain the suits' reach envelope, strength, and treadmill performance. No significant operational differences were found between the two suit designs.

  12. Structural imprints in vivo decode RNA regulatory mechanisms.

    Spitale, Robert C; Flynn, Ryan A; Zhang, Qiangfeng Cliff; Crisalli, Pete; Lee, Byron; Jung, Jong-Wha; Kuchelmeister, Hannes Y; Batista, Pedro J; Torre, Eduardo A; Kool, Eric T; Chang, Howard Y

    2015-03-26

    Visualizing the physical basis for molecular behaviour inside living cells is a great challenge for biology. RNAs are central to biological regulation, and the ability of RNA to adopt specific structures intimately controls every step of the gene expression program. However, our understanding of physiological RNA structures is limited; current in vivo RNA structure profiles include only two of the four nucleotides that make up RNA. Here we present a novel biochemical approach, in vivo click selective 2'-hydroxyl acylation and profiling experiment (icSHAPE), which enables the first global view, to our knowledge, of RNA secondary structures in living cells for all four bases. icSHAPE of the mouse embryonic stem cell transcriptome versus purified RNA folded in vitro shows that the structural dynamics of RNA in the cellular environment distinguish different classes of RNAs and regulatory elements. Structural signatures at translational start sites and ribosome pause sites are conserved from in vitro conditions, suggesting that these RNA elements are programmed by sequence. In contrast, focal structural rearrangements in vivo reveal precise interfaces of RNA with RNA-binding proteins or RNA-modification sites that are consistent with atomic-resolution structural data. Such dynamic structural footprints enable accurate prediction of RNA-protein interactions and N(6)-methyladenosine (m(6)A) modification genome wide. These results open the door for structural genomics of RNA in living cells and reveal key physiological structures controlling gene expression.

  13. Enhanced Verification Test Suite for Physics Simulation Codes

    Kamm, J R; Brock, J S; Brandon, S T; Cotrell, D L; Johnson, B; Knupp, P; Rider, W; Trucano, T; Weirs, V G

    2008-10-10

    This document discusses problems with which to augment, in quantity and in quality, the existing tri-laboratory suite of verification problems used by Los Alamos National Laboratory (LANL), Lawrence Livermore National Laboratory (LLNL), and Sandia National Laboratories (SNL). The purpose of verification analysis is demonstrate whether the numerical results of the discretization algorithms in physics and engineering simulation codes provide correct solutions of the corresponding continuum equations. The key points of this document are: (1) Verification deals with mathematical correctness of the numerical algorithms in a code, while validation deals with physical correctness of a simulation in a regime of interest. This document is about verification. (2) The current seven-problem Tri-Laboratory Verification Test Suite, which has been used for approximately five years at the DOE WP laboratories, is limited. (3) Both the methodology for and technology used in verification analysis have evolved and been improved since the original test suite was proposed. (4) The proposed test problems are in three basic areas: (a) Hydrodynamics; (b) Transport processes; and (c) Dynamic strength-of-materials. (5) For several of the proposed problems we provide a 'strong sense verification benchmark', consisting of (i) a clear mathematical statement of the problem with sufficient information to run a computer simulation, (ii) an explanation of how the code result and benchmark solution are to be evaluated, and (iii) a description of the acceptance criterion for simulation code results. (6) It is proposed that the set of verification test problems with which any particular code be evaluated include some of the problems described in this document. Analysis of the proposed verification test problems constitutes part of a necessary--but not sufficient--step that builds confidence in physics and engineering simulation codes. More complicated test cases, including physics models of

  14. RNA decay by messenger RNA interferases

    Christensen-Dalsgaard, Mikkel; Overgaard, Martin; Winther, Kristoffer Skovbo

    2008-01-01

    Two abundant toxin-antitoxin (TA) gene families, relBE and mazEF, encode mRNA cleaving enzymes whose ectopic overexpression abruptly inhibits translation and thereby induces a bacteriostatic condition. Here we describe and discuss protocols for the overproduction, purification, and analysis of mR...... cleaving enzymes such as RelE of Escherichia coli and the corresponding antitoxin RelB. In particular, we describe a set of plasmid vectors useful for the detailed analysis of cleavage sites in model mRNAs.......Two abundant toxin-antitoxin (TA) gene families, relBE and mazEF, encode mRNA cleaving enzymes whose ectopic overexpression abruptly inhibits translation and thereby induces a bacteriostatic condition. Here we describe and discuss protocols for the overproduction, purification, and analysis of mRNA...

  15. Modeling Coronal Mass Ejections with the Multi-Scale Fluid-Kinetic Simulation Suite

    Pogorelov, N. V.; Borovikov, S. N.; Wu, S. T.; Yalim, M. S.; Kryukov, I. A.; Colella, P. C.; Van Straalen, B.

    2017-01-01

    The solar eruptions and interacting solar wind streams are key drivers of geomagnetic storms and various related space weather disturbances that may have hazardous effects on the space-borne and ground-based technological systems as well as on human health. Coronal mass ejections (CMEs) and their interplanetary counterparts, interplanetary CMEs (ICMEs), belong to the strongest disturbances and therefore are of great importance for the space weather predictions. In this paper we show a few examples of how adaptive mesh refinement makes it possible to resolve the complex CME structure and its evolution in time while a CME propagates from the inner boundary to Earth. Simulations are performed with the Multi-Scale Fluid-Kinetic Simulation Suite (MS-FLUKSS). (paper)

  16. REDItools: high-throughput RNA editing detection made easy.

    Picardi, Ernesto; Pesole, Graziano

    2013-07-15

    The reliable detection of RNA editing sites from massive sequencing data remains challenging and, although several methodologies have been proposed, no computational tools have been released to date. Here, we introduce REDItools a suite of python scripts to perform high-throughput investigation of RNA editing using next-generation sequencing data. REDItools are in python programming language and freely available at http://code.google.com/p/reditools/. ernesto.picardi@uniba.it or graziano.pesole@uniba.it Supplementary data are available at Bioinformatics online.

  17. A suite of standards for radiation monitors and their revisions

    Noda, Kimio

    1991-01-01

    A suite of standards for radiation monitors applied in nuclear facilities in Japan was compiled mainly by Health Physicists in Power Reactor and Nuclear Fuel Development (PNC) and Japan Atomic Energy Research Institute (JAERI), and issued in 1971 as 'The Standard for Radiation Monitors'. PNC facilities such as Reprocessing Plant and Plutonium Fuel Fabrication Facility, as well as other nuclear industries have applied the standard, and contributed improvement of practical maintenability and availability of the radiation monitors. Meanwhile, the radiation monitors have remarkably progressed in its application and size of the monitors is growing. Furthermore, manufacturing techniques have significantly progressed especially in the field of system concepts and electronics elements. These progresses require revision of the standards. 'The Standard for Radiation Monitors' has been revised considering the problems in practical application and data processing capability. Considerations are given to keep compatibility of old and new modules. (author)

  18. User Guide for the STAYSL PNNL Suite of Software Tools

    Greenwood, Lawrence R.; Johnson, Christian D.

    2013-02-27

    The STAYSL PNNL software suite provides a set of tools for working with neutron activation rates measured in a nuclear fission reactor, an accelerator-based neutron source, or any neutron field to determine the neutron flux spectrum through a generalized least-squares approach. This process is referred to as neutron spectral adjustment since the preferred approach is to use measured data to adjust neutron spectra provided by neutron physics calculations. The input data consist of the reaction rates based on measured activities, an initial estimate of the neutron flux spectrum, neutron activation cross sections and their associated uncertainties (covariances), and relevant correction factors. The output consists of the adjusted neutron flux spectrum and associated covariance matrix, which is useful for neutron dosimetry and radiation damage calculations.

  19. Court rules against failed viatical firm in investor suit.

    1999-10-01

    A Federal appeals court has revived a claim against Dignity Partners Inc., a viatical business, and offshoot of a financial-services firm. Dignity Partners operated by buying the life insurance policies of terminally ill people. The company was charged with making false and misleading statements in its prospectus for an initial public stock offering. Five months later, the company announced that it would not accept new customers with AIDS, a group which represented 95 percent of its accounts at that time. The company had information from researchers and clinicians that the introduction of protease inhibitors would greatly increase life expectancy for its customers and would reduce company profits. This information was not generally available to potential investors. The suit against the company alleges violations of the Securities Act of 1933 and the Exchange Act of 1934, both which govern stock trading.

  20. STS-93 Commander Collins suits up for launch

    1999-01-01

    During the third launch preparations in the Operations and Checkout Building, STS-93 Commander Eileen M. Collins waves while having her launch and entry suit checked. After Space Shuttle Columbia's July 20 and 22 launch attempts were scrubbed, the launch was again rescheduled for Friday, July 23, at 12:24 a.m. EDT. STS-93 is a five-day mission primarily to release the Chandra X-ray Observatory, which will allow scientists from around the world to study some of the most distant, powerful and dynamic objects in the universe. The STS-93 crew numbers five: Commander Collins, Pilot Jeffrey S. Ashby, and Mission Specialists Stephen A. Hawley (Ph.D.), Catherine G. Coleman (Ph.D.) and Michel Tognini of France, with the Centre National d'Etudes Spatiales (CNES). Collins is the first woman to serve as commander of a shuttle mission.