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Sample records for secondary structure prediction

  1. Nucleic acid secondary structure prediction and display.

    OpenAIRE

    Stüber, K

    1986-01-01

    A set of programs has been developed for the prediction and display of nucleic acid secondary structures. Information from experimental data can be used to restrict or enforce secondary structural elements. The predictions can be displayed either on normal line printers or on graphic devices like plotters or graphic terminals.

  2. Protein secondary structure: category assignment and predictability

    DEFF Research Database (Denmark)

    Andersen, Claus A.; Bohr, Henrik; Brunak, Søren

    2001-01-01

    In the last decade, the prediction of protein secondary structure has been optimized using essentially one and the same assignment scheme known as DSSP. We present here a different scheme, which is more predictable. This scheme predicts directly the hydrogen bonds, which stabilize the secondary......-forward neural network with one hidden layer on a data set identical to the one used in earlier work....

  3. A Kernel for Protein Secondary Structure Prediction

    OpenAIRE

    Guermeur , Yann; Lifchitz , Alain; Vert , Régis

    2004-01-01

    http://mitpress.mit.edu/catalog/item/default.asp?ttype=2&tid=10338&mode=toc; International audience; Multi-class support vector machines have already proved efficient in protein secondary structure prediction as ensemble methods, to combine the outputs of sets of classifiers based on different principles. In this chapter, their implementation as basic prediction methods, processing the primary structure or the profile of multiple alignments, is investigated. A kernel devoted to the task is in...

  4. RNA secondary structure prediction using soft computing.

    Science.gov (United States)

    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.

  5. Predicting Protein Secondary Structure with Markov Models

    DEFF Research Database (Denmark)

    Fischer, Paul; Larsen, Simon; Thomsen, Claus

    2004-01-01

    we are considering here, is to predict the secondary structure from the primary one. To this end we train a Markov model on training data and then use it to classify parts of unknown protein sequences as sheets, helices or coils. We show how to exploit the directional information contained...... in the Markov model for this task. Classifications that are purely based on statistical models might not always be biologically meaningful. We present combinatorial methods to incorporate biological background knowledge to enhance the prediction performance....

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

    Science.gov (United States)

    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.

  7. Prediction of the Secondary Structure of HIV-1 gp120

    DEFF Research Database (Denmark)

    Hansen, Jan; Lund, Ole; Nielsen, Jens O.

    1996-01-01

    Fourier transform infrared spectroscopy. The predicted secondary structure of gp120 compared well with data from NMR analysis of synthetic peptides from the V3 loop and the C4 region. As a first step towards modeling the tertiary structure of gp120, the predicted secondary structure may guide the design......The secondary structure of HIV-1 gp120 was predicted using multiple alignment and a combination of two independent methods based on neural network and nearest-neighbor algorithms. The methods agreed on the secondary structure for 80% of the residues in BH10 gp120. Six helices were predicted in HIV...

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

    Science.gov (United States)

    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.

  9. Ensemble-based prediction of RNA secondary structures.

    Science.gov (United States)

    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

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

    Science.gov (United States)

    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/.

  11. Combining neural networks for protein secondary structure prediction

    DEFF Research Database (Denmark)

    Riis, Søren Kamaric

    1995-01-01

    In this paper structured neural networks are applied to the problem of predicting the secondary structure of proteins. A hierarchical approach is used where specialized neural networks are designed for each structural class and then combined using another neural network. The submodels are designed...... by using a priori knowledge of the mapping between protein building blocks and the secondary structure and by using weight sharing. Since none of the individual networks have more than 600 adjustable weights over-fitting is avoided. When ensembles of specialized experts are combined the performance...

  12. Cascaded bidirectional recurrent neural networks for protein secondary structure prediction.

    Science.gov (United States)

    Chen, Jinmiao; Chaudhari, Narendra

    2007-01-01

    Protein secondary structure (PSS) prediction is an important topic in bioinformatics. Our study on a large set of non-homologous proteins shows that long-range interactions commonly exist and negatively affect PSS prediction. Besides, we also reveal strong correlations between secondary structure (SS) elements. In order to take into account the long-range interactions and SS-SS correlations, we propose a novel prediction system based on cascaded bidirectional recurrent neural network (BRNN). We compare the cascaded BRNN against another two BRNN architectures, namely the original BRNN architecture used for speech recognition as well as Pollastri's BRNN that was proposed for PSS prediction. Our cascaded BRNN achieves an overall three state accuracy Q3 of 74.38\\%, and reaches a high Segment OVerlap (SOV) of 66.0455. It outperforms the original BRNN and Pollastri's BRNN in both Q3 and SOV. Specifically, it improves the SOV score by 4-6%.

  13. Evolutionary rate variation and RNA secondary structure prediction

    DEFF Research Database (Denmark)

    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...

  14. Parallel protein secondary structure prediction based on neural networks.

    Science.gov (United States)

    Zhong, Wei; Altun, Gulsah; Tian, Xinmin; Harrison, Robert; Tai, Phang C; Pan, Yi

    2004-01-01

    Protein secondary structure prediction has a fundamental influence on today's bioinformatics research. In this work, binary and tertiary classifiers of protein secondary structure prediction are implemented on Denoeux belief neural network (DBNN) architecture. Hydrophobicity matrix, orthogonal matrix, BLOSUM62 and PSSM (position specific scoring matrix) are experimented separately as the encoding schemes for DBNN. The experimental results contribute to the design of new encoding schemes. New binary classifier for Helix versus not Helix ( approximately H) for DBNN produces prediction accuracy of 87% when PSSM is used for the input profile. The performance of DBNN binary classifier is comparable to other best prediction methods. The good test results for binary classifiers open a new approach for protein structure prediction with neural networks. Due to the time consuming task of training the neural networks, Pthread and OpenMP are employed to parallelize DBNN in the hyperthreading enabled Intel architecture. Speedup for 16 Pthreads is 4.9 and speedup for 16 OpenMP threads is 4 in the 4 processors shared memory architecture. Both speedup performance of OpenMP and Pthread is superior to that of other research. With the new parallel training algorithm, thousands of amino acids can be processed in reasonable amount of time. Our research also shows that hyperthreading technology for Intel architecture is efficient for parallel biological algorithms.

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

    Directory of Open Access Journals (Sweden)

    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.

  16. PCI-SS: MISO dynamic nonlinear protein secondary structure prediction

    Directory of Open Access Journals (Sweden)

    Aboul-Magd Mohammed O

    2009-07-01

    Full Text Available Abstract Background Since the function of a protein is largely dictated by its three dimensional configuration, determining a protein's structure is of fundamental importance to biology. Here we report on a novel approach to determining the one dimensional secondary structure of proteins (distinguishing α-helices, β-strands, and non-regular structures from primary sequence data which makes use of Parallel Cascade Identification (PCI, a powerful technique from the field of nonlinear system identification. Results Using PSI-BLAST divergent evolutionary profiles as input data, dynamic nonlinear systems are built through a black-box approach to model the process of protein folding. Genetic algorithms (GAs are applied in order to optimize the architectural parameters of the PCI models. The three-state prediction problem is broken down into a combination of three binary sub-problems and protein structure classifiers are built using 2 layers of PCI classifiers. Careful construction of the optimization, training, and test datasets ensures that no homology exists between any training and testing data. A detailed comparison between PCI and 9 contemporary methods is provided over a set of 125 new protein chains guaranteed to be dissimilar to all training data. Unlike other secondary structure prediction methods, here a web service is developed to provide both human- and machine-readable interfaces to PCI-based protein secondary structure prediction. This server, called PCI-SS, is available at http://bioinf.sce.carleton.ca/PCISS. In addition to a dynamic PHP-generated web interface for humans, a Simple Object Access Protocol (SOAP interface is added to permit invocation of the PCI-SS service remotely. This machine-readable interface facilitates incorporation of PCI-SS into multi-faceted systems biology analysis pipelines requiring protein secondary structure information, and greatly simplifies high-throughput analyses. XML is used to represent the input

  17. Protein 8-class secondary structure prediction using conditional neural fields.

    Science.gov (United States)

    Wang, Zhiyong; Zhao, Feng; Peng, Jian; Xu, Jinbo

    2011-10-01

    Compared with the protein 3-class secondary structure (SS) prediction, the 8-class prediction gains less attention and is also much more challenging, especially for proteins with few sequence homologs. This paper presents a new probabilistic method for 8-class SS prediction using conditional neural fields (CNFs), a recently invented probabilistic graphical model. This CNF method not only models the complex relationship between sequence features and SS, but also exploits the interdependency among SS types of adjacent residues. In addition to sequence profiles, our method also makes use of non-evolutionary information for SS prediction. Tested on the CB513 and RS126 data sets, our method achieves Q8 accuracy of 64.9 and 64.7%, respectively, which are much better than the SSpro8 web server (51.0 and 48.0%, respectively). Our method can also be used to predict other structure properties (e.g. solvent accessibility) of a protein or the SS of RNA. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  18. Protein Secondary Structure Prediction Using Deep Convolutional Neural Fields.

    Science.gov (United States)

    Wang, Sheng; Peng, Jian; Ma, Jianzhu; Xu, Jinbo

    2016-01-11

    Protein secondary structure (SS) prediction is important for studying protein structure and function. When only the sequence (profile) information is used as input feature, currently the best predictors can obtain ~80% Q3 accuracy, which has not been improved in the past decade. Here we present DeepCNF (Deep Convolutional Neural Fields) for protein SS prediction. DeepCNF is a Deep Learning extension of Conditional Neural Fields (CNF), which is an integration of Conditional Random Fields (CRF) and shallow neural networks. DeepCNF can model not only complex sequence-structure relationship by a deep hierarchical architecture, but also interdependency between adjacent SS labels, so it is much more powerful than CNF. Experimental results show that DeepCNF can obtain ~84% Q3 accuracy, ~85% SOV score, and ~72% Q8 accuracy, respectively, on the CASP and CAMEO test proteins, greatly outperforming currently popular predictors. As a general framework, DeepCNF can be used to predict other protein structure properties such as contact number, disorder regions, and solvent accessibility.

  19. Viral IRES prediction system - a web server for prediction of the IRES secondary structure in silico.

    Directory of Open Access Journals (Sweden)

    Jun-Jie Hong

    Full Text Available The internal ribosomal entry site (IRES functions as cap-independent translation initiation sites in eukaryotic cells. IRES elements have been applied as useful tools for bi-cistronic expression vectors. Current RNA structure prediction programs are unable to predict precisely the potential IRES element. We have designed a viral IRES prediction system (VIPS to perform the IRES secondary structure prediction. In order to obtain better results for the IRES prediction, the VIPS can evaluate and predict for all four different groups of IRESs with a higher accuracy. RNA secondary structure prediction, comparison, and pseudoknot prediction programs were implemented to form the three-stage procedure for the VIPS. The backbone of VIPS includes: the RNAL fold program, aimed to predict local RNA secondary structures by minimum free energy method; the RNA Align program, intended to compare predicted structures; and pknotsRG program, used to calculate the pseudoknot structure. VIPS was evaluated by using UTR database, IRES database and Virus database, and the accuracy rate of VIPS was assessed as 98.53%, 90.80%, 82.36% and 80.41% for IRES groups 1, 2, 3, and 4, respectively. This advance useful search approach for IRES structures will facilitate IRES related studies. The VIPS on-line website service is available at http://140.135.61.250/vips/.

  20. Improving the accuracy of protein secondary structure prediction using structural alignment

    Directory of Open Access Journals (Sweden)

    Gallin Warren J

    2006-06-01

    Full Text Available Abstract Background The accuracy of protein secondary structure prediction has steadily improved over the past 30 years. Now many secondary structure prediction methods routinely achieve an accuracy (Q3 of about 75%. We believe this accuracy could be further improved by including structure (as opposed to sequence database comparisons as part of the prediction process. Indeed, given the large size of the Protein Data Bank (>35,000 sequences, the probability of a newly identified sequence having a structural homologue is actually quite high. Results We have developed a method that performs structure-based sequence alignments as part of the secondary structure prediction process. By mapping the structure of a known homologue (sequence ID >25% onto the query protein's sequence, it is possible to predict at least a portion of that query protein's secondary structure. By integrating this structural alignment approach with conventional (sequence-based secondary structure methods and then combining it with a "jury-of-experts" system to generate a consensus result, it is possible to attain very high prediction accuracy. Using a sequence-unique test set of 1644 proteins from EVA, this new method achieves an average Q3 score of 81.3%. Extensive testing indicates this is approximately 4–5% better than any other method currently available. Assessments using non sequence-unique test sets (typical of those used in proteome annotation or structural genomics indicate that this new method can achieve a Q3 score approaching 88%. Conclusion By using both sequence and structure databases and by exploiting the latest techniques in machine learning it is possible to routinely predict protein secondary structure with an accuracy well above 80%. A program and web server, called PROTEUS, that performs these secondary structure predictions is accessible at http://wishart.biology.ualberta.ca/proteus. For high throughput or batch sequence analyses, the PROTEUS programs

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

    Science.gov (United States)

    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…

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

    Science.gov (United States)

    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.

  3. Predicting beta-turns and their types using predicted backbone dihedral angles and secondary structures.

    Science.gov (United States)

    Kountouris, Petros; Hirst, Jonathan D

    2010-07-31

    Beta-turns are secondary structure elements usually classified as coil. Their prediction is important, because of their role in protein folding and their frequent occurrence in protein chains. We have developed a novel method that predicts beta-turns and their types using information from multiple sequence alignments, predicted secondary structures and, for the first time, predicted dihedral angles. Our method uses support vector machines, a supervised classification technique, and is trained and tested on three established datasets of 426, 547 and 823 protein chains. We achieve a Matthews correlation coefficient of up to 0.49, when predicting the location of beta-turns, the highest reported value to date. Moreover, the additional dihedral information improves the prediction of beta-turn types I, II, IV, VIII and "non-specific", achieving correlation coefficients up to 0.39, 0.33, 0.27, 0.14 and 0.38, respectively. Our results are more accurate than other methods. We have created an accurate predictor of beta-turns and their types. Our method, called DEBT, is available online at http://comp.chem.nottingham.ac.uk/debt/.

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

    DEFF Research Database (Denmark)

    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...

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

    Science.gov (United States)

    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.

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

    Science.gov (United States)

    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.

  7. Prediction of backbone dihedral angles and protein secondary structure using support vector machines

    Directory of Open Access Journals (Sweden)

    Hirst Jonathan D

    2009-12-01

    Full Text Available Abstract Background The prediction of the secondary structure of a protein is a critical step in the prediction of its tertiary structure and, potentially, its function. Moreover, the backbone dihedral angles, highly correlated with secondary structures, provide crucial information about the local three-dimensional structure. Results We predict independently both the secondary structure and the backbone dihedral angles and combine the results in a loop to enhance each prediction reciprocally. Support vector machines, a state-of-the-art supervised classification technique, achieve secondary structure predictive accuracy of 80% on a non-redundant set of 513 proteins, significantly higher than other methods on the same dataset. The dihedral angle space is divided into a number of regions using two unsupervised clustering techniques in order to predict the region in which a new residue belongs. The performance of our method is comparable to, and in some cases more accurate than, other multi-class dihedral prediction methods. Conclusions We have created an accurate predictor of backbone dihedral angles and secondary structure. Our method, called DISSPred, is available online at http://comp.chem.nottingham.ac.uk/disspred/.

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

    Science.gov (United States)

    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.

  9. Protein Secondary Structure Prediction Using AutoEncoder Network and Bayes Classifier

    Science.gov (United States)

    Wang, Leilei; Cheng, Jinyong

    2018-03-01

    Protein secondary structure prediction is belong to bioinformatics,and it's important in research area. In this paper, we propose a new prediction way of protein using bayes classifier and autoEncoder network. Our experiments show some algorithms including the construction of the model, the classification of parameters and so on. The data set is a typical CB513 data set for protein. In terms of accuracy, the method is the cross validation based on the 3-fold. Then we can get the Q3 accuracy. Paper results illustrate that the autoencoder network improved the prediction accuracy of protein secondary structure.

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

    OpenAIRE

    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...

  11. Prediction of beta-turns at over 80% accuracy based on an ensemble of predicted secondary structures and multiple alignments.

    Science.gov (United States)

    Zheng, Ce; Kurgan, Lukasz

    2008-10-10

    beta-turn is a secondary protein structure type that plays significant role in protein folding, stability, and molecular recognition. To date, several methods for prediction of beta-turns from protein sequences were developed, but they are characterized by relatively poor prediction quality. The novelty of the proposed sequence-based beta-turn predictor stems from the usage of a window based information extracted from four predicted three-state secondary structures, which together with a selected set of position specific scoring matrix (PSSM) values serve as an input to the support vector machine (SVM) predictor. We show that (1) all four predicted secondary structures are useful; (2) the most useful information extracted from the predicted secondary structure includes the structure of the predicted residue, secondary structure content in a window around the predicted residue, and features that indicate whether the predicted residue is inside a secondary structure segment; (3) the PSSM values of Asn, Asp, Gly, Ile, Leu, Met, Pro, and Val were among the top ranked features, which corroborates with recent studies. The Asn, Asp, Gly, and Pro indicate potential beta-turns, while the remaining four amino acids are useful to predict non-beta-turns. Empirical evaluation using three nonredundant datasets shows favorable Q total, Q predicted and MCC values when compared with over a dozen of modern competing methods. Our method is the first to break the 80% Q total barrier and achieves Q total = 80.9%, MCC = 0.47, and Q predicted higher by over 6% when compared with the second best method. We use feature selection to reduce the dimensionality of the feature vector used as the input for the proposed prediction method. The applied feature set is smaller by 86, 62 and 37% when compared with the second and two third-best (with respect to MCC) competing methods, respectively. Experiments show that the proposed method constitutes an improvement over the competing prediction

  12. Artificial Intelligence in Prediction of Secondary Protein Structure Using CB513 Database

    Science.gov (United States)

    Avdagic, Zikrija; Purisevic, Elvir; Omanovic, Samir; Coralic, Zlatan

    2009-01-01

    In this paper we describe CB513 a non-redundant dataset, suitable for development of algorithms for prediction of secondary protein structure. A program was made in Borland Delphi for transforming data from our dataset to make it suitable for learning of neural network for prediction of secondary protein structure implemented in MATLAB Neural-Network Toolbox. Learning (training and testing) of neural network is researched with different sizes of windows, different number of neurons in the hidden layer and different number of training epochs, while using dataset CB513. PMID:21347158

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

    Science.gov (United States)

    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.

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

    Science.gov (United States)

    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

  15. Prediction of beta-turns at over 80% accuracy based on an ensemble of predicted secondary structures and multiple alignments

    Directory of Open Access Journals (Sweden)

    Kurgan Lukasz

    2008-10-01

    Full Text Available Abstract Background β-turn is a secondary protein structure type that plays significant role in protein folding, stability, and molecular recognition. To date, several methods for prediction of β-turns from protein sequences were developed, but they are characterized by relatively poor prediction quality. The novelty of the proposed sequence-based β-turn predictor stems from the usage of a window based information extracted from four predicted three-state secondary structures, which together with a selected set of position specific scoring matrix (PSSM values serve as an input to the support vector machine (SVM predictor. Results We show that (1 all four predicted secondary structures are useful; (2 the most useful information extracted from the predicted secondary structure includes the structure of the predicted residue, secondary structure content in a window around the predicted residue, and features that indicate whether the predicted residue is inside a secondary structure segment; (3 the PSSM values of Asn, Asp, Gly, Ile, Leu, Met, Pro, and Val were among the top ranked features, which corroborates with recent studies. The Asn, Asp, Gly, and Pro indicate potential β-turns, while the remaining four amino acids are useful to predict non-β-turns. Empirical evaluation using three nonredundant datasets shows favorable Qtotal, Qpredicted and MCC values when compared with over a dozen of modern competing methods. Our method is the first to break the 80% Qtotal barrier and achieves Qtotal = 80.9%, MCC = 0.47, and Qpredicted higher by over 6% when compared with the second best method. We use feature selection to reduce the dimensionality of the feature vector used as the input for the proposed prediction method. The applied feature set is smaller by 86, 62 and 37% when compared with the second and two third-best (with respect to MCC competing methods, respectively. Conclusion Experiments show that the proposed method constitutes an

  16. Tchebichef image moment approach to the prediction of protein secondary structures based on circular dichroism.

    Science.gov (United States)

    Li, Sha Sha; Li, Bao Qiong; Liu, Jin Jin; Lu, Shao Hua; Zhai, Hong Lin

    2018-04-20

    Circular dichroism (CD) spectroscopy is a widely used technique for the evaluation of protein secondary structures that has a significant impact for the understanding of molecular biology. However, the quantitative analysis of protein secondary structures based on CD spectra is still a hard work due to the serious overlap of the spectra corresponding to different structural motifs. Here, Tchebichef image moment (TM) approach is introduced for the first time, which can effectively extract the chemical features in CD spectra for the quantitative analysis of protein secondary structures. The proposed approach was applied to analyze reference set. and the obtained results were evaluated by the strict statistical parameters such as correlation coefficient, cross-validation correlation coefficient and root mean squared error. Compared with several specialized prediction methods, TM approach provided satisfactory results, especially for turns and unordered structures. Our study indicates that TM approach can be regarded as a feasible tool for the analysis of the secondary structures of proteins based on CD spectra. An available TMs package is provided and can be used directly for secondary structures prediction. This article is protected by copyright. All rights reserved. © 2018 Wiley Periodicals, Inc.

  17. Bayesian Inference using Neural Net Likelihood Models for Protein Secondary Structure Prediction

    Directory of Open Access Journals (Sweden)

    Seong-Gon Kim

    2011-06-01

    Full Text Available Several techniques such as Neural Networks, Genetic Algorithms, Decision Trees and other statistical or heuristic methods have been used to approach the complex non-linear task of predicting Alpha-helicies, Beta-sheets and Turns of a proteins secondary structure in the past. This project introduces a new machine learning method by using an offline trained Multilayered Perceptrons (MLP as the likelihood models within a Bayesian Inference framework to predict secondary structures proteins. Varying window sizes are used to extract neighboring amino acid information and passed back and forth between the Neural Net models and the Bayesian Inference process until there is a convergence of the posterior secondary structure probability.

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

    Science.gov (United States)

    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

  19. SAAS: Short Amino Acid Sequence - A Promising Protein Secondary Structure Prediction Method of Single Sequence

    Directory of Open Access Journals (Sweden)

    Zhou Yuan Wu

    2013-07-01

    Full Text Available In statistical methods of predicting protein secondary structure, many researchers focus on single amino acid frequencies in α-helices, β-sheets, and so on, or the impact near amino acids on an amino acid forming a secondary structure. But the paper considers a short sequence of amino acids (3, 4, 5 or 6 amino acids as integer, and statistics short sequence's probability forming secondary structure. Also, many researchers select low homologous sequences as statistical database. But this paper select whole PDB database. In this paper we propose a strategy to predict protein secondary structure using simple statistical method. Numerical computation shows that, short amino acids sequence as integer to statistics, which can easy see trend of short sequence forming secondary structure, and it will work well to select large statistical database (whole PDB database without considering homologous, and Q3 accuracy is ca. 74% using this paper proposed simple statistical method, but accuracy of others statistical methods is less than 70%.

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

    Science.gov (United States)

    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 .

  1. Exploiting the Past and the Future in Protein Secondary Structure Prediction

    DEFF Research Database (Denmark)

    Baldi, Pierre; Brunak, Søren; Frasconi, P

    1999-01-01

    predictions based on variable ranges of dependencies. These architectures extend recurrent neural networks, introducing non-causal bidirectional dynamics to capture both upstream and downstream information. The prediction algorithm is completed by the use of mixtures of estimators that leverage evolutionary......Motivation: Predicting the secondary structure of a protein (alpha-helix, beta-sheet, coil) is an important step towards elucidating its three-dimensional structure, as well as its function. Presently, the best predictors are based on machine learning approaches, in particular neural network...

  2. Knowledge base and neural network approach for protein secondary structure prediction.

    Science.gov (United States)

    Patel, Maulika S; Mazumdar, Himanshu S

    2014-11-21

    Protein structure prediction is of great relevance given the abundant genomic and proteomic data generated by the genome sequencing projects. Protein secondary structure prediction is addressed as a sub task in determining the protein tertiary structure and function. In this paper, a novel algorithm, KB-PROSSP-NN, which is a combination of knowledge base and modeling of the exceptions in the knowledge base using neural networks for protein secondary structure prediction (PSSP), is proposed. The knowledge base is derived from a proteomic sequence-structure database and consists of the statistics of association between the 5-residue words and corresponding secondary structure. The predicted results obtained using knowledge base are refined with a Backpropogation neural network algorithm. Neural net models the exceptions of the knowledge base. The Q3 accuracy of 90% and 82% is achieved on the RS126 and CB396 test sets respectively which suggest improvement over existing state of art methods. Copyright © 2014 Elsevier Ltd. All rights reserved.

  3. SVM-PB-Pred: SVM based protein block prediction method using sequence profiles and secondary structures.

    Science.gov (United States)

    Suresh, V; Parthasarathy, S

    2014-01-01

    We developed a support vector machine based web server called SVM-PB-Pred, to predict the Protein Block for any given amino acid sequence. The input features of SVM-PB-Pred include i) sequence profiles (PSSM) and ii) actual secondary structures (SS) from DSSP method or predicted secondary structures from NPS@ and GOR4 methods. There were three combined input features PSSM+SS(DSSP), PSSM+SS(NPS@) and PSSM+SS(GOR4) used to test and train the SVM models. Similarly, four datasets RS90, DB433, LI1264 and SP1577 were used to develop the SVM models. These four SVM models developed were tested using three different benchmarking tests namely; (i) self consistency, (ii) seven fold cross validation test and (iii) independent case test. The maximum possible prediction accuracy of ~70% was observed in self consistency test for the SVM models of both LI1264 and SP1577 datasets, where PSSM+SS(DSSP) input features was used to test. The prediction accuracies were reduced to ~53% for PSSM+SS(NPS@) and ~43% for PSSM+SS(GOR4) in independent case test, for the SVM models of above two same datasets. Using our method, it is possible to predict the protein block letters for any query protein sequence with ~53% accuracy, when the SP1577 dataset and predicted secondary structure from NPS@ server were used. The SVM-PB-Pred server can be freely accessed through http://bioinfo.bdu.ac.in/~svmpbpred.

  4. MUFOLD-SS: New deep inception-inside-inception networks for protein secondary structure prediction.

    Science.gov (United States)

    Fang, Chao; Shang, Yi; Xu, Dong

    2018-05-01

    Protein secondary structure prediction can provide important information for protein 3D structure prediction and protein functions. Deep learning offers a new opportunity to significantly improve prediction accuracy. In this article, a new deep neural network architecture, named the Deep inception-inside-inception (Deep3I) network, is proposed for protein secondary structure prediction and implemented as a software tool MUFOLD-SS. The input to MUFOLD-SS is a carefully designed feature matrix corresponding to the primary amino acid sequence of a protein, which consists of a rich set of information derived from individual amino acid, as well as the context of the protein sequence. Specifically, the feature matrix is a composition of physio-chemical properties of amino acids, PSI-BLAST profile, and HHBlits profile. MUFOLD-SS is composed of a sequence of nested inception modules and maps the input matrix to either eight states or three states of secondary structures. The architecture of MUFOLD-SS enables effective processing of local and global interactions between amino acids in making accurate prediction. In extensive experiments on multiple datasets, MUFOLD-SS outperformed the best existing methods and other deep neural networks significantly. MUFold-SS can be downloaded from http://dslsrv8.cs.missouri.edu/~cf797/MUFoldSS/download.html. © 2018 Wiley Periodicals, Inc.

  5. Protein secondary structure prediction using modular reciprocal bidirectional recurrent neural networks.

    Science.gov (United States)

    Babaei, Sepideh; Geranmayeh, Amir; Seyyedsalehi, Seyyed Ali

    2010-12-01

    The supervised learning of recurrent neural networks well-suited for prediction of protein secondary structures from the underlying amino acids sequence is studied. Modular reciprocal recurrent neural networks (MRR-NN) are proposed to model the strong correlations between adjacent secondary structure elements. Besides, a multilayer bidirectional recurrent neural network (MBR-NN) is introduced to capture the long-range intramolecular interactions between amino acids in formation of the secondary structure. The final modular prediction system is devised based on the interactive integration of the MRR-NN and the MBR-NN structures to arbitrarily engage the neighboring effects of the secondary structure types concurrent with memorizing the sequential dependencies of amino acids along the protein chain. The advanced combined network augments the percentage accuracy (Q₃) to 79.36% and boosts the segment overlap (SOV) up to 70.09% when tested on the PSIPRED dataset in three-fold cross-validation. Copyright © 2010 Elsevier Ireland Ltd. All rights reserved.

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

    Science.gov (United States)

    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

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

    Science.gov (United States)

    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.

  8. Protein secondary structure prediction for a single-sequence using hidden semi-Markov models

    Directory of Open Access Journals (Sweden)

    Borodovsky Mark

    2006-03-01

    Full Text Available Abstract Background The accuracy of protein secondary structure prediction has been improving steadily towards the 88% estimated theoretical limit. There are two types of prediction algorithms: Single-sequence prediction algorithms imply that information about other (homologous proteins is not available, while algorithms of the second type imply that information about homologous proteins is available, and use it intensively. The single-sequence algorithms could make an important contribution to studies of proteins with no detected homologs, however the accuracy of protein secondary structure prediction from a single-sequence is not as high as when the additional evolutionary information is present. Results In this paper, we further refine and extend the hidden semi-Markov model (HSMM initially considered in the BSPSS algorithm. We introduce an improved residue dependency model by considering the patterns of statistically significant amino acid correlation at structural segment borders. We also derive models that specialize on different sections of the dependency structure and incorporate them into HSMM. In addition, we implement an iterative training method to refine estimates of HSMM parameters. The three-state-per-residue accuracy and other accuracy measures of the new method, IPSSP, are shown to be comparable or better than ones for BSPSS as well as for PSIPRED, tested under the single-sequence condition. Conclusions We have shown that new dependency models and training methods bring further improvements to single-sequence protein secondary structure prediction. The results are obtained under cross-validation conditions using a dataset with no pair of sequences having significant sequence similarity. As new sequences are added to the database it is possible to augment the dependency structure and obtain even higher accuracy. Current and future advances should contribute to the improvement of function prediction for orphan proteins inscrutable

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

    Science.gov (United States)

    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

  10. RDNAnalyzer: A tool for DNA secondary structure prediction and sequence analysis.

    Science.gov (United States)

    Afzal, Muhammad; Shahid, Ahmad Ali; Shehzadi, Abida; Nadeem, Shahid; Husnain, Tayyab

    2012-01-01

    RDNAnalyzer is an innovative computer based tool designed for DNA secondary structure prediction and sequence analysis. It can randomly generate the DNA sequence or user can upload the sequences of their own interest in RAW format. It uses and extends the Nussinov dynamic programming algorithm and has various application for the sequence analysis. It predicts the DNA secondary structure and base pairings. It also provides the tools for routinely performed sequence analysis by the biological scientists such as DNA replication, reverse compliment generation, transcription, translation, sequence specific information as total number of nucleotide bases, ATGC base contents along with their respective percentages and sequence cleaner. RDNAnalyzer is a unique tool developed in Microsoft Visual Studio 2008 using Microsoft Visual C# and Windows Presentation Foundation and provides user friendly environment for sequence analysis. It is freely available. http://www.cemb.edu.pk/sw.html RDNAnalyzer - Random DNA Analyser, GUI - Graphical user interface, XAML - Extensible Application Markup Language.

  11. CNNH_PSS: protein 8-class secondary structure prediction by convolutional neural network with highway.

    Science.gov (United States)

    Zhou, Jiyun; Wang, Hongpeng; Zhao, Zhishan; Xu, Ruifeng; Lu, Qin

    2018-05-08

    Protein secondary structure is the three dimensional form of local segments of proteins and its prediction is an important problem in protein tertiary structure prediction. Developing computational approaches for protein secondary structure prediction is becoming increasingly urgent. We present a novel deep learning based model, referred to as CNNH_PSS, by using multi-scale CNN with highway. In CNNH_PSS, any two neighbor convolutional layers have a highway to deliver information from current layer to the output of the next one to keep local contexts. As lower layers extract local context while higher layers extract long-range interdependencies, the highways between neighbor layers allow CNNH_PSS to have ability to extract both local contexts and long-range interdependencies. We evaluate CNNH_PSS on two commonly used datasets: CB6133 and CB513. CNNH_PSS outperforms the multi-scale CNN without highway by at least 0.010 Q8 accuracy and also performs better than CNF, DeepCNF and SSpro8, which cannot extract long-range interdependencies, by at least 0.020 Q8 accuracy, demonstrating that both local contexts and long-range interdependencies are indeed useful for prediction. Furthermore, CNNH_PSS also performs better than GSM and DCRNN which need extra complex model to extract long-range interdependencies. It demonstrates that CNNH_PSS not only cost less computer resource, but also achieves better predicting performance. CNNH_PSS have ability to extracts both local contexts and long-range interdependencies by combing multi-scale CNN and highway network. The evaluations on common datasets and comparisons with state-of-the-art methods indicate that CNNH_PSS is an useful and efficient tool for protein secondary structure prediction.

  12. A systematic review on popularity, application and characteristics of protein secondary structure prediction tools.

    Science.gov (United States)

    Kashani-Amin, Elaheh; Tabatabaei-Malazy, Ozra; Sakhteman, Amirhossein; Larijani, Bagher; Ebrahim-Habibi, Azadeh

    2018-02-27

    Prediction of proteins' secondary structure is one of the major steps in the generation of homology models. These models provide structural information which is used to design suitable ligands for potential medicinal targets. However, selecting a proper tool between multiple secondary structure prediction (SSP) options is challenging. The current study is an insight onto currently favored methods and tools, within various contexts. A systematic review was performed for a comprehensive access to recent (2013-2016) studies which used or recommended protein SSP tools. Three databases, Web of Science, PubMed and Scopus were systematically searched and 99 out of 209 studies were finally found eligible to extract data. Four categories of applications for 59 retrieved SSP tools were: (I) prediction of structural features of a given sequence, (II) evaluation of a method, (III) providing input for a new SSP method and (IV) integrating a SSP tool as a component for a program. PSIPRED was found to be the most popular tool in all four categories. JPred and tools utilizing PHD (Profile network from HeiDelberg) method occupied second and third places of popularity in categories I and II. JPred was only found in the two first categories, while PHD was present in three fields. This study provides a comprehensive insight about the recent usage of SSP tools which could be helpful for selecting a proper tool's choice. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

  13. A Deep Learning Network Approach to ab initio Protein Secondary Structure Prediction.

    Science.gov (United States)

    Spencer, Matt; Eickholt, Jesse; Jianlin Cheng

    2015-01-01

    Ab initio protein secondary structure (SS) predictions are utilized to generate tertiary structure predictions, which are increasingly demanded due to the rapid discovery of proteins. Although recent developments have slightly exceeded previous methods of SS prediction, accuracy has stagnated around 80 percent and many wonder if prediction cannot be advanced beyond this ceiling. Disciplines that have traditionally employed neural networks are experimenting with novel deep learning techniques in attempts to stimulate progress. Since neural networks have historically played an important role in SS prediction, we wanted to determine whether deep learning could contribute to the advancement of this field as well. We developed an SS predictor that makes use of the position-specific scoring matrix generated by PSI-BLAST and deep learning network architectures, which we call DNSS. Graphical processing units and CUDA software optimize the deep network architecture and efficiently train the deep networks. Optimal parameters for the training process were determined, and a workflow comprising three separately trained deep networks was constructed in order to make refined predictions. This deep learning network approach was used to predict SS for a fully independent test dataset of 198 proteins, achieving a Q3 accuracy of 80.7 percent and a Sov accuracy of 74.2 percent.

  14. Predicting protein folding pathways at the mesoscopic level based on native interactions between secondary structure elements

    Directory of Open Access Journals (Sweden)

    Sze Sing-Hoi

    2008-07-01

    Full Text Available Abstract Background Since experimental determination of protein folding pathways remains difficult, computational techniques are often used to simulate protein folding. Most current techniques to predict protein folding pathways are computationally intensive and are suitable only for small proteins. Results By assuming that the native structure of a protein is known and representing each intermediate conformation as a collection of fully folded structures in which each of them contains a set of interacting secondary structure elements, we show that it is possible to significantly reduce the conformation space while still being able to predict the most energetically favorable folding pathway of large proteins with hundreds of residues at the mesoscopic level, including the pig muscle phosphoglycerate kinase with 416 residues. The model is detailed enough to distinguish between different folding pathways of structurally very similar proteins, including the streptococcal protein G and the peptostreptococcal protein L. The model is also able to recognize the differences between the folding pathways of protein G and its two structurally similar variants NuG1 and NuG2, which are even harder to distinguish. We show that this strategy can produce accurate predictions on many other proteins with experimentally determined intermediate folding states. Conclusion Our technique is efficient enough to predict folding pathways for both large and small proteins at the mesoscopic level. Such a strategy is often the only feasible choice for large proteins. A software program implementing this strategy (SSFold is available at http://faculty.cs.tamu.edu/shsze/ssfold.

  15. Secondary Structure Prediction of Protein using Resilient Back Propagation Learning Algorithm

    Directory of Open Access Journals (Sweden)

    Jyotshna Dongardive

    2015-12-01

    Full Text Available The paper proposes a neural network based approach to predict secondary structure of protein. It uses Multilayer Feed Forward Network (MLFN with resilient back propagation as the learning algorithm. Point Accepted Mutation (PAM is adopted as the encoding scheme and CB396 data set is used for the training and testing of the network. Overall accuracy of the network has been experimentally calculated with different window sizes for the sliding window scheme and by varying the number of units in the hidden layer. The best results were obtained with eleven as the window size and seven as the number of units in the hidden layer.

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

    International Nuclear Information System (INIS)

    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

  17. A search for H/ACA snoRNAs in yeast using MFE secondary structure prediction.

    Science.gov (United States)

    Edvardsson, Sverker; Gardner, Paul P; Poole, Anthony M; Hendy, Michael D; Penny, David; Moulton, Vincent

    2003-05-01

    Noncoding RNA genes produce functional RNA molecules rather than coding for proteins. One such family is the H/ACA snoRNAs. Unlike the related C/D snoRNAs these have resisted automated detection to date. We develop an algorithm to screen the yeast genome for novel H/ACA snoRNAs. To achieve this, we introduce some new methods for facilitating the search for noncoding RNAs in genomic sequences which are based on properties of predicted minimum free-energy (MFE) secondary structures. The algorithm has been implemented and can be generalized to enable screening of other eukaryote genomes. We find that use of primary sequence alone is insufficient for identifying novel H/ACA snoRNAs. Only the use of secondary structure filters reduces the number of candidates to a manageable size. From genomic context, we identify three strong H/ACA snoRNA candidates. These together with a further 47 candidates obtained by our analysis are being experimentally screened.

  18. Combining sequence-based prediction methods and circular dichroism and infrared spectroscopic data to improve protein secondary structure determinations

    Directory of Open Access Journals (Sweden)

    Lees Jonathan G

    2008-01-01

    Full Text Available Abstract Background A number of sequence-based methods exist for protein secondary structure prediction. Protein secondary structures can also be determined experimentally from circular dichroism, and infrared spectroscopic data using empirical analysis methods. It has been proposed that comparable accuracy can be obtained from sequence-based predictions as from these biophysical measurements. Here we have examined the secondary structure determination accuracies of sequence prediction methods with the empirically determined values from the spectroscopic data on datasets of proteins for which both crystal structures and spectroscopic data are available. Results In this study we show that the sequence prediction methods have accuracies nearly comparable to those of spectroscopic methods. However, we also demonstrate that combining the spectroscopic and sequences techniques produces significant overall improvements in secondary structure determinations. In addition, combining the extra information content available from synchrotron radiation circular dichroism data with sequence methods also shows improvements. Conclusion Combining sequence prediction with experimentally determined spectroscopic methods for protein secondary structure content significantly enhances the accuracy of the overall results obtained.

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

    Directory of Open Access Journals (Sweden)

    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

  20. Prediction of guide strand of microRNAs from its sequence and secondary structure

    Directory of Open Access Journals (Sweden)

    Ahmed Firoz

    2009-04-01

    Full Text Available Abstract Background MicroRNAs (miRNAs are produced by the sequential processing of a long hairpin RNA transcript by Drosha and Dicer, an RNase III enzymes, and form transitory small RNA duplexes. One strand of the duplex, which incorporates into RNA-induced silencing complex (RISC and silences the gene expression is called guide strand, or miRNA; while the other strand of duplex is degraded and called the passenger strand, or miRNA*. Predicting the guide strand of miRNA is important for better understanding the RNA interference pathways. Results This paper describes support vector machine (SVM models developed for predicting the guide strands of miRNAs. All models were trained and tested on a dataset consisting of 329 miRNA and 329 miRNA* pairs using five fold cross validation technique. Firstly, models were developed using mono-, di-, and tri-nucleotide composition of miRNA strands and achieved the highest accuracies of 0.588, 0.638 and 0.596 respectively. Secondly, models were developed using split nucleotide composition and achieved maximum accuracies of 0.553, 0.641 and 0.602 for mono-, di-, and tri-nucleotide respectively. Thirdly, models were developed using binary pattern and achieved the highest accuracy of 0.708. Furthermore, when integrating the secondary structure features with binary pattern, an accuracy of 0.719 was seen. Finally, hybrid models were developed by combining various features and achieved maximum accuracy of 0.799 with sensitivity 0.781 and specificity 0.818. Moreover, the performance of this model was tested on an independent dataset that achieved an accuracy of 0.80. In addition, we also compared the performance of our method with various siRNA-designing methods on miRNA and siRNA datasets. Conclusion In this study, first time a method has been developed to predict guide miRNA strands, of miRNA duplex. This study demonstrates that guide and passenger strand of miRNA precursors can be distinguished using their

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

    Science.gov (United States)

    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.

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

    Directory of Open Access Journals (Sweden)

    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.

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

    Czech Academy of Sciences Publication Activity Database

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

    Science.gov (United States)

    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.

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

    Directory of Open Access Journals (Sweden)

    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.

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

    Directory of Open Access Journals (Sweden)

    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.

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

    DEFF Research Database (Denmark)

    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...

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

    DEFF Research Database (Denmark)

    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...

  9. Correlation of MFOLD-predicted DNA secondary structures with separation patterns obtained by capillary electrophoresis single-strand conformation polymorphism (CE-SSCP) analysis.

    Science.gov (United States)

    Glavac, Damjan; Potocnik, Uros; Podpecnik, Darja; Zizek, Teofil; Smerkolj, Sava; Ravnik-Glavac, Metka

    2002-04-01

    We have studied 57 different mutations within three beta-globin gene promoter fragments with sizes 52 bp, 77 bp, and 193 bp by fluorescent capillary electrophoresis CE-SSCP analysis. For each mutation and wild type, energetically most-favorable predicted secondary structures were calculated for sense and antisense strands using the MFOLD DNA-folding algorithm in order to investigate if any correlation exists between predicted DNA structures and actual CE migration time shifts. The overall CE-SSCP detection rate was 100% for all mutations in three studied DNA fragments. For shorter 52 bp and 77 bp DNA fragments we obtained a positive correlation between the migration time shifts and difference in free energy values of predicted secondary structures at all temperatures. For longer 193 bp beta-globin gene fragments with 46 mutations MFOLD predicted different secondary structures for 89% of mutated strands at 25 degrees C and 40 degrees C. However, the magnitude of the mobility shifts did not necessarily correlate with their secondary structures and free energy values except for the sense strand at 40 degrees C where this correlation was statistically significant (r = 0.312, p = 0.033). Results of this study provided more direct insight into the mechanism of CE-SSCP and showed that MFOLD prediction could be helpful in making decisions about the running temperatures and in prediction of CE-SSCP data patterns, especially for shorter (50-100 bp) DNA fragments. Copyright 2002 Wiley-Liss, Inc.

  10. Implications of secondary structure prediction and amino acid sequence comparison of class I and class II phosphoribosyl diphosphate synthases on catalysis, regulation, and quaternary structure

    DEFF Research Database (Denmark)

    Krath, B N; Hove-Jensen, B

    2001-01-01

    Spinach 5-phospho-D-ribosyl alpha-1-diphosphate (PRPP) synthase isozyme 4 was synthesized in Escherichia coli and purified to near homogeneity. The activity of the enzyme is independent of P(i); it is inhibited by ADP in a competitive manner, indicating a lack of an allosteric site; and it accepts...... is consistent with a homotrimer. Secondary structure prediction shows that spinach PRPP synthase isozyme 4 has a general folding similar to that of Bacillus subtilis class I PRPP synthase, for which the three-dimensional structure has been solved, as the position and extent of helices and beta-sheets of the two...... in the spinach enzyme. In contrast, residues of the active site of B. subtilis PRPP synthase show extensive conservation in spinach PRPP synthase isozyme 4....

  11. A novel Multi-Agent Ada-Boost algorithm for predicting protein structural class with the information of protein secondary structure.

    Science.gov (United States)

    Fan, Ming; Zheng, Bin; Li, Lihua

    2015-10-01

    Knowledge of the structural class of a given protein is important for understanding its folding patterns. Although a lot of efforts have been made, it still remains a challenging problem for prediction of protein structural class solely from protein sequences. The feature extraction and classification of proteins are the main problems in prediction. In this research, we extended our earlier work regarding these two aspects. In protein feature extraction, we proposed a scheme by calculating the word frequency and word position from sequences of amino acid, reduced amino acid, and secondary structure. For an accurate classification of the structural class of protein, we developed a novel Multi-Agent Ada-Boost (MA-Ada) method by integrating the features of Multi-Agent system into Ada-Boost algorithm. Extensive experiments were taken to test and compare the proposed method using four benchmark datasets in low homology. The results showed classification accuracies of 88.5%, 96.0%, 88.4%, and 85.5%, respectively, which are much better compared with the existing methods. The source code and dataset are available on request.

  12. Detection of non-coding RNAs on the basis of predicted secondary structure formation free energy change

    Directory of Open Access Journals (Sweden)

    Uzilov Andrew V

    2006-03-01

    Full Text Available Abstract Background Non-coding RNAs (ncRNAs have a multitude of roles in the cell, many of which remain to be discovered. However, it is difficult to detect novel ncRNAs in biochemical screens. To advance biological knowledge, computational methods that can accurately detect ncRNAs in sequenced genomes are therefore desirable. The increasing number of genomic sequences provides a rich dataset for computational comparative sequence analysis and detection of novel ncRNAs. Results Here, Dynalign, a program for predicting secondary structures common to two RNA sequences on the basis of minimizing folding free energy change, is utilized as a computational ncRNA detection tool. The Dynalign-computed optimal total free energy change, which scores the structural alignment and the free energy change of folding into a common structure for two RNA sequences, is shown to be an effective measure for distinguishing ncRNA from randomized sequences. To make the classification as a ncRNA, the total free energy change of an input sequence pair can either be compared with the total free energy changes of a set of control sequence pairs, or be used in combination with sequence length and nucleotide frequencies as input to a classification support vector machine. The latter method is much faster, but slightly less sensitive at a given specificity. Additionally, the classification support vector machine method is shown to be sensitive and specific on genomic ncRNA screens of two different Escherichia coli and Salmonella typhi genome alignments, in which many ncRNAs are known. The Dynalign computational experiments are also compared with two other ncRNA detection programs, RNAz and QRNA. Conclusion The Dynalign-based support vector machine method is more sensitive for known ncRNAs in the test genomic screens than RNAz and QRNA. Additionally, both Dynalign-based methods are more sensitive than RNAz and QRNA at low sequence pair identities. Dynalign can be used as a

  13. IRSS: a web-based tool for automatic layout and analysis of IRES secondary structure prediction and searching system in silico

    Directory of Open Access Journals (Sweden)

    Hong Jun-Jie

    2009-05-01

    Full Text Available Abstract Background Internal ribosomal entry sites (IRESs provide alternative, cap-independent translation initiation sites in eukaryotic cells. IRES elements are important factors in viral genomes and are also useful tools for bi-cistronic expression vectors. Most existing RNA structure prediction programs are unable to deal with IRES elements. Results We designed an IRES search system, named IRSS, to obtain better results for IRES prediction. RNA secondary structure prediction and comparison software programs were implemented to construct our two-stage strategy for the IRSS. Two software programs formed the backbone of IRSS: the RNAL fold program, used to predict local RNA secondary structures by minimum free energy method; and the RNA Align program, used to compare predicted structures. After complete viral genome database search, the IRSS have low error rate and up to 72.3% sensitivity in appropriated parameters. Conclusion IRSS is freely available at this website http://140.135.61.9/ires/. In addition, all source codes, precompiled binaries, examples and documentations are downloadable for local execution. This new search approach for IRES elements will provide a useful research tool on IRES related studies.

  14. An efficient method for the prediction of deleterious multiple-point mutations in the secondary structure of RNAs using suboptimal folding solutions

    Directory of Open Access Journals (Sweden)

    Barash Danny

    2008-04-01

    Full Text Available Abstract Background RNAmute is an interactive Java application which, given an RNA sequence, calculates the secondary structure of all single point mutations and organizes them into categories according to their similarity to the predicted structure of the wild type. The secondary structure predictions are performed using the Vienna RNA package. A more efficient implementation of RNAmute is needed, however, to extend from the case of single point mutations to the general case of multiple point mutations, which may often be desired for computational predictions alongside mutagenesis experiments. But analyzing multiple point mutations, a process that requires traversing all possible mutations, becomes highly expensive since the running time is O(nm for a sequence of length n with m-point mutations. Using Vienna's RNAsubopt, we present a method that selects only those mutations, based on stability considerations, which are likely to be conformational rearranging. The approach is best examined using the dot plot representation for RNA secondary structure. Results Using RNAsubopt, the suboptimal solutions for a given wild-type sequence are calculated once. Then, specific mutations are selected that are most likely to cause a conformational rearrangement. For an RNA sequence of about 100 nts and 3-point mutations (n = 100, m = 3, for example, the proposed method reduces the running time from several hours or even days to several minutes, thus enabling the practical application of RNAmute to the analysis of multiple-point mutations. Conclusion A highly efficient addition to RNAmute that is as user friendly as the original application but that facilitates the practical analysis of multiple-point mutations is presented. Such an extension can now be exploited prior to site-directed mutagenesis experiments by virologists, for example, who investigate the change of function in an RNA virus via mutations that disrupt important motifs in its secondary

  15. Life prediction of simple structures subject to cyclic primary and secondary loading resulting in creep and platicity

    International Nuclear Information System (INIS)

    Otter, N.R.; Jones, R.T.

    1979-01-01

    High temperature reactors are subject to cyclic mechanical and thermal loadings resulting from start up and shut down operations. The design must therefore guard against structural failure resulting from excessive deformation and creep-fatigue damage. Before any simplified inelastic analysis techniques can be applied, their validity needs to be examined under situations representative of the reactor. For this to be carried out it is necessary to determine the behaviour of components, initially geometrically simple, subject to loadings, cyclic primary and secondary in nature, which result in creep and plasticity. Beam-like structures have been investigated on a finite element basis with the aim of determining how cyclic plasticity, creep enhancement and plastic ratchetting vary in relationship with modified shakedown criteria, magnitude of loading and hold time. (orig.)

  16. A folding algorithm for extended RNA secondary structures.

    Science.gov (United States)

    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/.

  17. Prediction of the secondary structure of the mitochondrial tRNASer (UCN) of Lutzomyia hartmanni (Diptera: Psychodidae)

    International Nuclear Information System (INIS)

    Perez Doria, Alveiro; Bejarano, Eduar E

    2011-01-01

    Lutzomyia (Helcocyrtomyia) hartmanni is a sand fly that has been implicated in the transmission of Leishmania (Viannia) colombiensis, an etiologic agent of cutaneous Leishmaniasis in Colombia. The objective of this work was to explore the potential usefulness of the mitochondrial serine transfer RNA (UCN) (tRNASer) in the taxonomic determination of L. hartmanni. Mitochondrial DNA was extracted, amplified and sequenced from entomological material collected in Envigado, Antioquia, Colombia. The tRNASer gene length was 68 nucleotide pairs, with an average adenine-thymine content of 80.9%. The studied tRNASer differs from other sand fly tRNASer known to date, on the basis of its primary and secondary structure. The observed number of intrachain base pairing was 7 in the acceptor arm, 3 in the dihydrouridine (DHU) arm, 5 in the anticodon arm, and 5 in the ribothymidine-pseudouridine-cytosine (TC) arm. The size of the DHU, anticodon, variable and TC loops was estimated to be 5, 7, 4, and 8 nucleotides, respectively. The notorious absence of non-Watson-Crick base pairs in the four arms of the tRNASer distinguishes that of L. hartmanni from others Lutzomyia spp.

  18. Models for predicting turnover of residential aged care nurses: a structural equation modelling analysis of secondary data.

    Science.gov (United States)

    Gao, Fengsong; Newcombe, Peter; Tilse, Cheryl; Wilson, Jill; Tuckett, Anthony

    2014-09-01

    Nurse turnover in the residential aged care industry is a pressing issue. Researchers have shown ongoing interest in exploring how the factors that are amendable to change in aged care policy, regulation and funding and in organizational procedures (e.g. job demands, coping resources and psychological health of nurses) impact on turnover. However, the findings are mixed. This study tested two theoretical models of turnover to examine the structural relationships among job demands, coping resources, psychological health and turnover of residential aged care nurses. Although many previous studies operationalized turnover as intention to leave, the present study investigated actual turnover by following up with the same individuals over time, and thus provided more accurate predictive models of turnover behaviour. The sample, 239 Australian residential aged care nurses, came from the Nurses and Midwives e-cohort Study. Job demands, coping resources, and psychological health were measured using standardized instruments. Structural equation modelling was used to test the measurement and structural models. Controlling for a number of workforce and individual characteristics, coping resources (measured by job control, supervisor support, and co-worker support) were negatively and directly associated with turnover. Additionally, the findings supported the Job Demand-Control-Support model in that higher coping resources and lower job demands (indicated by psychological demands, physical demands, and effort) were related to better psychological health (measured by vitality, social functioning, role emotional, and mental health), and higher job demands were related to lower coping resources. Findings suggest that aged care policy makers and service providers might consider increasing coping resources available to nurses and minimizing job demands of care work to reduce turnover and improve nurses' psychological health. Moreover, findings from this Australian study may provide

  19. Neural Networks for protein Structure Prediction

    DEFF Research Database (Denmark)

    Bohr, Henrik

    1998-01-01

    This is a review about neural network applications in bioinformatics. Especially the applications to protein structure prediction, e.g. prediction of secondary structures, prediction of surface structure, fold class recognition and prediction of the 3-dimensional structure of protein backbones...

  20. On the prediction of turbulent secondary flows

    Science.gov (United States)

    Speziale, C. G.; So, R. M. C.; Younis, B. A.

    1992-01-01

    The prediction of turbulent secondary flows, with Reynolds stress models, in circular pipes and non-circular ducts is reviewed. Turbulence-driven secondary flows in straight non-circular ducts are considered along with turbulent secondary flows in pipes and ducts that arise from curvature or a system rotation. The physical mechanisms that generate these different kinds of secondary flows are outlined and the level of turbulence closure required to properly compute each type is discussed in detail. Illustrative computations of a variety of different secondary flows obtained from two-equation turbulence models and second-order closures are provided to amplify these points.

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

    Science.gov (United States)

    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

  2. Development of methods to predict both the dynamic and the pseudo-static response of secondary structures subjected to seismic excitations

    International Nuclear Information System (INIS)

    Subudhi, M.; Bezler, P.

    1984-01-01

    Multiple independent support excitation time history formulations have been used to investigate simplified methods to predict the inertial (or dynamic) component of response as well as the pseudo-static (or static) component of response of secondary structures subjected to seismic excitations. For the dynamic component the independent response spectrum method is used with current industry practice for the modal and direction of excitation combinations being adopted and various procedures for the group combination and sequence being investigated. SRSS combination between support groups is found to yield satisfactory results. For the static component, support grouping by elevation for preliminary design followed by support grouping by attachment point for final design assure overall safety in the design

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

    Directory of Open Access Journals (Sweden)

    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.

  4. Fisher: a program for the detection of H/ACA snoRNAs using MFE secondary structure prediction and comparative genomics - assessment and update.

    Science.gov (United States)

    Freyhult, Eva; Edvardsson, Sverker; Tamas, Ivica; Moulton, Vincent; Poole, Anthony M

    2008-07-21

    The H/ACA family of small nucleolar RNAs (snoRNAs) plays a central role in guiding the pseudouridylation of ribosomal RNA (rRNA). In an effort to systematically identify the complete set of rRNA-modifying H/ACA snoRNAs from the genome sequence of the budding yeast, Saccharomyces cerevisiae, we developed a program - Fisher - and previously presented several candidate snoRNAs based on our analysis 1. In this report, we provide a brief update of this work, which was aborted after the publication of experimentally-identified snoRNAs 2 identical to candidates we had identified bioinformatically using Fisher. Our motivation for revisiting this work is to report on the status of the candidate snoRNAs described in 1, and secondly, to report that a modified version of Fisher together with the available multiple yeast genome sequences was able to correctly identify several H/ACA snoRNAs for modification sites not identified by the snoGPS program 3. While we are no longer developing Fisher, we briefly consider the merits of the Fisher algorithm relative to snoGPS, which may be of use for workers considering pursuing a similar search strategy for the identification of small RNAs. The modified source code for Fisher is made available as supplementary material. Our results confirm the validity of using minimum free energy (MFE) secondary structure prediction to guide comparative genomic screening for RNA families with few sequence constraints.

  5. Algorithms for Protein Structure Prediction

    DEFF Research Database (Denmark)

    Paluszewski, Martin

    -trace. Here we present three different approaches for reconstruction of C-traces from predictable measures. In our first approach [63, 62], the C-trace is positioned on a lattice and a tabu-search algorithm is applied to find minimum energy structures. The energy function is based on half-sphere-exposure (HSE......) is more robust than standard Monte Carlo search. In the second approach for reconstruction of C-traces, an exact branch and bound algorithm has been developed [67, 65]. The model is discrete and makes use of secondary structure predictions, HSE, CN and radius of gyration. We show how to compute good lower...... bounds for partial structures very fast. Using these lower bounds, we are able to find global minimum structures in a huge conformational space in reasonable time. We show that many of these global minimum structures are of good quality compared to the native structure. Our branch and bound algorithm...

  6. Deep recurrent conditional random field network for protein secondary prediction

    DEFF Research Database (Denmark)

    Johansen, Alexander Rosenberg; Sønderby, Søren Kaae; Sønderby, Casper Kaae

    2017-01-01

    Deep learning has become the state-of-the-art method for predicting protein secondary structure from only its amino acid residues and sequence profile. Building upon these results, we propose to combine a bi-directional recurrent neural network (biRNN) with a conditional random field (CRF), which...... of the labels for all time-steps. We condition the CRF on the output of biRNN, which learns a distributed representation based on the entire sequence. The biRNN-CRF is therefore close to ideally suited for the secondary structure task because a high degree of cross-talk between neighboring elements can...

  7. Facilitating RNA structure prediction with microarrays.

    Science.gov (United States)

    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.

  8. Fisher: a program for the detection of H/ACA snoRNAs using MFE secondary structure prediction and comparative genomics – assessment and update

    Directory of Open Access Journals (Sweden)

    Tamas Ivica

    2008-07-01

    Full Text Available Abstract Background The H/ACA family of small nucleolar RNAs (snoRNAs plays a central role in guiding the pseudouridylation of ribosomal RNA (rRNA. In an effort to systematically identify the complete set of rRNA-modifying H/ACA snoRNAs from the genome sequence of the budding yeast, Saccharomyces cerevisiae, we developed a program – Fisher – and previously presented several candidate snoRNAs based on our analysis 1. Findings In this report, we provide a brief update of this work, which was aborted after the publication of experimentally-identified snoRNAs 2 identical to candidates we had identified bioinformatically using Fisher. Our motivation for revisiting this work is to report on the status of the candidate snoRNAs described in 1, and secondly, to report that a modified version of Fisher together with the available multiple yeast genome sequences was able to correctly identify several H/ACA snoRNAs for modification sites not identified by the snoGPS program 3. While we are no longer developing Fisher, we briefly consider the merits of the Fisher algorithm relative to snoGPS, which may be of use for workers considering pursuing a similar search strategy for the identification of small RNAs. The modified source code for Fisher is made available as supplementary material. Conclusion Our results confirm the validity of using minimum free energy (MFE secondary structure prediction to guide comparative genomic screening for RNA families with few sequence constraints.

  9. Structural prediction in aphasia

    Directory of Open Access Journals (Sweden)

    Tessa Warren

    2015-05-01

    Full Text Available There is considerable evidence that young healthy comprehenders predict the structure of upcoming material, and that their processing is facilitated when they encounter material matching those predictions (e.g., Staub & Clifton, 2006; Yoshida, Dickey & Sturt, 2013. However, less is known about structural prediction in aphasia. There is evidence that lexical prediction may be spared in aphasia (Dickey et al., 2014; Love & Webb, 1977; cf. Mack et al, 2013. However, predictive mechanisms supporting facilitated lexical access may not necessarily support structural facilitation. Given that many people with aphasia (PWA exhibit syntactic deficits (e.g. Goodglass, 1993, PWA with such impairments may not engage in structural prediction. However, recent evidence suggests that some PWA may indeed predict upcoming structure (Hanne, Burchert, De Bleser, & Vashishth, 2015. Hanne et al. tracked the eyes of PWA (n=8 with sentence-comprehension deficits while they listened to reversible subject-verb-object (SVO and object-verb-subject (OVS sentences in German, in a sentence-picture matching task. Hanne et al. manipulated case and number marking to disambiguate the sentences’ structure. Gazes to an OVS or SVO picture during the unfolding of a sentence were assumed to indicate prediction of the structure congruent with that picture. According to this measure, the PWA’s structural prediction was impaired compared to controls, but they did successfully predict upcoming structure when morphosyntactic cues were strong and unambiguous. Hanne et al.’s visual-world evidence is suggestive, but their forced-choice sentence-picture matching task places tight constraints on possible structural predictions. Clearer evidence of structural prediction would come from paradigms where the content of upcoming material is not as constrained. The current study used self-paced reading study to examine structural prediction among PWA in less constrained contexts. PWA (n=17 who

  10. Linguistic Structure Prediction

    CERN Document Server

    Smith, Noah A

    2011-01-01

    A major part of natural language processing now depends on the use of text data to build linguistic analyzers. We consider statistical, computational approaches to modeling linguistic structure. We seek to unify across many approaches and many kinds of linguistic structures. Assuming a basic understanding of natural language processing and/or machine learning, we seek to bridge the gap between the two fields. Approaches to decoding (i.e., carrying out linguistic structure prediction) and supervised and unsupervised learning of models that predict discrete structures as outputs are the focus. W

  11. Amino acid code of protein secondary structure.

    Science.gov (United States)

    Shestopalov, B V

    2003-01-01

    The calculation of protein three-dimensional structure from the amino acid sequence is a fundamental problem to be solved. This paper presents principles of the code theory of protein secondary structure, and their consequence--the amino acid code of protein secondary structure. The doublet code model of protein secondary structure, developed earlier by the author (Shestopalov, 1990), is part of this theory. The theory basis are: 1) the name secondary structure is assigned to the conformation, stabilized only by the nearest (intraresidual) and middle-range (at a distance no more than that between residues i and i + 5) interactions; 2) the secondary structure consists of regular (alpha-helical and beta-structural) and irregular (coil) segments; 3) the alpha-helices, beta-strands and coil segments are encoded, respectively, by residue pairs (i, i + 4), (i, i + 2), (i, i = 1), according to the numbers of residues per period, 3.6, 2, 1; 4) all such pairs in the amino acid sequence are codons for elementary structural elements, or structurons; 5) the codons are divided into 21 types depending on their strength, i.e. their encoding capability; 6) overlappings of structurons of one and the same structure generate the longer segments of this structure; 7) overlapping of structurons of different structures is forbidden, and therefore selection of codons is required, the codon selection is hierarchic; 8) the code theory of protein secondary structure generates six variants of the amino acid code of protein secondary structure. There are two possible kinds of model construction based on the theory: the physical one using physical properties of amino acid residues, and the statistical one using results of statistical analysis of a great body of structural data. Some evident consequences of the theory are: a) the theory can be used for calculating the secondary structure from the amino acid sequence as a partial solution of the problem of calculation of protein three

  12. Use of secondary structural information and Cα-Cα distance ...

    Indian Academy of Sciences (India)

    PRAKASH KUMAR

    2007-06-21

    Jun 21, 2007 ... Model evolution; protein modelling; residue contact prediction; secondary structure prediction. Abbreviations used: ... set of sequence data (NR) and calculated conservation index of each ... evaluators (Moult et al 2003) to evaluate these model ... (Siew et al 2000), is a measure aims at identifying the largest.

  13. Predicting RNA Structure Using Mutual Information

    DEFF Research Database (Denmark)

    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...

  14. Characteristics and Prediction of RNA Structure

    Directory of Open Access Journals (Sweden)

    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.

  15. Computing the Partition Function for Kinetically Trapped RNA Secondary Structures

    Science.gov (United States)

    Lorenz, William A.; Clote, Peter

    2011-01-01

    An RNA secondary structure is locally optimal if there is no lower energy structure that can be obtained by the addition or removal of a single base pair, where energy is defined according to the widely accepted Turner nearest neighbor model. Locally optimal structures form kinetic traps, since any evolution away from a locally optimal structure must involve energetically unfavorable folding steps. Here, we present a novel, efficient algorithm to compute the partition function over all locally optimal secondary structures of a given RNA sequence. Our software, RNAlocopt runs in time and space. Additionally, RNAlocopt samples a user-specified number of structures from the Boltzmann subensemble of all locally optimal structures. We apply RNAlocopt to show that (1) the number of locally optimal structures is far fewer than the total number of structures – indeed, the number of locally optimal structures approximately equal to the square root of the number of all structures, (2) the structural diversity of this subensemble may be either similar to or quite different from the structural diversity of the entire Boltzmann ensemble, a situation that depends on the type of input RNA, (3) the (modified) maximum expected accuracy structure, computed by taking into account base pairing frequencies of locally optimal structures, is a more accurate prediction of the native structure than other current thermodynamics-based methods. The software RNAlocopt constitutes a technical breakthrough in our study of the folding landscape for RNA secondary structures. For the first time, locally optimal structures (kinetic traps in the Turner energy model) can be rapidly generated for long RNA sequences, previously impossible with methods that involved exhaustive enumeration. Use of locally optimal structure leads to state-of-the-art secondary structure prediction, as benchmarked against methods involving the computation of minimum free energy and of maximum expected accuracy. Web server

  16. Computing the partition function for kinetically trapped RNA secondary structures.

    Directory of Open Access Journals (Sweden)

    William A Lorenz

    Full Text Available An RNA secondary structure is locally optimal if there is no lower energy structure that can be obtained by the addition or removal of a single base pair, where energy is defined according to the widely accepted Turner nearest neighbor model. Locally optimal structures form kinetic traps, since any evolution away from a locally optimal structure must involve energetically unfavorable folding steps. Here, we present a novel, efficient algorithm to compute the partition function over all locally optimal secondary structures of a given RNA sequence. Our software, RNAlocopt runs in O(n3 time and O(n2 space. Additionally, RNAlocopt samples a user-specified number of structures from the Boltzmann subensemble of all locally optimal structures. We apply RNAlocopt to show that (1 the number of locally optimal structures is far fewer than the total number of structures--indeed, the number of locally optimal structures approximately equal to the square root of the number of all structures, (2 the structural diversity of this subensemble may be either similar to or quite different from the structural diversity of the entire Boltzmann ensemble, a situation that depends on the type of input RNA, (3 the (modified maximum expected accuracy structure, computed by taking into account base pairing frequencies of locally optimal structures, is a more accurate prediction of the native structure than other current thermodynamics-based methods. The software RNAlocopt constitutes a technical breakthrough in our study of the folding landscape for RNA secondary structures. For the first time, locally optimal structures (kinetic traps in the Turner energy model can be rapidly generated for long RNA sequences, previously impossible with methods that involved exhaustive enumeration. Use of locally optimal structure leads to state-of-the-art secondary structure prediction, as benchmarked against methods involving the computation of minimum free energy and of maximum expected

  17. Secondary structural analyses of ITS1 in Paramecium.

    Science.gov (United States)

    Hoshina, Ryo

    2010-01-01

    The nuclear ribosomal RNA gene operon is interrupted by internal transcribed spacer (ITS) 1 and ITS2. Although the secondary structure of ITS2 has been widely investigated, less is known about ITS1 and its structure. In this study, the secondary structure of ITS1 sequences for Paramecium and other ciliates was predicted. Each Paramecium ITS1 forms an open loop with three helices, A through C. Helix B was highly conserved among Paramecium, and similar helices were found in other ciliates. A phylogenetic analysis using the ITS1 sequences showed high-resolution, implying that ITS1 is a good tool for species-level analyses.

  18. A method for rapid similarity analysis of RNA secondary structures

    Directory of Open Access Journals (Sweden)

    Liu Na

    2006-11-01

    Full Text Available Abstract Background Owing to the rapid expansion of RNA structure databases in recent years, efficient methods for structure comparison are in demand for function prediction and evolutionary analysis. Usually, the similarity of RNA secondary structures is evaluated based on tree models and dynamic programming algorithms. We present here a new method for the similarity analysis of RNA secondary structures. Results Three sets of real data have been used as input for the example applications. Set I includes the structures from 5S rRNAs. Set II includes the secondary structures from RNase P and RNase MRP. Set III includes the structures from 16S rRNAs. Reasonable phylogenetic trees are derived for these three sets of data by using our method. Moreover, our program runs faster as compared to some existing ones. Conclusion The famous Lempel-Ziv algorithm can efficiently extract the information on repeated patterns encoded in RNA secondary structures and makes our method an alternative to analyze the similarity of RNA secondary structures. This method will also be useful to researchers who are interested in evolutionary analysis.

  19. Strong eukaryotic IRESs have weak secondary structure.

    Directory of Open Access Journals (Sweden)

    Xuhua Xia

    Full Text Available BACKGROUND: The objective of this work was to investigate the hypothesis that eukaryotic Internal Ribosome Entry Sites (IRES lack secondary structure and to examine the generality of the hypothesis. METHODOLOGY/PRINCIPAL FINDINGS: IRESs of the yeast and the fruit fly are located in the 5'UTR immediately upstream of the initiation codon. The minimum folding energy (MFE of 60 nt RNA segments immediately upstream of the initiation codons was calculated as a proxy of secondary structure stability. MFE of the reverse complements of these 60 nt segments was also calculated. The relationship between MFE and empirically determined IRES activity was investigated to test the hypothesis that strong IRES activity is associated with weak secondary structure. We show that IRES activity in the yeast and the fruit fly correlates strongly with the structural stability, with highest IRES activity found in RNA segments that exhibit the weakest secondary structure. CONCLUSIONS: We found that a subset of eukaryotic IRESs exhibits very low secondary structure in the 5'-UTR sequences immediately upstream of the initiation codon. The consistency in results between the yeast and the fruit fly suggests a possible shared mechanism of cap-independent translation initiation that relies on an unstructured RNA segment.

  20. Capturing non-local interactions by long short-term memory bidirectional recurrent neural networks for improving prediction of protein secondary structure, backbone angles, contact numbers and solvent accessibility.

    Science.gov (United States)

    Heffernan, Rhys; Yang, Yuedong; Paliwal, Kuldip; Zhou, Yaoqi

    2017-09-15

    The accuracy of predicting protein local and global structural properties such as secondary structure and solvent accessible surface area has been stagnant for many years because of the challenge of accounting for non-local interactions between amino acid residues that are close in three-dimensional structural space but far from each other in their sequence positions. All existing machine-learning techniques relied on a sliding window of 10-20 amino acid residues to capture some 'short to intermediate' non-local interactions. Here, we employed Long Short-Term Memory (LSTM) Bidirectional Recurrent Neural Networks (BRNNs) which are capable of capturing long range interactions without using a window. We showed that the application of LSTM-BRNN to the prediction of protein structural properties makes the most significant improvement for residues with the most long-range contacts (|i-j| >19) over a previous window-based, deep-learning method SPIDER2. Capturing long-range interactions allows the accuracy of three-state secondary structure prediction to reach 84% and the correlation coefficient between predicted and actual solvent accessible surface areas to reach 0.80, plus a reduction of 5%, 10%, 5% and 10% in the mean absolute error for backbone ϕ , ψ , θ and τ angles, respectively, from SPIDER2. More significantly, 27% of 182724 40-residue models directly constructed from predicted C α atom-based θ and τ have similar structures to their corresponding native structures (6Å RMSD or less), which is 3% better than models built by ϕ and ψ angles. We expect the method to be useful for assisting protein structure and function prediction. The method is available as a SPIDER3 server and standalone package at http://sparks-lab.org . yaoqi.zhou@griffith.edu.au or yuedong.yang@griffith.edu.au. Supplementary data are available at Bioinformatics online. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email

  1. Predicting Thermal Behavior of Secondary Organic Aerosols

    Science.gov (United States)

    Volume concentrations of steady-state secondary organic aerosol (SOA) were measured in 139 steadystate single precursor hydrocarbon oxidation experiments after passing through a temperature controlled inlet tube. Higher temperatures resulted in greater loss of particle volume, wi...

  2. Predicting Thermal Behavior of Secondary Organic Aerosols

    Data.gov (United States)

    U.S. Environmental Protection Agency — Volume concentrations of secondary organic aerosol (SOA) are measured in 139 steady-state, single precursor hydrocarbon oxidation experiments after passing through a...

  3. Accurate SHAPE-directed RNA secondary structure modeling, including pseudoknots.

    Science.gov (United States)

    Hajdin, Christine E; Bellaousov, Stanislav; Huggins, Wayne; Leonard, Christopher W; Mathews, David H; Weeks, Kevin M

    2013-04-02

    A pseudoknot forms in an RNA when nucleotides in a loop pair with a region outside the helices that close the loop. Pseudoknots occur relatively rarely in RNA but are highly overrepresented in functionally critical motifs in large catalytic RNAs, in riboswitches, and in regulatory elements of viruses. Pseudoknots are usually excluded from RNA structure prediction algorithms. When included, these pairings are difficult to model accurately, especially in large RNAs, because allowing this structure dramatically increases the number of possible incorrect folds and because it is difficult to search the fold space for an optimal structure. We have developed a concise secondary structure modeling approach that combines SHAPE (selective 2'-hydroxyl acylation analyzed by primer extension) experimental chemical probing information and a simple, but robust, energy model for the entropic cost of single pseudoknot formation. Structures are predicted with iterative refinement, using a dynamic programming algorithm. This melded experimental and thermodynamic energy function predicted the secondary structures and the pseudoknots for a set of 21 challenging RNAs of known structure ranging in size from 34 to 530 nt. On average, 93% of known base pairs were predicted, and all pseudoknots in well-folded RNAs were identified.

  4. Sensitization predicts asthma development among wheezing toddlers in secondary healthcare

    NARCIS (Netherlands)

    Boersma, Nienke A.; Meijneke, Ruud W.H.; Kelder, Johannes C.; van der Ent, Cornelis K.; Balemans, Walter A.F.

    2017-01-01

    Introduction: Some wheezing toddlers develop asthma later in childhood. Sensitization is known to predict asthma in birth cohorts. However, its predictive value in secondary healthcare is uncertain. Aim: This study examines the predictive value of sensitization to inhalant allergens among wheezing

  5. Structure elucidation of secondary natural products

    International Nuclear Information System (INIS)

    Seger, C.

    2001-06-01

    The presented thesis deals with the structure elucidation of secondary natural products. Most of the compounds under investigation were terpenes, especially triterpenes, alkaloids and stilbenoids. Besides characterizing a multitude of already known and also new compounds, it was possible to detect and correct wrongly assigned literature data. The methodological aspect of this thesis lies - beside in the utilization of modern 2D NMR spectroscopy - in the evaluation of computer assisted structure elucidation (CASE) techniques in the course of spectroscopy supported structure elucidation processes. (author)

  6. Predicting secondary school dropout among South African ...

    African Journals Online (AJOL)

    ... not living with one's mother, smoking cigarettes in the past month, and lower levels of leisure-related intrinsic motivation significantly predicted dropout. Results support comprehensive prevention programmes that target risk behaviour and leisure. Keywords: adolescence; leisure motivation; school dropout; substance use ...

  7. STUDYING THE SECONDARY STRUCTURE OF ACCESSION NUMBER USING CETD MATRIX

    Directory of Open Access Journals (Sweden)

    Anamika Dutta

    2016-10-01

    Full Text Available This paper, we have tried to analyze about the Secondary Structure of nucleotide sequences of rice. The data have been collected from NCBI (National Centre for Biotechnology Information using Nucleotide as data base. All the programs were developed using R programming language using “sequinr” package. Here, we have used CETD matrix method to study the prediction. The conclusions are drawn accordingly.

  8. Improved protein structure reconstruction using secondary structures, contacts at higher distance thresholds, and non-contacts.

    Science.gov (United States)

    Adhikari, Badri; Cheng, Jianlin

    2017-08-29

    Residue-residue contacts are key features for accurate de novo protein structure prediction. For the optimal utilization of these predicted contacts in folding proteins accurately, it is important to study the challenges of reconstructing protein structures using true contacts. Because contact-guided protein modeling approach is valuable for predicting the folds of proteins that do not have structural templates, it is necessary for reconstruction studies to focus on hard-to-predict protein structures. Using a data set consisting of 496 structural domains released in recent CASP experiments and a dataset of 150 representative protein structures, in this work, we discuss three techniques to improve the reconstruction accuracy using true contacts - adding secondary structures, increasing contact distance thresholds, and adding non-contacts. We find that reconstruction using secondary structures and contacts can deliver accuracy higher than using full contact maps. Similarly, we demonstrate that non-contacts can improve reconstruction accuracy not only when the used non-contacts are true but also when they are predicted. On the dataset consisting of 150 proteins, we find that by simply using low ranked predicted contacts as non-contacts and adding them as additional restraints, can increase the reconstruction accuracy by 5% when the reconstructed models are evaluated using TM-score. Our findings suggest that secondary structures are invaluable companions of contacts for accurate reconstruction. Confirming some earlier findings, we also find that larger distance thresholds are useful for folding many protein structures which cannot be folded using the standard definition of contacts. Our findings also suggest that for more accurate reconstruction using predicted contacts it is useful to predict contacts at higher distance thresholds (beyond 8 Å) and predict non-contacts.

  9. JNSViewer-A JavaScript-based Nucleotide Sequence Viewer for DNA/RNA secondary structures.

    Science.gov (United States)

    Shi, Jieming; Li, Xi; Dong, Min; Graham, Mitchell; Yadav, Nehul; Liang, Chun

    2017-01-01

    Many tools are available for visualizing RNA or DNA secondary structures, but there is scarce implementation in JavaScript that provides seamless integration with the increasingly popular web computational platforms. We have developed JNSViewer, a highly interactive web service, which is bundled with several popular tools for DNA/RNA secondary structure prediction and can provide precise and interactive correspondence among nucleotides, dot-bracket data, secondary structure graphs, and genic annotations. In JNSViewer, users can perform RNA secondary structure predictions with different programs and settings, add customized genic annotations in GFF format to structure graphs, search for specific linear motifs, and extract relevant structure graphs of sub-sequences. JNSViewer also allows users to choose a transcript or specific segment of Arabidopsis thaliana genome sequences and predict the corresponding secondary structure. Popular genome browsers (i.e., JBrowse and BrowserGenome) were integrated into JNSViewer to provide powerful visualizations of chromosomal locations, genic annotations, and secondary structures. In addition, we used StructureFold with default settings to predict some RNA structures for Arabidopsis by incorporating in vivo high-throughput RNA structure profiling data and stored the results in our web server, which might be a useful resource for RNA secondary structure studies in plants. JNSViewer is available at http://bioinfolab.miamioh.edu/jnsviewer/index.html.

  10. JNSViewer—A JavaScript-based Nucleotide Sequence Viewer for DNA/RNA secondary structures

    Science.gov (United States)

    Dong, Min; Graham, Mitchell; Yadav, Nehul

    2017-01-01

    Many tools are available for visualizing RNA or DNA secondary structures, but there is scarce implementation in JavaScript that provides seamless integration with the increasingly popular web computational platforms. We have developed JNSViewer, a highly interactive web service, which is bundled with several popular tools for DNA/RNA secondary structure prediction and can provide precise and interactive correspondence among nucleotides, dot-bracket data, secondary structure graphs, and genic annotations. In JNSViewer, users can perform RNA secondary structure predictions with different programs and settings, add customized genic annotations in GFF format to structure graphs, search for specific linear motifs, and extract relevant structure graphs of sub-sequences. JNSViewer also allows users to choose a transcript or specific segment of Arabidopsis thaliana genome sequences and predict the corresponding secondary structure. Popular genome browsers (i.e., JBrowse and BrowserGenome) were integrated into JNSViewer to provide powerful visualizations of chromosomal locations, genic annotations, and secondary structures. In addition, we used StructureFold with default settings to predict some RNA structures for Arabidopsis by incorporating in vivo high-throughput RNA structure profiling data and stored the results in our web server, which might be a useful resource for RNA secondary structure studies in plants. JNSViewer is available at http://bioinfolab.miamioh.edu/jnsviewer/index.html. PMID:28582416

  11. JNSViewer-A JavaScript-based Nucleotide Sequence Viewer for DNA/RNA secondary structures.

    Directory of Open Access Journals (Sweden)

    Jieming Shi

    Full Text Available Many tools are available for visualizing RNA or DNA secondary structures, but there is scarce implementation in JavaScript that provides seamless integration with the increasingly popular web computational platforms. We have developed JNSViewer, a highly interactive web service, which is bundled with several popular tools for DNA/RNA secondary structure prediction and can provide precise and interactive correspondence among nucleotides, dot-bracket data, secondary structure graphs, and genic annotations. In JNSViewer, users can perform RNA secondary structure predictions with different programs and settings, add customized genic annotations in GFF format to structure graphs, search for specific linear motifs, and extract relevant structure graphs of sub-sequences. JNSViewer also allows users to choose a transcript or specific segment of Arabidopsis thaliana genome sequences and predict the corresponding secondary structure. Popular genome browsers (i.e., JBrowse and BrowserGenome were integrated into JNSViewer to provide powerful visualizations of chromosomal locations, genic annotations, and secondary structures. In addition, we used StructureFold with default settings to predict some RNA structures for Arabidopsis by incorporating in vivo high-throughput RNA structure profiling data and stored the results in our web server, which might be a useful resource for RNA secondary structure studies in plants. JNSViewer is available at http://bioinfolab.miamioh.edu/jnsviewer/index.html.

  12. Strategies for measuring evolutionary conservation of RNA secondary structures

    Directory of Open Access Journals (Sweden)

    Hofacker Ivo L

    2008-02-01

    Full Text Available Abstract Background Evolutionary conservation of RNA secondary structure is a typical feature of many functional non-coding RNAs. Since almost all of the available methods used for prediction and annotation of non-coding RNA genes rely on this evolutionary signature, accurate measures for structural conservation are essential. Results We systematically assessed the ability of various measures to detect conserved RNA structures in multiple sequence alignments. We tested three existing and eight novel strategies that are based on metrics of folding energies, metrics of single optimal structure predictions, and metrics of structure ensembles. We find that the folding energy based SCI score used in the RNAz program and a simple base-pair distance metric are by far the most accurate. The use of more complex metrics like for example tree editing does not improve performance. A variant of the SCI performed particularly well on highly conserved alignments and is thus a viable alternative when only little evolutionary information is available. Surprisingly, ensemble based methods that, in principle, could benefit from the additional information contained in sub-optimal structures, perform particularly poorly. As a general trend, we observed that methods that include a consensus structure prediction outperformed equivalent methods that only consider pairwise comparisons. Conclusion Structural conservation can be measured accurately with relatively simple and intuitive metrics. They have the potential to form the basis of future RNA gene finders, that face new challenges like finding lineage specific structures or detecting mis-aligned sequences.

  13. Rtools: a web server for various secondary structural analyses on single RNA sequences.

    Science.gov (United States)

    Hamada, Michiaki; Ono, Yukiteru; Kiryu, Hisanori; Sato, Kengo; Kato, Yuki; Fukunaga, Tsukasa; Mori, Ryota; Asai, Kiyoshi

    2016-07-08

    The secondary structures, as well as the nucleotide sequences, are the important features of RNA molecules to characterize their functions. According to the thermodynamic model, however, the probability of any secondary structure is very small. As a consequence, any tool to predict the secondary structures of RNAs has limited accuracy. On the other hand, there are a few tools to compensate the imperfect predictions by calculating and visualizing the secondary structural information from RNA sequences. It is desirable to obtain the rich information from those tools through a friendly interface. We implemented a web server of the tools to predict secondary structures and to calculate various structural features based on the energy models of secondary structures. By just giving an RNA sequence to the web server, the user can get the different types of solutions of the secondary structures, the marginal probabilities such as base-paring probabilities, loop probabilities and accessibilities of the local bases, the energy changes by arbitrary base mutations as well as the measures for validations of the predicted secondary structures. The web server is available at http://rtools.cbrc.jp, which integrates software tools, CentroidFold, CentroidHomfold, IPKnot, CapR, Raccess, Rchange and RintD. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

  14. Prediction of molecular crystal structures

    International Nuclear Information System (INIS)

    Beyer, Theresa

    2001-01-01

    The ab initio prediction of molecular crystal structures is a scientific challenge. Reliability of first-principle prediction calculations would show a fundamental understanding of crystallisation. Crystal structure prediction is also of considerable practical importance as different crystalline arrangements of the same molecule in the solid state (polymorphs)are likely to have different physical properties. A method of crystal structure prediction based on lattice energy minimisation has been developed in this work. The choice of the intermolecular potential and of the molecular model is crucial for the results of such studies and both of these criteria have been investigated. An empirical atom-atom repulsion-dispersion potential for carboxylic acids has been derived and applied in a crystal structure prediction study of formic, benzoic and the polymorphic system of tetrolic acid. As many experimental crystal structure determinations at different temperatures are available for the polymorphic system of paracetamol (acetaminophen), the influence of the variations of the molecular model on the crystal structure lattice energy minima, has also been studied. The general problem of prediction methods based on the assumption that the experimental thermodynamically stable polymorph corresponds to the global lattice energy minimum, is that more hypothetical low lattice energy structures are found within a few kJ mol -1 of the global minimum than are likely to be experimentally observed polymorphs. This is illustrated by the results for molecule I, 3-oxabicyclo(3.2.0)hepta-1,4-diene, studied for the first international blindtest for small organic crystal structures organised by the Cambridge Crystallographic Data Centre (CCDC) in May 1999. To reduce the number of predicted polymorphs, additional factors to thermodynamic criteria have to be considered. Therefore the elastic constants and vapour growth morphologies have been calculated for the lowest lattice energy

  15. Prediction of molecular crystal structures

    Energy Technology Data Exchange (ETDEWEB)

    Beyer, Theresa

    2001-07-01

    The ab initio prediction of molecular crystal structures is a scientific challenge. Reliability of first-principle prediction calculations would show a fundamental understanding of crystallisation. Crystal structure prediction is also of considerable practical importance as different crystalline arrangements of the same molecule in the solid state (polymorphs)are likely to have different physical properties. A method of crystal structure prediction based on lattice energy minimisation has been developed in this work. The choice of the intermolecular potential and of the molecular model is crucial for the results of such studies and both of these criteria have been investigated. An empirical atom-atom repulsion-dispersion potential for carboxylic acids has been derived and applied in a crystal structure prediction study of formic, benzoic and the polymorphic system of tetrolic acid. As many experimental crystal structure determinations at different temperatures are available for the polymorphic system of paracetamol (acetaminophen), the influence of the variations of the molecular model on the crystal structure lattice energy minima, has also been studied. The general problem of prediction methods based on the assumption that the experimental thermodynamically stable polymorph corresponds to the global lattice energy minimum, is that more hypothetical low lattice energy structures are found within a few kJ mol{sup -1} of the global minimum than are likely to be experimentally observed polymorphs. This is illustrated by the results for molecule I, 3-oxabicyclo(3.2.0)hepta-1,4-diene, studied for the first international blindtest for small organic crystal structures organised by the Cambridge Crystallographic Data Centre (CCDC) in May 1999. To reduce the number of predicted polymorphs, additional factors to thermodynamic criteria have to be considered. Therefore the elastic constants and vapour growth morphologies have been calculated for the lowest lattice energy

  16. Sensitization predicts asthma development among wheezing toddlers in secondary healthcare.

    Science.gov (United States)

    Boersma, Nienke A; Meijneke, Ruud W H; Kelder, Johannes C; van der Ent, Cornelis K; Balemans, Walter A F

    2017-06-01

    Some wheezing toddlers develop asthma later in childhood. Sensitization is known to predict asthma in birth cohorts. However, its predictive value in secondary healthcare is uncertain. This study examines the predictive value of sensitization to inhalant allergens among wheezing toddlers in secondary healthcare for the development of asthma at school age (≥6 years). Preschool children (1-3 years) who presented with wheezing in secondary healthcare were screened on asthma at school age with the International Study of Asthma and Allergies in Childhood questionnaire. The positive and negative predictive value (PPV and NPV) of specific IgE to inhalant allergens (cut-off concentration 0.35 kU/L) and several non-invasive variables from a child's history (such as hospitalization, eczema, and parental atopy) were calculated. The additional predictive value of sensitization when combined with non-invasive predictors was examined in multivariate analysis and by ROC curves. Of 116 included children, 63% developed asthma at school age. Sensitization to inhalant allergens was a strong asthma predictor. The odds ratio (OR), PPV and NPV were 7.4%, 86%, and 55%, respectively. Eczema (OR 3.4) and hospital admission (OR 2.6) were significant non-invasive determinants. Adding sensitization to these non-invasive predictors in multivariate analysis resulted in a significantly better asthma prediction. The area under the ROC curve increased from 0.70 with only non-invasive predictors to 0.79 after adding sensitization. Sensitization to inhalant allergens is a strong predictor of school age asthma in secondary healthcare and has added predictive value when combined with non-invasive determinants. Pediatr Pulmonol. 2017;52:729-736. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

  17. Capturing alternative secondary structures of RNA by decomposition of base-pairing probabilities.

    Science.gov (United States)

    Hagio, Taichi; Sakuraba, Shun; Iwakiri, Junichi; Mori, Ryota; Asai, Kiyoshi

    2018-02-19

    It is known that functional RNAs often switch their functions by forming different secondary structures. Popular tools for RNA secondary structures prediction, however, predict the single 'best' structures, and do not produce alternative structures. There are bioinformatics tools to predict suboptimal structures, but it is difficult to detect which alternative secondary structures are essential. We proposed a new computational method to detect essential alternative secondary structures from RNA sequences by decomposing the base-pairing probability matrix. The decomposition is calculated by a newly implemented software tool, RintW, which efficiently computes the base-pairing probability distributions over the Hamming distance from arbitrary reference secondary structures. The proposed approach has been demonstrated on ROSE element RNA thermometer sequence and Lysine RNA ribo-switch, showing that the proposed approach captures conformational changes in secondary structures. We have shown that alternative secondary structures are captured by decomposing base-paring probabilities over Hamming distance. Source code is available from http://www.ncRNA.org/RintW .

  18. Mathematical and Biological Modelling of RNA Secondary Structure and Its Effects on Gene Expression

    Directory of Open Access Journals (Sweden)

    T. A. Hughes

    2006-01-01

    Full Text Available Secondary structures within the 5′ untranslated regions of messenger RNAs can have profound effects on the efficiency of translation of their messages and thereby on gene expression. Consequently they can act as important regulatory motifs in both physiological and pathological settings. Current approaches to predicting the secondary structure of these RNA sequences find the structure with the global-minimum free energy. However, since RNA folds progressively from the 5′ end when synthesised or released from the translational machinery, this may not be the most probable structure. We discuss secondary structure prediction based on local-minimisation of free energy with thermodynamic fluctuations as nucleotides are added to the 3′ end and show that these can result in different secondary structures. We also discuss approaches for studying the extent of the translational inhibition specified by structures within the 5′ untranslated region.

  19. Protein Structure Prediction by Protein Threading

    Science.gov (United States)

    Xu, Ying; Liu, Zhijie; Cai, Liming; Xu, Dong

    The seminal work of Bowie, Lüthy, and Eisenberg (Bowie et al., 1991) on "the inverse protein folding problem" laid the foundation of protein structure prediction by protein threading. By using simple measures for fitness of different amino acid types to local structural environments defined in terms of solvent accessibility and protein secondary structure, the authors derived a simple and yet profoundly novel approach to assessing if a protein sequence fits well with a given protein structural fold. Their follow-up work (Elofsson et al., 1996; Fischer and Eisenberg, 1996; Fischer et al., 1996a,b) and the work by Jones, Taylor, and Thornton (Jones et al., 1992) on protein fold recognition led to the development of a new brand of powerful tools for protein structure prediction, which we now term "protein threading." These computational tools have played a key role in extending the utility of all the experimentally solved structures by X-ray crystallography and nuclear magnetic resonance (NMR), providing structural models and functional predictions for many of the proteins encoded in the hundreds of genomes that have been sequenced up to now.

  20. Random generation of RNA secondary structures according to native distributions

    Directory of Open Access Journals (Sweden)

    Nebel Markus E

    2011-10-01

    Full Text Available Abstract Background Random biological sequences are a topic of great interest in genome analysis since, according to a powerful paradigm, they represent the background noise from which the actual biological information must differentiate. Accordingly, the generation of random sequences has been investigated for a long time. Similarly, random object of a more complicated structure like RNA molecules or proteins are of interest. Results In this article, we present a new general framework for deriving algorithms for the non-uniform random generation of combinatorial objects according to the encoding and probability distribution implied by a stochastic context-free grammar. Briefly, the framework extends on the well-known recursive method for (uniform random generation and uses the popular framework of admissible specifications of combinatorial classes, introducing weighted combinatorial classes to allow for the non-uniform generation by means of unranking. This framework is used to derive an algorithm for the generation of RNA secondary structures of a given fixed size. We address the random generation of these structures according to a realistic distribution obtained from real-life data by using a very detailed context-free grammar (that models the class of RNA secondary structures by distinguishing between all known motifs in RNA structure. Compared to well-known sampling approaches used in several structure prediction tools (such as SFold ours has two major advantages: Firstly, after a preprocessing step in time O(n2 for the computation of all weighted class sizes needed, with our approach a set of m random secondary structures of a given structure size n can be computed in worst-case time complexity Om⋅n⋅ log(n while other algorithms typically have a runtime in O(m⋅n2. Secondly, our approach works with integer arithmetic only which is faster and saves us from all the discomforting details of using floating point arithmetic with

  1. Secondary Structure of Rat and Human Amylin across Force Fields.

    Directory of Open Access Journals (Sweden)

    Kyle Quynn Hoffmann

    Full Text Available The aggregation of human amylin has been strongly implicated in the progression of Type II diabetes. This 37-residue peptide forms a variety of secondary structures, including random coils, α-helices, and β-hairpins. The balance between these structures depends on the chemical environment, making amylin an ideal candidate to examine inherent biases in force fields. Rat amylin differs from human amylin by only 6 residues; however, it does not form fibrils. Therefore it provides a useful complement to human amylin in studies of the key events along the aggregation pathway. In this work, the free energy of rat and human amylin was determined as a function of α-helix and β-hairpin content for the Gromos96 53a6, OPLS-AA/L, CHARMM22/CMAP, CHARMM22*, Amberff99sb*-ILDN, and Amberff03w force fields using advanced sampling techniques, specifically bias exchange metadynamics. This work represents a first systematic attempt to evaluate the conformations and the corresponding free energy of a large, clinically relevant disordered peptide in solution across force fields. The NMR chemical shifts of rIAPP were calculated for each of the force fields using their respective free energy maps, allowing us to quantitatively assess their predictions. We show that the predicted distribution of secondary structures is sensitive to the choice of force-field: Gromos53a6 is biased towards β-hairpins, while CHARMM22/CMAP predicts structures that are overly α-helical. OPLS-AA/L favors disordered structures. Amberff99sb*-ILDN, AmberFF03w and CHARMM22* provide the balance between secondary structures that is most consistent with available experimental data. In contrast to previous reports, our findings suggest that the equilibrium conformations of human and rat amylin are remarkably similar, but that subtle differences arise in transient alpha-helical and beta-strand containing structures that the human peptide can more readily adopt. We hypothesize that these transient

  2. Critical Features of Fragment Libraries for Protein Structure Prediction.

    Science.gov (United States)

    Trevizani, Raphael; Custódio, Fábio Lima; Dos Santos, Karina Baptista; Dardenne, Laurent Emmanuel

    2017-01-01

    The use of fragment libraries is a popular approach among protein structure prediction methods and has proven to substantially improve the quality of predicted structures. However, some vital aspects of a fragment library that influence the accuracy of modeling a native structure remain to be determined. This study investigates some of these features. Particularly, we analyze the effect of using secondary structure prediction guiding fragments selection, different fragments sizes and the effect of structural clustering of fragments within libraries. To have a clearer view of how these factors affect protein structure prediction, we isolated the process of model building by fragment assembly from some common limitations associated with prediction methods, e.g., imprecise energy functions and optimization algorithms, by employing an exact structure-based objective function under a greedy algorithm. Our results indicate that shorter fragments reproduce the native structure more accurately than the longer. Libraries composed of multiple fragment lengths generate even better structures, where longer fragments show to be more useful at the beginning of the simulations. The use of many different fragment sizes shows little improvement when compared to predictions carried out with libraries that comprise only three different fragment sizes. Models obtained from libraries built using only sequence similarity are, on average, better than those built with a secondary structure prediction bias. However, we found that the use of secondary structure prediction allows greater reduction of the search space, which is invaluable for prediction methods. The results of this study can be critical guidelines for the use of fragment libraries in protein structure prediction.

  3. ncRNA consensus secondary structure derivation using grammar strings.

    Science.gov (United States)

    Achawanantakun, Rujira; Sun, Yanni; Takyar, Seyedeh Shohreh

    2011-04-01

    Many noncoding RNAs (ncRNAs) function through both their sequences and secondary structures. Thus, secondary structure derivation is an important issue in today's RNA research. The state-of-the-art structure annotation tools are based on comparative analysis, which derives consensus structure of homologous ncRNAs. Despite promising results from existing ncRNA aligning and consensus structure derivation tools, there is a need for more efficient and accurate ncRNA secondary structure modeling and alignment methods. In this work, we introduce a consensus structure derivation approach based on grammar string, a novel ncRNA secondary structure representation that encodes an ncRNA's sequence and secondary structure in the parameter space of a context-free grammar (CFG) and a full RNA grammar including pseudoknots. Being a string defined on a special alphabet constructed from a grammar, grammar string converts ncRNA alignment into sequence alignment. We derive consensus secondary structures from hundreds of ncRNA families from BraliBase 2.1 and 25 families containing pseudoknots using grammar string alignment. Our experiments have shown that grammar string-based structure derivation competes favorably in consensus structure quality with Murlet and RNASampler. Source code and experimental data are available at http://www.cse.msu.edu/~yannisun/grammar-string.

  4. Predicted Rates of Secondary Malignancies From Proton Versus Photon Radiation Therapy for Stage I Seminoma

    Energy Technology Data Exchange (ETDEWEB)

    Simone, Charles B., E-mail: csimone@alumni.upenn.edu [Department of Radiation Oncology, Hospital of University of Pennsylvania, Philadelphia, Pennsylvania (United States); Radiation Oncology Branch, National Cancer Institute, National Institutes of Health, Bethesda, Maryland (United States); Kramer, Kevin [Henry M. Jackson Foundation for the Advancement of Military Medicine, Rockville, Maryland (United States); O' Meara, William P. [Division of Radiation Oncology, National Naval Medical Center, Bethesda, Maryland (United States); Bekelman, Justin E. [Department of Radiation Oncology, Hospital of University of Pennsylvania, Philadelphia, Pennsylvania (United States); Belard, Arnaud [Henry M. Jackson Foundation for the Advancement of Military Medicine, Rockville, Maryland (United States); McDonough, James [Department of Radiation Oncology, Hospital of University of Pennsylvania, Philadelphia, Pennsylvania (United States); O' Connell, John [Radiation Oncology Service, Walter Reed Army Medical Center, Washington, DC (United States)

    2012-01-01

    Purpose: Photon radiotherapy has been the standard adjuvant treatment for stage I seminoma. Single-dose carboplatin therapy and observation have emerged as alternative options due to concerns for acute toxicities and secondary malignancies from radiation. In this institutional review board-approved study, we compared photon and proton radiotherapy for stage I seminoma and the predicted rates of excess secondary malignancies for both treatment modalities. Methods and Material: Computed tomography images from 10 consecutive patients with stage I seminoma were used to quantify dosimetric differences between photon and proton therapies. Structures reported to be at increased risk for secondary malignancies and in-field critical structures were contoured. Reported models of organ-specific radiation-induced cancer incidence rates based on organ equivalent dose were used to determine the excess absolute risk of secondary malignancies. Calculated values were compared with tumor registry reports of excess secondary malignancies among testicular cancer survivors. Results: Photon and proton plans provided comparable target volume coverage. Proton plans delivered significantly lower mean doses to all examined normal tissues, except for the kidneys. The greatest absolute reduction in mean dose was observed for the stomach (119 cGy for proton plans vs. 768 cGy for photon plans; p < 0.0001). Significantly more excess secondary cancers per 10,000 patients/year were predicted for photon radiation than for proton radiation to the stomach (4.11; 95% confidence interval [CI], 3.22-5.01), large bowel (0.81; 95% CI, 0.39-1.01), and bladder (0.03; 95% CI, 0.01-0.58), while no difference was demonstrated for radiation to the pancreas (0.02; 95% CI, -0.01-0.06). Conclusions: For patients with stage I seminoma, proton radiation therapy reduced the predicted secondary cancer risk compared with photon therapy. We predict a reduction of one additional secondary cancer for every 50 patients

  5. Secondary Education in the European Union: Structures, Organisation and Administration.

    Science.gov (United States)

    EURYDICE European Unit, Brussels (Belgium).

    This study examines the existing secondary education structures of the European Union member nations, the organization of education, teacher training, and the way in which secondary education is managed in Europe today. The three European Free Trade Association/European Economic Area (EFTA/EEC) countries (Iceland, Liechtenstein, and Norway) also…

  6. Original Paper Floristic and structural changes in secondary forests ...

    African Journals Online (AJOL)

    Data from the first inventory in secondary and old-growth forests were ... Structural changes in secondary forests are less known in West Africa, and ... temporal succession from one time spatial ..... s = number of species sampled per hectare; S = species richness of the whole forest; NF = the number of taxonomic families,.

  7. Influence of thermodynamically unfavorable secondary structures on DNA hybridization kinetics

    Science.gov (United States)

    Hata, Hiroaki; Kitajima, Tetsuro

    2018-01-01

    Abstract Nucleic acid secondary structure plays an important role in nucleic acid–nucleic acid recognition/hybridization processes, and is also a vital consideration in DNA nanotechnology. Although the influence of stable secondary structures on hybridization kinetics has been characterized, unstable secondary structures, which show positive ΔG° with self-folding, can also form, and their effects have not been systematically investigated. Such thermodynamically unfavorable secondary structures should not be ignored in DNA hybridization kinetics, especially under isothermal conditions. Here, we report that positive ΔG° secondary structures can change the hybridization rate by two-orders of magnitude, despite the fact that their hybridization obeyed second-order reaction kinetics. The temperature dependence of hybridization rates showed non-Arrhenius behavior; thus, their hybridization is considered to be nucleation limited. We derived a model describing how ΔG° positive secondary structures affect hybridization kinetics in stopped-flow experiments with 47 pairs of oligonucleotides. The calculated hybridization rates, which were based on the model, quantitatively agreed with the experimental rate constant. PMID:29220504

  8. Prediction of adolescents doing physical activity after completing secondary education.

    Science.gov (United States)

    Moreno-Murcia, Juan Antonio; Huéscar, Elisa; Cervelló, Eduardo

    2012-03-01

    The purpose of this study, based on the self-determination theory (Ryan & Deci, 2000) was to test the prediction power of student's responsibility, psychological mediators, intrinsic motivation and the importance attached to physical education in the intention to continue to practice some form of physical activity and/or sport, and the possible relationships that exist between these variables. We used a sample of 482 adolescent students in physical education classes, with a mean age of 14.3 years, which were measured for responsibility, psychological mediators, sports motivation, the importance of physical education and intention to be physically active. We completed an analysis of structural equations modelling. The results showed that the responsibility positively predicted psychological mediators, and this predicted intrinsic motivation, which positively predicted the importance students attach to physical education, and this, finally, positively predicted the intention of the student to continue doing sport. Results are discussed in relation to the promotion of student's responsibility towards a greater commitment to the practice of physical exercise.

  9. An image processing approach to computing distances between RNA secondary structures dot plots

    Directory of Open Access Journals (Sweden)

    Sapiro Guillermo

    2009-02-01

    Full Text Available Abstract Background Computing the distance between two RNA secondary structures can contribute in understanding the functional relationship between them. When used repeatedly, such a procedure may lead to finding a query RNA structure of interest in a database of structures. Several methods are available for computing distances between RNAs represented as strings or graphs, but none utilize the RNA representation with dot plots. Since dot plots are essentially digital images, there is a clear motivation to devise an algorithm for computing the distance between dot plots based on image processing methods. Results We have developed a new metric dubbed 'DoPloCompare', which compares two RNA structures. The method is based on comparing dot plot diagrams that represent the secondary structures. When analyzing two diagrams and motivated by image processing, the distance is based on a combination of histogram correlations and a geometrical distance measure. We introduce, describe, and illustrate the procedure by two applications that utilize this metric on RNA sequences. The first application is the RNA design problem, where the goal is to find the nucleotide sequence for a given secondary structure. Examples where our proposed distance measure outperforms others are given. The second application locates peculiar point mutations that induce significant structural alternations relative to the wild type predicted secondary structure. The approach reported in the past to solve this problem was tested on several RNA sequences with known secondary structures to affirm their prediction, as well as on a data set of ribosomal pieces. These pieces were computationally cut from a ribosome for which an experimentally derived secondary structure is available, and on each piece the prediction conveys similarity to the experimental result. Our newly proposed distance measure shows benefit in this problem as well when compared to standard methods used for assessing

  10. Protein secondary structure appears to be robust under in silico evolution while protein disorder appears not to be.

    KAUST Repository

    Schaefer, Christian

    2010-01-16

    MOTIVATION: The mutation of amino acids often impacts protein function and structure. Mutations without negative effect sustain evolutionary pressure. We study a particular aspect of structural robustness with respect to mutations: regular protein secondary structure and natively unstructured (intrinsically disordered) regions. Is the formation of regular secondary structure an intrinsic feature of amino acid sequences, or is it a feature that is lost upon mutation and is maintained by evolution against the odds? Similarly, is disorder an intrinsic sequence feature or is it difficult to maintain? To tackle these questions, we in silico mutated native protein sequences into random sequence-like ensembles and monitored the change in predicted secondary structure and disorder. RESULTS: We established that by our coarse-grained measures for change, predictions and observations were similar, suggesting that our results were not biased by prediction mistakes. Changes in secondary structure and disorder predictions were linearly proportional to the change in sequence. Surprisingly, neither the content nor the length distribution for the predicted secondary structure changed substantially. Regions with long disorder behaved differently in that significantly fewer such regions were predicted after a few mutation steps. Our findings suggest that the formation of regular secondary structure is an intrinsic feature of random amino acid sequences, while the formation of long-disordered regions is not an intrinsic feature of proteins with disordered regions. Put differently, helices and strands appear to be maintained easily by evolution, whereas maintaining disordered regions appears difficult. Neutral mutations with respect to disorder are therefore very unlikely.

  11. Protein secondary structure appears to be robust under in silico evolution while protein disorder appears not to be.

    KAUST Repository

    Schaefer, Christian; Schlessinger, Avner; Rost, Burkhard

    2010-01-01

    MOTIVATION: The mutation of amino acids often impacts protein function and structure. Mutations without negative effect sustain evolutionary pressure. We study a particular aspect of structural robustness with respect to mutations: regular protein secondary structure and natively unstructured (intrinsically disordered) regions. Is the formation of regular secondary structure an intrinsic feature of amino acid sequences, or is it a feature that is lost upon mutation and is maintained by evolution against the odds? Similarly, is disorder an intrinsic sequence feature or is it difficult to maintain? To tackle these questions, we in silico mutated native protein sequences into random sequence-like ensembles and monitored the change in predicted secondary structure and disorder. RESULTS: We established that by our coarse-grained measures for change, predictions and observations were similar, suggesting that our results were not biased by prediction mistakes. Changes in secondary structure and disorder predictions were linearly proportional to the change in sequence. Surprisingly, neither the content nor the length distribution for the predicted secondary structure changed substantially. Regions with long disorder behaved differently in that significantly fewer such regions were predicted after a few mutation steps. Our findings suggest that the formation of regular secondary structure is an intrinsic feature of random amino acid sequences, while the formation of long-disordered regions is not an intrinsic feature of proteins with disordered regions. Put differently, helices and strands appear to be maintained easily by evolution, whereas maintaining disordered regions appears difficult. Neutral mutations with respect to disorder are therefore very unlikely.

  12. PSPP: a protein structure prediction pipeline for computing clusters.

    Directory of Open Access Journals (Sweden)

    Michael S Lee

    2009-07-01

    Full Text Available Protein structures are critical for understanding the mechanisms of biological systems and, subsequently, for drug and vaccine design. Unfortunately, protein sequence data exceed structural data by a factor of more than 200 to 1. This gap can be partially filled by using computational protein structure prediction. While structure prediction Web servers are a notable option, they often restrict the number of sequence queries and/or provide a limited set of prediction methodologies. Therefore, we present a standalone protein structure prediction software package suitable for high-throughput structural genomic applications that performs all three classes of prediction methodologies: comparative modeling, fold recognition, and ab initio. This software can be deployed on a user's own high-performance computing cluster.The pipeline consists of a Perl core that integrates more than 20 individual software packages and databases, most of which are freely available from other research laboratories. The query protein sequences are first divided into domains either by domain boundary recognition or Bayesian statistics. The structures of the individual domains are then predicted using template-based modeling or ab initio modeling. The predicted models are scored with a statistical potential and an all-atom force field. The top-scoring ab initio models are annotated by structural comparison against the Structural Classification of Proteins (SCOP fold database. Furthermore, secondary structure, solvent accessibility, transmembrane helices, and structural disorder are predicted. The results are generated in text, tab-delimited, and hypertext markup language (HTML formats. So far, the pipeline has been used to study viral and bacterial proteomes.The standalone pipeline that we introduce here, unlike protein structure prediction Web servers, allows users to devote their own computing assets to process a potentially unlimited number of queries as well as perform

  13. RNA secondary structure diagrams for very large molecules: RNAfdl

    DEFF Research Database (Denmark)

    Hecker, Nikolai; Wiegels, Tim; Torda, Andrew E.

    2013-01-01

    There are many programs that can read the secondary structure of an RNA molecule and draw a diagram, but hardly any that can cope with 10 3 bases. RNAfdl is slow but capable of producing intersection-free diagrams for ribosome-sized structures, has a graphical user interface for adjustments...

  14. A possible contribution of mRNA secondary structure to translation initiation efficiency in Lactococcus lactis

    NARCIS (Netherlands)

    Guchte, Maarten van de; Lende, Ted van der; Kok, Jan; Venema, Gerard

    1991-01-01

    Gene expression signals derived from Lactococcus lactis were linked to lacZ-fused genes with different 5'-nucleotide sequences. Computer predictions of mRNA secondary structure were combined with lacZ expression studies to direct base-substitutions that could possibly influence gene expression.

  15. Nuclear fuel assembly incorporating primary and secondary structural support members

    International Nuclear Information System (INIS)

    Carlson, W.R.; Gjertsen, R.K.; Miller, J.V.

    1987-01-01

    A nuclear fuel assembly, comprising: (a) an upper end structure; (b) a lower end structure; (c) elongated primary structural members extending longitudinally between and rigidly interconnecting the upper and lower end structures, the upper and lower end structures and primary structural members together forming a rigid structural skeleton of the fuel assembly; (d) transverse grids supported on the primary structural members at axially spaced locations therealong between the upper and lower end structures; (e) fuel rods extending through and supported by the grids between the upper and lower end structures so as to extend in generally side-by-side spaced relation to one another and to the primary structural members; and (f) elongated secondary structural members extending longitudinally between but unconnected with the upper and lower end structures, the secondary structural members extending through and rigidly interconnected with the grids to extend in generally side-by-side spaced relation to one another, to the fuel rods and to the primary structural members so as to bolster the stiffness of the structural skeleton of the fuel assembly

  16. RNA secondary structure image - fRNAdb | LSDB Archive [Life Science Database Archive metadata

    Lifescience Database Archive (English)

    Full Text Available List Contact us fRNAdb RNA secondary structure image Data detail Data name RNA secondary structure image DOI... 10.18908/lsdba.nbdc00452-005 Description of data contents RNA secondary structure images - png.zip: RNA secondary structure image...s (PNG) - pdf.zip: RNA secondary structure images (PDF) - thumbnail.zip: Thumbnails of... RNA secondary structure images Data file File name: RNA_secondary_structure_image... File URL: ftp://ftp.biosciencedbc.jp/archive/frnadb/LATEST/RNA_secondary_structure_image File size: 9.6 GB

  17. Thermodynamic heuristics with case-based reasoning: combined insights for RNA pseudoknot secondary structure.

    Science.gov (United States)

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

    2011-08-01

    The secondary structure of RNA pseudoknots has been extensively inferred and scrutinized by computational approaches. Experimental methods for determining RNA structure are time consuming and tedious; therefore, predictive computational approaches are required. Predicting the most accurate and energy-stable pseudoknot RNA secondary structure has been proven to be an NP-hard problem. In this paper, a new RNA folding approach, termed MSeeker, is presented; it includes KnotSeeker (a heuristic method) and Mfold (a thermodynamic algorithm). The global optimization of this thermodynamic heuristic approach was further enhanced by using a case-based reasoning technique as a local optimization method. MSeeker is a proposed algorithm for predicting RNA pseudoknot structure from individual sequences, especially long ones. This research demonstrates that MSeeker improves the sensitivity and specificity of existing RNA pseudoknot structure predictions. The performance and structural results from this proposed method were evaluated against seven other state-of-the-art pseudoknot prediction methods. The MSeeker method had better sensitivity than the DotKnot, FlexStem, HotKnots, pknotsRG, ILM, NUPACK and pknotsRE methods, with 79% of the predicted pseudoknot base-pairs being correct.

  18. Approaches to link RNA secondary structures with splicing regulation

    DEFF Research Database (Denmark)

    Plass, Mireya; Eyras, Eduardo

    2014-01-01

    In higher eukaryotes, alternative splicing is usually regulated by protein factors, which bind to the pre-mRNA and affect the recognition of splicing signals. There is recent evidence that the secondary structure of the pre-mRNA may also play an important role in this process, either by facilitat...... describes the steps in the analysis of the secondary structure of the pre-mRNA and its possible relation to splicing. As a working example, we use the case of yeast and the problem of the recognition of the 3' splice site (3'ss).......In higher eukaryotes, alternative splicing is usually regulated by protein factors, which bind to the pre-mRNA and affect the recognition of splicing signals. There is recent evidence that the secondary structure of the pre-mRNA may also play an important role in this process, either...

  19. Correlation of RNA secondary structure statistics with thermodynamic stability and applications to folding.

    Science.gov (United States)

    Wu, Johnny C; Gardner, David P; Ozer, Stuart; Gutell, Robin R; Ren, Pengyu

    2009-08-28

    The accurate prediction of the secondary and tertiary structure of an RNA with different folding algorithms is dependent on several factors, including the energy functions. However, an RNA higher-order structure cannot be predicted accurately from its sequence based on a limited set of energy parameters. The inter- and intramolecular forces between this RNA and other small molecules and macromolecules, in addition to other factors in the cell such as pH, ionic strength, and temperature, influence the complex dynamics associated with transition of a single stranded RNA to its secondary and tertiary structure. Since all of the factors that affect the formation of an RNAs 3D structure cannot be determined experimentally, statistically derived potential energy has been used in the prediction of protein structure. In the current work, we evaluate the statistical free energy of various secondary structure motifs, including base-pair stacks, hairpin loops, and internal loops, using their statistical frequency obtained from the comparative analysis of more than 50,000 RNA sequences stored in the RNA Comparative Analysis Database (rCAD) at the Comparative RNA Web (CRW) Site. Statistical energy was computed from the structural statistics for several datasets. While the statistical energy for a base-pair stack correlates with experimentally derived free energy values, suggesting a Boltzmann-like distribution, variation is observed between different molecules and their location on the phylogenetic tree of life. Our statistical energy values calculated for several structural elements were utilized in the Mfold RNA-folding algorithm. The combined statistical energy values for base-pair stacks, hairpins and internal loop flanks result in a significant improvement in the accuracy of secondary structure prediction; the hairpin flanks contribute the most.

  20. Prediction of primary vs secondary hypertension in children.

    Science.gov (United States)

    Baracco, Rossana; Kapur, Gaurav; Mattoo, Tej; Jain, Amrish; Valentini, Rudolph; Ahmed, Maheen; Thomas, Ronald

    2012-05-01

    Despite current guidelines, variability exists in the workup of hypertensive children due to physician preferences. The study evaluates primary vs secondary hypertension diagnosis from investigations routinely performed in hypertensive children. This retrospective study included children 5 to 19 years with primary and secondary hypertension. The proportions of abnormal laboratory and imaging tests were compared between primary and secondary hypertension groups. Risk factors for primary vs secondary hypertension were evaluated by logistic regression and likelihood function analysis. Patients with secondary hypertension were younger (5-12 years) and had a higher proportion of abnormal creatinine, renal ultrasound, and echocardiogram findings. There was no significant difference in abnormal results of thyroid function, urine catecholamines, plasma renin, and aldosterone. Abnormal renal ultrasound findings and age were predictors of secondary hypertension by regression and likelihood function analysis. Children aged 5 to 12 years with abnormal renal ultrasound findings and high diastolic blood pressures are at higher risk for secondary hypertension that requires detailed evaluation. © 2012 Wiley Periodicals, Inc.

  1. General enumeration of RNA secondary structures based on new ...

    African Journals Online (AJOL)

    Crick base pairs between AU and GC. Based on the new representation, this paper also computes the number of various types of constrained secondary structures taking the minimum stack length 1 and minimum size m for each bonding loop as ...

  2. A combinatorial enumeration problem of RNA secondary structures

    African Journals Online (AJOL)

    use

    2011-12-21

    Dec 21, 2011 ... connection between Discrete Mathematics and Compu- tational Molecular Biology (Chen et al, 2005; Hofacker et ... in Computational Molecular Biology. An RNA molecule is described by its sequences of bases ... Here, a mathematical definition of secondary structure is given (Stein and Waterman 1978).

  3. A combinatorial enumeration problem of RNA secondary structures

    African Journals Online (AJOL)

    use

    2011-12-21

    Dec 21, 2011 ... interesting combinatorial questions (Chen et al., 2005;. Liu, 2006; Schmitt and Waterman 1994; Stein and. Waterman 1978). The research on the enumeration of. RNA secondary structures becomes one of the hot topics in Computational Molecular Biology. An RNA molecule is described by its sequences of.

  4. Quantitative DMS mapping for automated RNA secondary structure inference

    OpenAIRE

    Cordero, Pablo; Kladwang, Wipapat; VanLang, Christopher C.; Das, Rhiju

    2012-01-01

    For decades, dimethyl sulfate (DMS) mapping has informed manual modeling of RNA structure in vitro and in vivo. Here, we incorporate DMS data into automated secondary structure inference using a pseudo-energy framework developed for 2'-OH acylation (SHAPE) mapping. On six non-coding RNAs with crystallographic models, DMS- guided modeling achieves overall false negative and false discovery rates of 9.5% and 11.6%, comparable or better than SHAPE-guided modeling; and non-parametric bootstrappin...

  5. Applications of contact predictions to structural biology

    Directory of Open Access Journals (Sweden)

    Felix Simkovic

    2017-05-01

    Full Text Available Evolutionary pressure on residue interactions, intramolecular or intermolecular, that are important for protein structure or function can lead to covariance between the two positions. Recent methodological advances allow much more accurate contact predictions to be derived from this evolutionary covariance signal. The practical application of contact predictions has largely been confined to structural bioinformatics, yet, as this work seeks to demonstrate, the data can be of enormous value to the structural biologist working in X-ray crystallography, cryo-EM or NMR. Integrative structural bioinformatics packages such as Rosetta can already exploit contact predictions in a variety of ways. The contribution of contact predictions begins at construct design, where structural domains may need to be expressed separately and contact predictions can help to predict domain limits. Structure solution by molecular replacement (MR benefits from contact predictions in diverse ways: in difficult cases, more accurate search models can be constructed using ab initio modelling when predictions are available, while intermolecular contact predictions can allow the construction of larger, oligomeric search models. Furthermore, MR using supersecondary motifs or large-scale screens against the PDB can exploit information, such as the parallel or antiparallel nature of any β-strand pairing in the target, that can be inferred from contact predictions. Contact information will be particularly valuable in the determination of lower resolution structures by helping to assign sequence register. In large complexes, contact information may allow the identity of a protein responsible for a certain region of density to be determined and then assist in the orientation of an available model within that density. In NMR, predicted contacts can provide long-range information to extend the upper size limit of the technique in a manner analogous but complementary to experimental

  6. Exact calculation of loop formation probability identifies folding motifs in RNA secondary structures

    Science.gov (United States)

    Sloma, Michael F.; Mathews, David H.

    2016-01-01

    RNA secondary structure prediction is widely used to analyze RNA sequences. In an RNA partition function calculation, free energy nearest neighbor parameters are used in a dynamic programming algorithm to estimate statistical properties of the secondary structure ensemble. Previously, partition functions have largely been used to estimate the probability that a given pair of nucleotides form a base pair, the conditional stacking probability, the accessibility to binding of a continuous stretch of nucleotides, or a representative sample of RNA structures. Here it is demonstrated that an RNA partition function can also be used to calculate the exact probability of formation of hairpin loops, internal loops, bulge loops, or multibranch loops at a given position. This calculation can also be used to estimate the probability of formation of specific helices. Benchmarking on a set of RNA sequences with known secondary structures indicated that loops that were calculated to be more probable were more likely to be present in the known structure than less probable loops. Furthermore, highly probable loops are more likely to be in the known structure than the set of loops predicted in the lowest free energy structures. PMID:27852924

  7. A Reference Database for Circular Dichroism Spectroscopy Covering Fold and Secondary Structure Space

    International Nuclear Information System (INIS)

    Lees, J.; Miles, A.; Wien, F.; Wallace, B.

    2006-01-01

    Circular Dichroism (CD) spectroscopy is a long-established technique for studying protein secondary structures in solution. Empirical analyses of CD data rely on the availability of reference datasets comprised of far-UV CD spectra of proteins whose crystal structures have been determined. This article reports on the creation of a new reference dataset which effectively covers both secondary structure and fold space, and uses the higher information content available in synchrotron radiation circular dichroism (SRCD) spectra to more accurately predict secondary structure than has been possible with existing reference datasets. It also examines the effects of wavelength range, structural redundancy and different means of categorizing secondary structures on the accuracy of the analyses. In addition, it describes a novel use of hierarchical cluster analyses to identify protein relatedness based on spectral properties alone. The databases are shown to be applicable in both conventional CD and SRCD spectroscopic analyses of proteins. Hence, by combining new bioinformatics and biophysical methods, a database has been produced that should have wide applicability as a tool for structural molecular biology

  8. SeMPI: a genome-based secondary metabolite prediction and identification web server.

    Science.gov (United States)

    Zierep, Paul F; Padilla, Natàlia; Yonchev, Dimitar G; Telukunta, Kiran K; Klementz, Dennis; Günther, Stefan

    2017-07-03

    The secondary metabolism of bacteria, fungi and plants yields a vast number of bioactive substances. The constantly increasing amount of published genomic data provides the opportunity for an efficient identification of gene clusters by genome mining. Conversely, for many natural products with resolved structures, the encoding gene clusters have not been identified yet. Even though genome mining tools have become significantly more efficient in the identification of biosynthetic gene clusters, structural elucidation of the actual secondary metabolite is still challenging, especially due to as yet unpredictable post-modifications. Here, we introduce SeMPI, a web server providing a prediction and identification pipeline for natural products synthesized by polyketide synthases of type I modular. In order to limit the possible structures of PKS products and to include putative tailoring reactions, a structural comparison with annotated natural products was introduced. Furthermore, a benchmark was designed based on 40 gene clusters with annotated PKS products. The web server of the pipeline (SeMPI) is freely available at: http://www.pharmaceutical-bioinformatics.de/sempi. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

  9. Protein energetic conformational analysis from NMR chemical shifts (PECAN) and its use in determining secondary structural elements

    Energy Technology Data Exchange (ETDEWEB)

    Eghbalnia, Hamid R.; Wang Liya; Bahrami, Arash [National Magnetic Resonance Facility at Madison, Biochemistry Department (United States); Assadi, Amir [University of Wisconsin-Madison, Mathematics Department (United States); Markley, John L. [National Magnetic Resonance Facility at Madison, Biochemistry Department (United States)], E-mail: eghbalni@nmrfam.wisc.edu

    2005-05-15

    We present an energy model that combines information from the amino acid sequence of a protein and available NMR chemical shifts for the purposes of identifying low energy conformations and determining elements of secondary structure. The model ('PECAN', Protein Energetic Conformational Analysis from NMR chemical shifts) optimizes a combination of sequence information and residue-specific statistical energy function to yield energetic descriptions most favorable to predicting secondary structure. Compared to prior methods for secondary structure determination, PECAN provides increased accuracy and range, particularly in regions of extended structure. Moreover, PECAN uses the energetics to identify residues located at the boundaries between regions of predicted secondary structure that may not fit the stringent secondary structure class definitions. The energy model offers insights into the local energetic patterns that underlie conformational preferences. For example, it shows that the information content for defining secondary structure is localized about a residue and reaches a maximum when two residues on either side are considered. The current release of the PECAN software determines the well-defined regions of secondary structure in novel proteins with assigned chemical shifts with an overall accuracy of 90%, which is close to the practical limit of achievable accuracy in classifying the states.

  10. Protein energetic conformational analysis from NMR chemical shifts (PECAN) and its use in determining secondary structural elements

    International Nuclear Information System (INIS)

    Eghbalnia, Hamid R.; Wang Liya; Bahrami, Arash; Assadi, Amir; Markley, John L.

    2005-01-01

    We present an energy model that combines information from the amino acid sequence of a protein and available NMR chemical shifts for the purposes of identifying low energy conformations and determining elements of secondary structure. The model ('PECAN', Protein Energetic Conformational Analysis from NMR chemical shifts) optimizes a combination of sequence information and residue-specific statistical energy function to yield energetic descriptions most favorable to predicting secondary structure. Compared to prior methods for secondary structure determination, PECAN provides increased accuracy and range, particularly in regions of extended structure. Moreover, PECAN uses the energetics to identify residues located at the boundaries between regions of predicted secondary structure that may not fit the stringent secondary structure class definitions. The energy model offers insights into the local energetic patterns that underlie conformational preferences. For example, it shows that the information content for defining secondary structure is localized about a residue and reaches a maximum when two residues on either side are considered. The current release of the PECAN software determines the well-defined regions of secondary structure in novel proteins with assigned chemical shifts with an overall accuracy of 90%, which is close to the practical limit of achievable accuracy in classifying the states

  11. Accurate prediction of secondary metabolite gene clusters in filamentous fungi

    DEFF Research Database (Denmark)

    Andersen, Mikael Rørdam; Nielsen, Jakob Blæsbjerg; Klitgaard, Andreas

    2013-01-01

    Biosynthetic pathways of secondary metabolites from fungi are currently subject to an intense effort to elucidate the genetic basis for these compounds due to their large potential within pharmaceutics and synthetic biochemistry. The preferred method is methodical gene deletions to identify...... used A. nidulans for our method development and validation due to the wealth of available biochemical data, but the method can be applied to any fungus with a sequenced and assembled genome, thus supporting further secondary metabolite pathway elucidation in the fungal kingdom....

  12. TurboFold: Iterative probabilistic estimation of secondary structures for multiple RNA sequences

    Directory of Open Access Journals (Sweden)

    Sharma Gaurav

    2011-04-01

    Full Text Available Abstract Background The prediction of secondary structure, i.e. the set of canonical base pairs between nucleotides, is a first step in developing an understanding of the function of an RNA sequence. The most accurate computational methods predict conserved structures for a set of homologous RNA sequences. These methods usually suffer from high computational complexity. In this paper, TurboFold, a novel and efficient method for secondary structure prediction for multiple RNA sequences, is presented. Results TurboFold takes, as input, a set of homologous RNA sequences and outputs estimates of the base pairing probabilities for each sequence. The base pairing probabilities for a sequence are estimated by combining intrinsic information, derived from the sequence itself via the nearest neighbor thermodynamic model, with extrinsic information, derived from the other sequences in the input set. For a given sequence, the extrinsic information is computed by using pairwise-sequence-alignment-based probabilities for co-incidence with each of the other sequences, along with estimated base pairing probabilities, from the previous iteration, for the other sequences. The extrinsic information is introduced as free energy modifications for base pairing in a partition function computation based on the nearest neighbor thermodynamic model. This process yields updated estimates of base pairing probability. The updated base pairing probabilities in turn are used to recompute extrinsic information, resulting in the overall iterative estimation procedure that defines TurboFold. TurboFold is benchmarked on a number of ncRNA datasets and compared against alternative secondary structure prediction methods. The iterative procedure in TurboFold is shown to improve estimates of base pairing probability with each iteration, though only small gains are obtained beyond three iterations. Secondary structures composed of base pairs with estimated probabilities higher than a

  13. A phase transition in energy-filtered RNA secondary structures

    DEFF Research Database (Denmark)

    Han, Hillary Siwei; reidys, Christian

    2012-01-01

    In this paper we study the effect of energy parameters on minimum free energy (mfe) RNA secondary structures. Employing a simplified combinatorial energy model, that is only dependent on the diagram representation and that is not sequence specific, we prove the following dichotomy result. Mfe...... this phase transition from a discrete limit to a central limit distribution and subsequently put our result into the context of quantifying the effect of sparsification of the folding of these respective mfe-structures. We show that the sparsification of realistic mfe-structures leads to a constant time...

  14. RNAmutants: a web server to explore the mutational landscape of RNA secondary structures

    Science.gov (United States)

    Waldispühl, Jerome; Devadas, Srinivas; Berger, Bonnie; Clote, Peter

    2009-01-01

    The history and mechanism of molecular evolution in DNA have been greatly elucidated by contributions from genetics, probability theory and bioinformatics—indeed, mathematical developments such as Kimura's neutral theory, Kingman's coalescent theory and efficient software such as BLAST, ClustalW, Phylip, etc., provide the foundation for modern population genetics. In contrast to DNA, the function of most noncoding RNA depends on tertiary structure, experimentally known to be largely determined by secondary structure, for which dynamic programming can efficiently compute the minimum free energy secondary structure. For this reason, understanding the effect of pointwise mutations in RNA secondary structure could reveal fundamental properties of structural RNA molecules and improve our understanding of molecular evolution of RNA. The web server RNAmutants provides several efficient tools to compute the ensemble of low-energy secondary structures for all k-mutants of a given RNA sequence, where k is bounded by a user-specified upper bound. As we have previously shown, these tools can be used to predict putative deleterious mutations and to analyze regulatory sequences from the hepatitis C and human immunodeficiency genomes. Web server is available at http://bioinformatics.bc.edu/clotelab/RNAmutants/, and downloadable binaries at http://rnamutants.csail.mit.edu/. PMID:19531740

  15. Web-Beagle: a web server for the alignment of RNA secondary structures.

    Science.gov (United States)

    Mattei, Eugenio; Pietrosanto, Marco; Ferrè, Fabrizio; Helmer-Citterich, Manuela

    2015-07-01

    Web-Beagle (http://beagle.bio.uniroma2.it) is a web server for the pairwise global or local alignment of RNA secondary structures. The server exploits a new encoding for RNA secondary structure and a substitution matrix of RNA structural elements to perform RNA structural alignments. The web server allows the user to compute up to 10 000 alignments in a single run, taking as input sets of RNA sequences and structures or primary sequences alone. In the latter case, the server computes the secondary structure prediction for the RNAs on-the-fly using RNAfold (free energy minimization). The user can also compare a set of input RNAs to one of five pre-compiled RNA datasets including lncRNAs and 3' UTRs. All types of comparison produce in output the pairwise alignments along with structural similarity and statistical significance measures for each resulting alignment. A graphical color-coded representation of the alignments allows the user to easily identify structural similarities between RNAs. Web-Beagle can be used for finding structurally related regions in two or more RNAs, for the identification of homologous regions or for functional annotation. Benchmark tests show that Web-Beagle has lower computational complexity, running time and better performances than other available methods. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

  16. Computational predictions of zinc oxide hollow structures

    Science.gov (United States)

    Tuoc, Vu Ngoc; Huan, Tran Doan; Thao, Nguyen Thi

    2018-03-01

    Nanoporous materials are emerging as potential candidates for a wide range of technological applications in environment, electronic, and optoelectronics, to name just a few. Within this active research area, experimental works are predominant while theoretical/computational prediction and study of these materials face some intrinsic challenges, one of them is how to predict porous structures. We propose a computationally and technically feasible approach for predicting zinc oxide structures with hollows at the nano scale. The designed zinc oxide hollow structures are studied with computations using the density functional tight binding and conventional density functional theory methods, revealing a variety of promising mechanical and electronic properties, which can potentially find future realistic applications.

  17. RNA secondary structures of the bacteriophage phi6 packaging regions.

    OpenAIRE

    Pirttimaa, M J; Bamford, D H

    2000-01-01

    Bacteriophage phi6 genome consists of three segments of double-stranded RNA. During maturation, single-stranded copies of these segments are packaged into preformed polymerase complex particles. Only phi6 RNA is packaged, and each particle contains only one copy of each segment. An in vitro packaging and replication assay has been developed for phi6, and the packaging signals (pac sites) have been mapped to the 5' ends of the RNA segments. In this study, we propose secondary structure models ...

  18. Cloud prediction of protein structure and function with PredictProtein for Debian.

    Science.gov (United States)

    Kaján, László; Yachdav, Guy; Vicedo, Esmeralda; Steinegger, Martin; Mirdita, Milot; Angermüller, Christof; Böhm, Ariane; Domke, Simon; Ertl, Julia; Mertes, Christian; Reisinger, Eva; Staniewski, Cedric; Rost, Burkhard

    2013-01-01

    We report the release of PredictProtein for the Debian operating system and derivatives, such as Ubuntu, Bio-Linux, and Cloud BioLinux. The PredictProtein suite is available as a standard set of open source Debian packages. The release covers the most popular prediction methods from the Rost Lab, including methods for the prediction of secondary structure and solvent accessibility (profphd), nuclear localization signals (predictnls), and intrinsically disordered regions (norsnet). We also present two case studies that successfully utilize PredictProtein packages for high performance computing in the cloud: the first analyzes protein disorder for whole organisms, and the second analyzes the effect of all possible single sequence variants in protein coding regions of the human genome.

  19. Structure of the spin polarization spectrum of secondary electrons emitted from nickel

    International Nuclear Information System (INIS)

    Helman, J.S.

    1985-01-01

    The main features of the structure observed in the energy resolved spin polarization of secondary electrons emitted from Ni are interpreted in terms of surface and bulk plasmon assisted emission. The model also predicts a measureable shift of the main polarization peak of about 0.3 eV to lower energies as the temperature is raised from room temperature to closely below the Curie temperature. (Author) [pt

  20. Stochastic Extreme Load Predictions for Marine Structures

    DEFF Research Database (Denmark)

    Jensen, Jørgen Juncher

    1999-01-01

    Development of rational design criteria for marine structures requires reliable estimates for the maximum wave-induced loads the structure may encounter during its operational lifetime. The paper discusses various methods for extreme value predictions taking into account the non-linearity of the ......Development of rational design criteria for marine structures requires reliable estimates for the maximum wave-induced loads the structure may encounter during its operational lifetime. The paper discusses various methods for extreme value predictions taking into account the non......-linearity of the waves and the response. As example the wave-induced bending moment in the ship hull girder is considered....

  1. Computational RNA secondary structure design: empirical complexity and improved methods

    Directory of Open Access Journals (Sweden)

    Condon Anne

    2007-01-01

    Full Text Available Abstract Background We investigate the empirical complexity of the RNA secondary structure design problem, that is, the scaling of the typical difficulty of the design task for various classes of RNA structures as the size of the target structure is increased. The purpose of this work is to understand better the factors that make RNA structures hard to design for existing, high-performance algorithms. Such understanding provides the basis for improving the performance of one of the best algorithms for this problem, RNA-SSD, and for characterising its limitations. Results To gain insights into the practical complexity of the problem, we present a scaling analysis on random and biologically motivated structures using an improved version of the RNA-SSD algorithm, and also the RNAinverse algorithm from the Vienna package. Since primary structure constraints are relevant for designing RNA structures, we also investigate the correlation between the number and the location of the primary structure constraints when designing structures and the performance of the RNA-SSD algorithm. The scaling analysis on random and biologically motivated structures supports the hypothesis that the running time of both algorithms scales polynomially with the size of the structure. We also found that the algorithms are in general faster when constraints are placed only on paired bases in the structure. Furthermore, we prove that, according to the standard thermodynamic model, for some structures that the RNA-SSD algorithm was unable to design, there exists no sequence whose minimum free energy structure is the target structure. Conclusion Our analysis helps to better understand the strengths and limitations of both the RNA-SSD and RNAinverse algorithms, and suggests ways in which the performance of these algorithms can be further improved.

  2. Global Analysis of RNA Secondary Structure in Two Metazoans

    Directory of Open Access Journals (Sweden)

    Fan Li

    2012-01-01

    Full Text Available The secondary structure of RNA is necessary for its maturation, regulation, processing, and function. However, the global influence of RNA folding in eukaryotes is still unclear. Here, we use a high-throughput, sequencing-based, structure-mapping approach to identify the paired (double-stranded RNA [dsRNA] and unpaired (single-stranded RNA [ssRNA] components of the Drosophila melanogaster and Caenorhabditis elegans transcriptomes, which allows us to identify conserved features of RNA secondary structure in metazoans. From this analysis, we find that ssRNAs and dsRNAs are significantly correlated with specific epigenetic modifications. Additionally, we find key structural patterns across protein-coding transcripts that indicate that RNA folding demarcates regions of protein translation and likely affects microRNA-mediated regulation of mRNAs in animals. Finally, we identify and characterize 546 mRNAs whose folding pattern is significantly correlated between these metazoans, suggesting that their structure has some function. Overall, our findings provide a global assessment of RNA folding in animals.

  3. In vivo genome-wide profiling of RNA secondary structure reveals novel regulatory features.

    Science.gov (United States)

    Ding, Yiliang; Tang, Yin; Kwok, Chun Kit; Zhang, Yu; Bevilacqua, Philip C; Assmann, Sarah M

    2014-01-30

    RNA structure has critical roles in processes ranging from ligand sensing to the regulation of translation, polyadenylation and splicing. However, a lack of genome-wide in vivo RNA structural data has limited our understanding of how RNA structure regulates gene expression in living cells. Here we present a high-throughput, genome-wide in vivo RNA structure probing method, structure-seq, in which dimethyl sulphate methylation of unprotected adenines and cytosines is identified by next-generation sequencing. Application of this method to Arabidopsis thaliana seedlings yielded the first in vivo genome-wide RNA structure map at nucleotide resolution for any organism, with quantitative structural information across more than 10,000 transcripts. Our analysis reveals a three-nucleotide periodic repeat pattern in the structure of coding regions, as well as a less-structured region immediately upstream of the start codon, and shows that these features are strongly correlated with translation efficiency. We also find patterns of strong and weak secondary structure at sites of alternative polyadenylation, as well as strong secondary structure at 5' splice sites that correlates with unspliced events. Notably, in vivo structures of messenger RNAs annotated for stress responses are poorly predicted in silico, whereas mRNA structures of genes related to cell function maintenance are well predicted. Global comparison of several structural features between these two categories shows that the mRNAs associated with stress responses tend to have more single-strandedness, longer maximal loop length and higher free energy per nucleotide, features that may allow these RNAs to undergo conformational changes in response to environmental conditions. Structure-seq allows the RNA structurome and its biological roles to be interrogated on a genome-wide scale and should be applicable to any organism.

  4. The trickle-down effect of predictability: Secondary task performance benefits from predictability in the primary task.

    Directory of Open Access Journals (Sweden)

    Magdalena Ewa Król

    Full Text Available Predictions optimize processing by reducing attentional resources allocation to expected or predictable sensory data. Our study demonstrates that these saved processing resources can be then used on concurrent stimuli, and in consequence improve their processing and encoding. We illustrate this "trickle-down" effect with a dual task, where the primary task varied in terms of predictability. The primary task involved detection of a pre-specified symbol that appeared at some point of a short video of a dot moving along a random, semi-predictable or predictable trajectory. The concurrent secondary task involved memorization of photographs representing either emotionally neutral or non-neutral (social or threatening content. Performance in the secondary task was measured by a memory test. We found that participants allocated more attention to unpredictable (random and semi-predictable stimuli than to predictable stimuli. Additionally, when the stimuli in the primary task were more predictable, participants performed better in the secondary task, as evidenced by higher sensitivity in the memory test. Finally, social or threatening stimuli were allocated more "looking time" and a larger number of saccades than neutral stimuli. This effect was stronger for the threatening stimuli than social stimuli. Thus, predictability of environmental input is used in optimizing the allocation of attentional resources, which trickles-down and benefits the processing of concurrent stimuli.

  5. The trickle-down effect of predictability: Secondary task performance benefits from predictability in the primary task.

    Science.gov (United States)

    Król, Magdalena Ewa; Król, Michał

    2017-01-01

    Predictions optimize processing by reducing attentional resources allocation to expected or predictable sensory data. Our study demonstrates that these saved processing resources can be then used on concurrent stimuli, and in consequence improve their processing and encoding. We illustrate this "trickle-down" effect with a dual task, where the primary task varied in terms of predictability. The primary task involved detection of a pre-specified symbol that appeared at some point of a short video of a dot moving along a random, semi-predictable or predictable trajectory. The concurrent secondary task involved memorization of photographs representing either emotionally neutral or non-neutral (social or threatening) content. Performance in the secondary task was measured by a memory test. We found that participants allocated more attention to unpredictable (random and semi-predictable) stimuli than to predictable stimuli. Additionally, when the stimuli in the primary task were more predictable, participants performed better in the secondary task, as evidenced by higher sensitivity in the memory test. Finally, social or threatening stimuli were allocated more "looking time" and a larger number of saccades than neutral stimuli. This effect was stronger for the threatening stimuli than social stimuli. Thus, predictability of environmental input is used in optimizing the allocation of attentional resources, which trickles-down and benefits the processing of concurrent stimuli.

  6. Softwood sawlog secondary transport travel speed prediction for the ...

    African Journals Online (AJOL)

    The objective of this study was to develop a predictive model for travel speed of softwood sawlog timber transport (STT) vehicles over a range of forest and provincial roads of varying condition for the South African forestry industry. Data was accumulated from both the Eastern Cape/KwaZulu-Natal and Mpumalanga forest ...

  7. RNA secondary structures of the bacteriophage phi6 packaging regions.

    Science.gov (United States)

    Pirttimaa, M J; Bamford, D H

    2000-06-01

    Bacteriophage phi6 genome consists of three segments of double-stranded RNA. During maturation, single-stranded copies of these segments are packaged into preformed polymerase complex particles. Only phi6 RNA is packaged, and each particle contains only one copy of each segment. An in vitro packaging and replication assay has been developed for phi6, and the packaging signals (pac sites) have been mapped to the 5' ends of the RNA segments. In this study, we propose secondary structure models for the pac sites of phi6 single-stranded RNA segments. Our models accommodate data from structure-specific chemical modifications, free energy minimizations, and phylogenetic comparisons. Previously reported pac site deletion studies are also discussed. Each pac site possesses a unique architecture, that, however, contains common structural elements.

  8. Changes in secondary structure of poliovirus ribonucleic acid

    International Nuclear Information System (INIS)

    Koza, J.

    1975-01-01

    Infectious single-stranded RNA isolated from mature purified poliovirus was separated into three fractions by means of chromatography on an ''evaporated'' calcium phosphate column. RNA molecules with a higher degree of secondary structure were detected in two of the fractions as a result of the chromatography. These RNA molecules (1) were resistant to hydrolysis by pancreatic ribonuclease A, (2) retained unchanged the original infectivity for actinomycin D-pretreated cells, (3) were resistant to ultraviolet-light inactivation and (4) were partially resistant to formaldehyde inactivation

  9. On infrared spectroscopic analysis of transfer RNA secondary structure

    Energy Technology Data Exchange (ETDEWEB)

    Semenov, M A; Starikov, E B

    1987-07-14

    Various techniques of IR spectroscopy in the 1550-1750 cm/sup -1/ region employed to analyse the tRNA secondary structure are discussed and a novel improved method is proposed. The main novel features of this method are the approximation of tRNA helical region spectra by catalogue carbonyl absorption bands and approximation of tRNA nonhelical region spectra by those of homopolyribonucleotides. The IR spectra of tRNA/sub yeast//sup phe/ and tRNA/sub E.coli//sup fmet/ in the carbonyl vibration region are explained on the basis of calculated transition moment coupling.

  10. DNA secondary structures: stability and function of G-quadruplex structures

    Science.gov (United States)

    Bochman, Matthew L.; Paeschke, Katrin; Zakian, Virginia A.

    2013-01-01

    In addition to the canonical double helix, DNA can fold into various other inter- and intramolecular secondary structures. Although many such structures were long thought to be in vitro artefacts, bioinformatics demonstrates that DNA sequences capable of forming these structures are conserved throughout evolution, suggesting the existence of non-B-form DNA in vivo. In addition, genes whose products promote formation or resolution of these structures are found in diverse organisms, and a growing body of work suggests that the resolution of DNA secondary structures is critical for genome integrity. This Review focuses on emerging evidence relating to the characteristics of G-quadruplex structures and the possible influence of such structures on genomic stability and cellular processes, such as transcription. PMID:23032257

  11. Secondary structural entropy in RNA switch (Riboswitch) identification.

    Science.gov (United States)

    Manzourolajdad, Amirhossein; Arnold, Jonathan

    2015-04-28

    RNA regulatory elements play a significant role in gene regulation. Riboswitches, a widespread group of regulatory RNAs, are vital components of many bacterial genomes. These regulatory elements generally function by forming a ligand-induced alternative fold that controls access to ribosome binding sites or other regulatory sites in RNA. Riboswitch-mediated mechanisms are ubiquitous across bacterial genomes. A typical class of riboswitch has its own unique structural and biological complexity, making de novo riboswitch identification a formidable task. Traditionally, riboswitches have been identified through comparative genomics based on sequence and structural homology. The limitations of structural-homology-based approaches, coupled with the assumption that there is a great diversity of undiscovered riboswitches, suggests the need for alternative methods for riboswitch identification, possibly based on features intrinsic to their structure. As of yet, no such reliable method has been proposed. We used structural entropy of riboswitch sequences as a measure of their secondary structural dynamics. Entropy values of a diverse set of riboswitches were compared to that of their mutants, their dinucleotide shuffles, and their reverse complement sequences under different stochastic context-free grammar folding models. Significance of our results was evaluated by comparison to other approaches, such as the base-pairing entropy and energy landscapes dynamics. Classifiers based on structural entropy optimized via sequence and structural features were devised as riboswitch identifiers and tested on Bacillus subtilis, Escherichia coli, and Synechococcus elongatus as an exploration of structural entropy based approaches. The unusually long untranslated region of the cotH in Bacillus subtilis, as well as upstream regions of certain genes, such as the sucC genes were associated with significant structural entropy values in genome-wide examinations. Various tests show that there

  12. Prediction of macroscopic and local stress-strain behaviors of perforated plates under primary and secondary creep conditions

    International Nuclear Information System (INIS)

    Igari, Toshihide; Tokiyoshi, Takumi; Mizokami, Yorikata

    2000-01-01

    Prediction methods of macroscopic and local creep behaviors of perforated plates are examined in order to apply these methods to the structural design of perforated structures such as heat exchangers used in elevated temperatures. Both primary and secondary creeps are considered for predicting macroscopic and local creep behaviors of perorated plates which are made of actual structural materials. Both uniaxial and multiaxial loading of perforated plates are taken into consideration. The concept of effective stress is applied to the prediction of macroscopic creep behaviors of perforated plates, and the predicted results are compared with the numerical results by FEM for the unit section of perorated plated under creep, in order to confirm the propriety of the proposed method. Based on the idea that stress exponents in creep equations govern the stress distribution of perforated plates, a modified Neuber's rule is used for predicting local stress and strain concentrations. The propriety of this prediction method is shown through a comparison of the prediction with the numerical results by FEM for the unit section of perforated plates under creep, and experimental results by the Moire method. (author)

  13. Validation of Molecular Dynamics Simulations for Prediction of Three-Dimensional Structures of Small Proteins.

    Science.gov (United States)

    Kato, Koichi; Nakayoshi, Tomoki; Fukuyoshi, Shuichi; Kurimoto, Eiji; Oda, Akifumi

    2017-10-12

    Although various higher-order protein structure prediction methods have been developed, almost all of them were developed based on the three-dimensional (3D) structure information of known proteins. Here we predicted the short protein structures by molecular dynamics (MD) simulations in which only Newton's equations of motion were used and 3D structural information of known proteins was not required. To evaluate the ability of MD simulationto predict protein structures, we calculated seven short test protein (10-46 residues) in the denatured state and compared their predicted and experimental structures. The predicted structure for Trp-cage (20 residues) was close to the experimental structure by 200-ns MD simulation. For proteins shorter or longer than Trp-cage, root-mean square deviation values were larger than those for Trp-cage. However, secondary structures could be reproduced by MD simulations for proteins with 10-34 residues. Simulations by replica exchange MD were performed, but the results were similar to those from normal MD simulations. These results suggest that normal MD simulations can roughly predict short protein structures and 200-ns simulations are frequently sufficient for estimating the secondary structures of protein (approximately 20 residues). Structural prediction method using only fundamental physical laws are useful for investigating non-natural proteins, such as primitive proteins and artificial proteins for peptide-based drug delivery systems.

  14. Rapid NMR screening of RNA secondary structure and binding

    International Nuclear Information System (INIS)

    Helmling, Christina; Keyhani, Sara; Sochor, Florian; Fürtig, Boris; Hengesbach, Martin; Schwalbe, Harald

    2015-01-01

    Determination of RNA secondary structures by NMR spectroscopy is a useful tool e.g. to elucidate RNA folding space or functional aspects of regulatory RNA elements. However, current approaches of RNA synthesis and preparation are usually time-consuming and do not provide analysis with single nucleotide precision when applied for a large number of different RNA sequences. Here, we significantly improve the yield and 3′ end homogeneity of RNA preparation by in vitro transcription. Further, by establishing a native purification procedure with increased throughput, we provide a shortcut to study several RNA constructs simultaneously. We show that this approach yields μmol quantities of RNA with purities comparable to PAGE purification, while avoiding denaturation of the RNA

  15. Rapid NMR screening of RNA secondary structure and binding

    Energy Technology Data Exchange (ETDEWEB)

    Helmling, Christina; Keyhani, Sara; Sochor, Florian; Fürtig, Boris; Hengesbach, Martin; Schwalbe, Harald, E-mail: schwalbe@nmr.uni-frankfurt.de [Johann Wolfgang Goethe-Universität, Institut für Organische Chemie und Chemische Biologie, Center for Biomolecular Magnetic Resonance (BMRZ) (Germany)

    2015-09-15

    Determination of RNA secondary structures by NMR spectroscopy is a useful tool e.g. to elucidate RNA folding space or functional aspects of regulatory RNA elements. However, current approaches of RNA synthesis and preparation are usually time-consuming and do not provide analysis with single nucleotide precision when applied for a large number of different RNA sequences. Here, we significantly improve the yield and 3′ end homogeneity of RNA preparation by in vitro transcription. Further, by establishing a native purification procedure with increased throughput, we provide a shortcut to study several RNA constructs simultaneously. We show that this approach yields μmol quantities of RNA with purities comparable to PAGE purification, while avoiding denaturation of the RNA.

  16. Class Anxiety in Secondary Education: Exploring Structural Relations with Perceived Control, Engagement, Disaffection, and Performance.

    Science.gov (United States)

    González, Antonio; Faílde Garrido, José María; Rodríguez Castro, Yolanda; Carrera Rodríguez, María Victoria

    2015-09-14

    The aim of this study was to assess the relationships between class-related anxiety with perceived control, teacher-reported behavioral engagement, behavioral disaffection, and academic performance. Participants were 355 compulsory secondary students (9th and 10th grades; Mean age = 15.2 years; SD = 1.8 years). Structural equation models revealed performance was predicted by perceived control, anxiety, disaffection, and engagement. Perceived control predicted anxiety, disaffection, and engagement. Anxiety predicted disaffection and engagement, and partially mediated the effects from control on disaffection (β = -.277, p anxiety and performance was mediated by engagement and disaffection (β = -.295, p Anxiety, engagement, and disaffection mediated the effects of control on performance (β = .352, p < .003; CI = .279, .440). The implications of these results are discussed in the light of current theory and educational interventions.

  17. Consequential secondary structure alterations and aggregation during prolonged casein glycation.

    Science.gov (United States)

    Jindal, Supriya; Naeem, Aabgeena

    2013-05-01

    Non-enzymatic glycosylation (glycation) of casein is a process used not just to ameliorate the quality of dairy products but also to increase the shelf life of canned foods, including baby milk supplements. Incubation of κ-casein with reducing sugars for 15 days at physiological temperature showed the formation of a molten globule state at day 9 and 12 during fructation and glucation respectively. This state exhibits substantial secondary structure and maximum ANS binding. Later on, glycation resulted in the formation of aggregates at day 12 in presence of fructose and day 15 in presence of glucose. Aggregates possess extensive β-sheet structure as revealed by far-UV CD and FTIR. These aggregates showed altered tryptophan environment, decrease ANS binding relative to molten globule state and increase in Thioflavin T fluorescence. Aggregates were also accompanied by the accumulation of AGEs, indicative of structural damage to the protein and formation of potentially harmful species at the physiological level. Fructose was more reactive than glucose and thus caused early and significant changes in the protein. From our studies, we conclude that controlling the extent of the Maillard reaction in the food industry is essential to counter its negative effects and expand its safety spectrum.

  18. SFESA: a web server for pairwise alignment refinement by secondary structure shifts.

    Science.gov (United States)

    Tong, Jing; Pei, Jimin; Grishin, Nick V

    2015-09-03

    Protein sequence alignment is essential for a variety of tasks such as homology modeling and active site prediction. Alignment errors remain the main cause of low-quality structure models. A bioinformatics tool to refine alignments is needed to make protein alignments more accurate. We developed the SFESA web server to refine pairwise protein sequence alignments. Compared to the previous version of SFESA, which required a set of 3D coordinates for a protein, the new server will search a sequence database for the closest homolog with an available 3D structure to be used as a template. For each alignment block defined by secondary structure elements in the template, SFESA evaluates alignment variants generated by local shifts and selects the best-scoring alignment variant. A scoring function that combines the sequence score of profile-profile comparison and the structure score of template-derived contact energy is used for evaluation of alignments. PROMALS pairwise alignments refined by SFESA are more accurate than those produced by current advanced alignment methods such as HHpred and CNFpred. In addition, SFESA also improves alignments generated by other software. SFESA is a web-based tool for alignment refinement, designed for researchers to compute, refine, and evaluate pairwise alignments with a combined sequence and structure scoring of alignment blocks. To our knowledge, the SFESA web server is the only tool that refines alignments by evaluating local shifts of secondary structure elements. The SFESA web server is available at http://prodata.swmed.edu/sfesa.

  19. Antibody structural modeling with prediction of immunoglobulin structure (PIGS)

    DEFF Research Database (Denmark)

    Marcatili, Paolo; Olimpieri, Pier Paolo; Chailyan, Anna

    2014-01-01

    Antibodies (or immunoglobulins) are crucial for defending organisms from pathogens, but they are also key players in many medical, diagnostic and biotechnological applications. The ability to predict their structure and the specific residues involved in antigen recognition has several useful...... applications in all of these areas. Over the years, we have developed or collaborated in developing a strategy that enables researchers to predict the 3D structure of antibodies with a very satisfactory accuracy. The strategy is completely automated and extremely fast, requiring only a few minutes (∼10 min...... on average) to build a structural model of an antibody. It is based on the concept of canonical structures of antibody loops and on our understanding of the way light and heavy chains pack together....

  20. Antibody structural modeling with prediction of immunoglobulin structure (PIGS)

    KAUST Repository

    Marcatili, Paolo

    2014-11-06

    © 2014 Nature America, Inc. All rights reserved. Antibodies (or immunoglobulins) are crucial for defending organisms from pathogens, but they are also key players in many medical, diagnostic and biotechnological applications. The ability to predict their structure and the specific residues involved in antigen recognition has several useful applications in all of these areas. Over the years, we have developed or collaborated in developing a strategy that enables researchers to predict the 3D structure of antibodies with a very satisfactory accuracy. The strategy is completely automated and extremely fast, requiring only a few minutes (~10 min on average) to build a structural model of an antibody. It is based on the concept of canonical structures of antibody loops and on our understanding of the way light and heavy chains pack together.

  1. CMD: A Database to Store the Bonding States of Cysteine Motifs with Secondary Structures

    Directory of Open Access Journals (Sweden)

    Hamed Bostan

    2012-01-01

    Full Text Available Computational approaches to the disulphide bonding state and its connectivity pattern prediction are based on various descriptors. One descriptor is the amino acid sequence motifs flanking the cysteine residue motifs. Despite the existence of disulphide bonding information in many databases and applications, there is no complete reference and motif query available at the moment. Cysteine motif database (CMD is the first online resource that stores all cysteine residues, their flanking motifs with their secondary structure, and propensity values assignment derived from the laboratory data. We extracted more than 3 million cysteine motifs from PDB and UniProt data, annotated with secondary structure assignment, propensity value assignment, and frequency of occurrence and coefficiency of their bonding status. Removal of redundancies generated 15875 unique flanking motifs that are always bonded and 41577 unique patterns that are always nonbonded. Queries are based on the protein ID, FASTA sequence, sequence motif, and secondary structure individually or in batch format using the provided APIs that allow remote users to query our database via third party software and/or high throughput screening/querying. The CMD offers extensive information about the bonded, free cysteine residues, and their motifs that allows in-depth characterization of the sequence motif composition.

  2. How does vegetation structure influence woodpeckers and secondary cavity nesting birds in African cork oak forest?

    Science.gov (United States)

    Segura, Amalia

    2017-08-01

    The Great Spotted Woodpecker provides important information about the status of a forest in terms of structure and age. As a primary cavity creator, it provides small-medium size cavities for passerines. However, despite its interest as an ecosystem engineer, studies of this species in Africa are scarce. Here, spatially explicit predictive models were used to investigate how forest structural variables are related to both the Great Spotted Woodpecker and secondary cavity nesting birds in Maamora cork oak forest (northwest Morocco). A positive association between Great Spotted Woodpecker and both dead-tree density and large mature trees (>60 cm dbh) was found. This study area, Maamora, has an old-growth forest structure incorporating a broad range of size and condition of live and dead trees, favouring Great Spotted Woodpecker by providing high availability of foraging and excavating sites. Secondary cavity nesting birds, represented by Great Tit, African Blue Tit, and Hoopoe, were predicted by Great Spotted Woodpecker detections. The findings suggest that the conservation of the Maamora cork oak forest could be key to maintaining these hole-nesting birds. However, this forest is threatened by forestry practises and livestock overgrazing and the challenge is therefore to find sustainable management strategies that ensure conservation while allowing its exploitation.

  3. Distance matrix-based approach to protein structure prediction.

    Science.gov (United States)

    Kloczkowski, Andrzej; Jernigan, Robert L; Wu, Zhijun; Song, Guang; Yang, Lei; Kolinski, Andrzej; Pokarowski, Piotr

    2009-03-01

    Much structural information is encoded in the internal distances; a distance matrix-based approach can be used to predict protein structure and dynamics, and for structural refinement. Our approach is based on the square distance matrix D = [r(ij)(2)] containing all square distances between residues in proteins. This distance matrix contains more information than the contact matrix C, that has elements of either 0 or 1 depending on whether the distance r (ij) is greater or less than a cutoff value r (cutoff). We have performed spectral decomposition of the distance matrices D = sigma lambda(k)V(k)V(kT), in terms of eigenvalues lambda kappa and the corresponding eigenvectors v kappa and found that it contains at most five nonzero terms. A dominant eigenvector is proportional to r (2)--the square distance of points from the center of mass, with the next three being the principal components of the system of points. By predicting r (2) from the sequence we can approximate a distance matrix of a protein with an expected RMSD value of about 7.3 A, and by combining it with the prediction of the first principal component we can improve this approximation to 4.0 A. We can also explain the role of hydrophobic interactions for the protein structure, because r is highly correlated with the hydrophobic profile of the sequence. Moreover, r is highly correlated with several sequence profiles which are useful in protein structure prediction, such as contact number, the residue-wise contact order (RWCO) or mean square fluctuations (i.e. crystallographic temperature factors). We have also shown that the next three components are related to spatial directionality of the secondary structure elements, and they may be also predicted from the sequence, improving overall structure prediction. We have also shown that the large number of available HIV-1 protease structures provides a remarkable sampling of conformations, which can be viewed as direct structural information about the

  4. Structure prediction of AlnOm clusters

    International Nuclear Information System (INIS)

    Smok, P

    2011-01-01

    Genetic algorithm simulations, using Buckingham potential to represent the anion-anion and cation-anion short-range interactions, were performed in order to predict the equilibrium positions of the Al and O ions in Al n O m clusters. In order to find the equilibrium structures of compounds a self-organizing genetic algorithm were constructed. The calculation were carried out for several clusters Al n O m , with different numbers of aluminium and oxygen atoms.

  5. Amino Acid Molecular Units: Building Primary and Secondary Protein Structures

    Directory of Open Access Journals (Sweden)

    Aparecido R. Silva

    2008-05-01

    Full Text Available In order to guarantee the learning quality and suitable knowledge  use  about structural biology, it is fundamental to  exist, since the beginning of  students’ formation, the possibility of clear visualization of biomolecule structures. Nevertheless, the didactic books can only bring  schematic  drawings; even more elaborated figures and graphic computation  do not permit the necessary interaction.  The representation of three-dimensional molecular structures with ludic models, built with representative units, have supplied to the students and teachers a successfully experience to  visualize such structures and correlate them to the real molecules.  The design and applicability of the representative units were discussed with researchers and teachers before mould implementation.  In this stage  it  will be presented the  developed  kit  containing the  representative  plastic parts of the main amino acids.  The kit can demonstrate the interaction among the amino acids  functional groups  (represented by colors, shapes,  sizes and  the peptidic bonds between them  facilitating the assembly and visuali zation of the primary and secondary protein structure.  The models were designed for  Ca,  amino,  carboxyl groups  and  hydrogen. The  lateral chains have  well defined models that represent their geometrical shape.  The completed kit set  will be presented in this meeting (patent requested.  In the last phase of the project will be realized  an effective evaluation  of the kit  as a facilitative didactic tool of the teaching/learning process in the Structural Molecular Biology area.

  6. Predicting Academic Success and Technological Literacy in Secondary Education: A Learning Styles Perspective

    Science.gov (United States)

    Avsec, Stanislav; Szewczyk-Zakrzewska, Agnieszka

    2017-01-01

    This paper aims to investigate the predictive validity of learning styles on academic achievement and technological literacy (TL). For this purpose, secondary school students were recruited (n = 150). An empirical research design was followed where the TL test was used with a learning style inventory measuring learning orientation, processing…

  7. Predicting Homework Time Management at the Secondary School Level: A Multilevel Analysis

    Science.gov (United States)

    Xu, Jianzhong

    2010-01-01

    The purpose of this study is to test empirical models of variables posited to predict homework time management at the secondary school level. Student- and class-level predictors of homework time management were analyzed in a survey of 1895 students from 111 classes. Most of the variance in homework time management occurred at the student level,…

  8. Primary School Text Comprehension Predicts Mathematical Word Problem-Solving Skills in Secondary School

    Science.gov (United States)

    Björn, Piia Maria; Aunola, Kaisa; Nurmi, Jari-Erik

    2016-01-01

    This longitudinal study aimed to investigate the extent to which primary school text comprehension predicts mathematical word problem-solving skills in secondary school among Finnish students. The participants were 224 fourth graders (9-10 years old at the baseline). The children's text-reading fluency, text comprehension and basic calculation…

  9. Constraint Logic Programming approach to protein structure prediction

    Directory of Open Access Journals (Sweden)

    Fogolari Federico

    2004-11-01

    Full Text Available Abstract Background The protein structure prediction problem is one of the most challenging problems in biological sciences. Many approaches have been proposed using database information and/or simplified protein models. The protein structure prediction problem can be cast in the form of an optimization problem. Notwithstanding its importance, the problem has very seldom been tackled by Constraint Logic Programming, a declarative programming paradigm suitable for solving combinatorial optimization problems. Results Constraint Logic Programming techniques have been applied to the protein structure prediction problem on the face-centered cube lattice model. Molecular dynamics techniques, endowed with the notion of constraint, have been also exploited. Even using a very simplified model, Constraint Logic Programming on the face-centered cube lattice model allowed us to obtain acceptable results for a few small proteins. As a test implementation their (known secondary structure and the presence of disulfide bridges are used as constraints. Simplified structures obtained in this way have been converted to all atom models with plausible structure. Results have been compared with a similar approach using a well-established technique as molecular dynamics. Conclusions The results obtained on small proteins show that Constraint Logic Programming techniques can be employed for studying protein simplified models, which can be converted into realistic all atom models. The advantage of Constraint Logic Programming over other, much more explored, methodologies, resides in the rapid software prototyping, in the easy way of encoding heuristics, and in exploiting all the advances made in this research area, e.g. in constraint propagation and its use for pruning the huge search space.

  10. Constraint Logic Programming approach to protein structure prediction.

    Science.gov (United States)

    Dal Palù, Alessandro; Dovier, Agostino; Fogolari, Federico

    2004-11-30

    The protein structure prediction problem is one of the most challenging problems in biological sciences. Many approaches have been proposed using database information and/or simplified protein models. The protein structure prediction problem can be cast in the form of an optimization problem. Notwithstanding its importance, the problem has very seldom been tackled by Constraint Logic Programming, a declarative programming paradigm suitable for solving combinatorial optimization problems. Constraint Logic Programming techniques have been applied to the protein structure prediction problem on the face-centered cube lattice model. Molecular dynamics techniques, endowed with the notion of constraint, have been also exploited. Even using a very simplified model, Constraint Logic Programming on the face-centered cube lattice model allowed us to obtain acceptable results for a few small proteins. As a test implementation their (known) secondary structure and the presence of disulfide bridges are used as constraints. Simplified structures obtained in this way have been converted to all atom models with plausible structure. Results have been compared with a similar approach using a well-established technique as molecular dynamics. The results obtained on small proteins show that Constraint Logic Programming techniques can be employed for studying protein simplified models, which can be converted into realistic all atom models. The advantage of Constraint Logic Programming over other, much more explored, methodologies, resides in the rapid software prototyping, in the easy way of encoding heuristics, and in exploiting all the advances made in this research area, e.g. in constraint propagation and its use for pruning the huge search space.

  11. 3x2 Classroom Goal Structures, Motivational Regulations, Self-Concept, and Affectivity in Secondary School.

    Science.gov (United States)

    Méndez-Giménez, Antonio; Cecchini-Estrada, José-Antonio; Fernández-Río, Javier; Prieto Saborit, José Antonio; Méndez-Alonso, David

    2017-09-20

    The main objective was to analyze relationships and predictive patterns between 3x2 classroom goal structures (CGS), and motivational regulations, dimensions of self-concept, and affectivity in the context of secondary education. A sample of 1,347 secondary school students (56.6% young men, 43.4% young women) from 10 different provinces of Spain agreed to participate (M age = 13.43, SD = 1.05). Hierarchical regression analyses indicated the self-approach CGS was the most adaptive within the spectrum of self-determination, followed by the task-approach CGS. The other-approach CGS had an ambivalent influence on motivation. Task-approach and self-approach CGS predicted academic self-concept (p approach CGS (negatively) predicted family self-concept (p approach and other-approach CGS's (p approach-oriented CGS's (p approach (positively) and self-approach (negatively) CGS (p < .001; p < .05, respectively; R 2 = .028). These results expand the 3x2 achievement goal framework to include environmental factors, and reiterate that teachers should focus on raising levels of self- and task-based goals for students in their classes.

  12. Evolutionary Structure Prediction of Stoichiometric Compounds

    Science.gov (United States)

    Zhu, Qiang; Oganov, Artem

    2014-03-01

    In general, for a given ionic compound AmBn\\ at ambient pressure condition, its stoichiometry reflects the valence state ratio between per chemical specie (i.e., the charges for each anion and cation). However, compounds under high pressure exhibit significantly behavior, compared to those analogs at ambient condition. Here we developed a method to solve the crystal structure prediction problem based on the evolutionary algorithms, which can predict both the stable compounds and their crystal structures at arbitrary P,T-conditions, given just the set of chemical elements. By applying this method to a wide range of binary ionic systems (Na-Cl, Mg-O, Xe-O, Cs-F, etc), we discovered a lot of compounds with brand new stoichimetries which can become thermodynamically stable. Further electronic structure analysis on these novel compounds indicates that several factors can contribute to this extraordinary phenomenon: (1) polyatomic anions; (2) free electron localization; (3) emergence of new valence states; (4) metallization. In particular, part of the results have been confirmed by experiment, which warrants that this approach can play a crucial role in new materials design under extreme pressure conditions. This work is funded by DARPA (Grants No. W31P4Q1210008 and W31P4Q1310005), NSF (EAR-1114313 and DMR-1231586).

  13. Alpha complexes in protein structure prediction

    DEFF Research Database (Denmark)

    Winter, Pawel; Fonseca, Rasmus

    2015-01-01

    Reducing the computational effort and increasing the accuracy of potential energy functions is of utmost importance in modeling biological systems, for instance in protein structure prediction, docking or design. Evaluating interactions between nonbonded atoms is the bottleneck of such computations......-complexes from scratch for every configuration encountered during the search for the native structure would make this approach hopelessly slow. However, it is argued that kinetic a-complexes can be used to reduce the computational effort of determining the potential energy when "moving" from one configuration...... to a neighboring one. As a consequence, relatively expensive (initial) construction of an a-complex is expected to be compensated by subsequent fast kinetic updates during the search process. Computational results presented in this paper are limited. However, they suggest that the applicability of a...

  14. Evolution of primary and secondary structures in 5S and 5.8S rRNA

    International Nuclear Information System (INIS)

    Curtiss, W.C.

    1986-01-01

    The secondary structure of Bombyx mori 5S rRNA was studied using the sing-strand specific S1 nuclease and the base pair specific cobra venom ribonuclease. The RNA was end-labeled with [ 32 P] at either the 5' or 3' end and sequenced using enzymatic digestion techniques. These enzymatic data coupled with thermodynamic structure prediction were used to generate a secondary structure for 5S rRNA. A computer algorithm has been implemented to aid in the comparison of a large set of homologous RNAs. Eukaryotic 5S rRNA sequences from thirty four diverse species were compared by (1) alignment or the sequences, (2) the positions of substitutions were located with respect to the aligned sequence and secondary structure, and (3) the R-Y model of base stacking was used to study stacking pattern relationships in the structure. Eukaryotic 5S rRNA was found to have significant sequence variation throughout much of the molecule while maintaining a relatively constant secondary structure. A detailed analysis of the sequence and structure variability in each region of the molecule is presented

  15. Protein structure based prediction of catalytic residues.

    Science.gov (United States)

    Fajardo, J Eduardo; Fiser, Andras

    2013-02-22

    Worldwide structural genomics projects continue to release new protein structures at an unprecedented pace, so far nearly 6000, but only about 60% of these proteins have any sort of functional annotation. We explored a range of features that can be used for the prediction of functional residues given a known three-dimensional structure. These features include various centrality measures of nodes in graphs of interacting residues: closeness, betweenness and page-rank centrality. We also analyzed the distance of functional amino acids to the general center of mass (GCM) of the structure, relative solvent accessibility (RSA), and the use of relative entropy as a measure of sequence conservation. From the selected features, neural networks were trained to identify catalytic residues. We found that using distance to the GCM together with amino acid type provide a good discriminant function, when combined independently with sequence conservation. Using an independent test set of 29 annotated protein structures, the method returned 411 of the initial 9262 residues as the most likely to be involved in function. The output 411 residues contain 70 of the annotated 111 catalytic residues. This represents an approximately 14-fold enrichment of catalytic residues on the entire input set (corresponding to a sensitivity of 63% and a precision of 17%), a performance competitive with that of other state-of-the-art methods. We found that several of the graph based measures utilize the same underlying feature of protein structures, which can be simply and more effectively captured with the distance to GCM definition. This also has the added the advantage of simplicity and easy implementation. Meanwhile sequence conservation remains by far the most influential feature in identifying functional residues. We also found that due the rapid changes in size and composition of sequence databases, conservation calculations must be recalibrated for specific reference databases.

  16. Personality traits measured at baseline can predict academic performance in upper secondary school three years late.

    Science.gov (United States)

    Rosander, Pia; Bäckström, Martin

    2014-12-01

    The aim of the present study was to explore the ability of personality to predict academic performance in a longitudinal study of a Swedish upper secondary school sample. Academic performance was assessed throughout a three-year period via final grades from the compulsory school and upper secondary school. The Big Five personality factors (Costa & McCrae, ) - particularly Conscientiousness and Neuroticism - were found to predict overall academic performance, after controlling for general intelligence. Results suggest that Conscientiousness, as measured at the age of 16, can explain change in academic performance at the age of 19. The effect of Neuroticism on Conscientiousness indicates that, as regarding getting good grades, it is better to be a bit neurotic than to be stable. The study extends previous work by assessing the relationship between the Big Five and academic performance over a three-year period. The results offer educators avenues for improving educational achievement. © 2014 Scandinavian Psychological Associations and John Wiley & Sons Ltd.

  17. Evaluating the effect of disturbed ensemble distributions on SCFG based statistical sampling of RNA secondary structures

    Directory of Open Access Journals (Sweden)

    Scheid Anika

    2012-07-01

    Full Text Available Abstract Background Over the past years, statistical and Bayesian approaches have become increasingly appreciated to address the long-standing problem of computational RNA structure prediction. Recently, a novel probabilistic method for the prediction of RNA secondary structures from a single sequence has been studied which is based on generating statistically representative and reproducible samples of the entire ensemble of feasible structures for a particular input sequence. This method samples the possible foldings from a distribution implied by a sophisticated (traditional or length-dependent stochastic context-free grammar (SCFG that mirrors the standard thermodynamic model applied in modern physics-based prediction algorithms. Specifically, that grammar represents an exact probabilistic counterpart to the energy model underlying the Sfold software, which employs a sampling extension of the partition function (PF approach to produce statistically representative subsets of the Boltzmann-weighted ensemble. Although both sampling approaches have the same worst-case time and space complexities, it has been indicated that they differ in performance (both with respect to prediction accuracy and quality of generated samples, where neither of these two competing approaches generally outperforms the other. Results In this work, we will consider the SCFG based approach in order to perform an analysis on how the quality of generated sample sets and the corresponding prediction accuracy changes when different degrees of disturbances are incorporated into the needed sampling probabilities. This is motivated by the fact that if the results prove to be resistant to large errors on the distinct sampling probabilities (compared to the exact ones, then it will be an indication that these probabilities do not need to be computed exactly, but it may be sufficient and more efficient to approximate them. Thus, it might then be possible to decrease the worst

  18. Workplace Deviance: A Predictive study of Occupational Stress and Emotional Intelligence among Secondary School teachers

    OpenAIRE

    Oguegbe Tochukwu Matthew; Uzoh Bonaventure Chigozie; Anyikwa Kosiso

    2014-01-01

    The study investigated workplace deviance:A predictive study of Occupational stress and Emotional intelligence among secondary school teachers. A total number of 198 teachers from Nigeria served as participants with the mean age of 32.98,standarddeviation 0f 9.26 and age range of 22 to 54years. Three instruments were used in the study: Workplace deviance scale, Occupational stress inventory and Emotional intelligence scale. The study adopted a correlational design with Pearson Product Moment ...

  19. Predictive validity of examinations at the Secondary Education Certificate (SEC) level

    OpenAIRE

    Farrugia, Josette; Ventura, Frank

    2007-01-01

    This paper presents the predictive validity of results obtained by 16-year-old Maltese students in the May 2004 Secondary Education Certificate (SEC) examinations in Biology, Chemistry, Physics, Mathematics, Computing, English and Maltese for the Advanced level examinations in these subjects taken by the same students two years later. The study checks whether the SEC level is a good foundation for the higher level, the likelihood of obtaining a high grade at A-level from particular SEC result...

  20. Repeat-swap homology modeling of secondary active transporters: updated protocol and prediction of elevator-type mechanisms.

    Science.gov (United States)

    Vergara-Jaque, Ariela; Fenollar-Ferrer, Cristina; Kaufmann, Desirée; Forrest, Lucy R

    2015-01-01

    Secondary active transporters are critical for neurotransmitter clearance and recycling during synaptic transmission and uptake of nutrients. These proteins mediate the movement of solutes against their concentration gradients, by using the energy released in the movement of ions down pre-existing concentration gradients. To achieve this, transporters conform to the so-called alternating-access hypothesis, whereby the protein adopts at least two conformations in which the substrate binding sites are exposed to one or other side of the membrane, but not both simultaneously. Structures of a bacterial homolog of neuronal glutamate transporters, GltPh, in several different conformational states have revealed that the protein structure is asymmetric in the outward- and inward-open states, and that the conformational change connecting them involves a elevator-like movement of a substrate binding domain across the membrane. The structural asymmetry is created by inverted-topology repeats, i.e., structural repeats with similar overall folds whose transmembrane topologies are related to each other by two-fold pseudo-symmetry around an axis parallel to the membrane plane. Inverted repeats have been found in around three-quarters of secondary transporter folds. Moreover, the (a)symmetry of these systems has been successfully used as a bioinformatic tool, called "repeat-swap modeling" to predict structural models of a transporter in one conformation using the known structure of the transporter in the complementary conformation as a template. Here, we describe an updated repeat-swap homology modeling protocol, and calibrate the accuracy of the method using GltPh, for which both inward- and outward-facing conformations are known. We then apply this repeat-swap homology modeling procedure to a concentrative nucleoside transporter, VcCNT, which has a three-dimensional arrangement related to that of GltPh. The repeat-swapped model of VcCNT predicts that nucleoside transport also

  1. Repeat-swap homology modeling of secondary active transporters: updated protocol and prediction of elevator-type mechanisms

    Directory of Open Access Journals (Sweden)

    Cristina eFenollar Ferrer

    2015-09-01

    Full Text Available Secondary active transporters are critical for neurotransmitter clearance and recycling during synaptic transmission and uptake of nutrients. These proteins mediate the movement of solutes against their concentration gradients, by using the energy released in the movement of ions down pre-existing concentration gradients. To achieve this, transporters conform to the so-called alternating-access hypothesis, whereby the protein adopts at least two conformations in which the substrate binding sites are exposed to either the outside or inside of the membrane, but not both simultaneously. Structures of a bacterial homolog of neuronal glutamate transporters, GltPh, in several different conformational states have revealed that the protein structure is asymmetric in the outward- and inward-open states, and that the conformational change connecting them involves a elevator-like movement of a substrate binding domain across the membrane. The structural asymmetry is created by inverted-topology repeats, i.e., structural repeats with similar overall folds whose transmembrane topologies are related to each other by two-fold pseudo-symmetry around an axis parallel to the membrane plane. Inverted repeats have been found in around three-quarters of secondary transporter folds. Moreover, the (asymmetry of these systems has been successfully used as a bioinformatic tool, called repeat-swap modeling to predict structural models of a transporter in one conformation using the known structure of the transporter in the complementary conformation as a template. Here, we describe an updated repeat-swap homology modeling protocol, and calibrate the accuracy of the method using GltPh, for which both inward- and outward-facing conformations are known. We then apply this repeat-swap homology modeling procedure to a concentrative nucleoside transporter, VcCNT, which has a three-dimensional arrangement related to that of GltPh. The repeat-swapped model of VcCNT predicts that

  2. Computational methods in sequence and structure prediction

    Science.gov (United States)

    Lang, Caiyi

    a software package which is capable of designing novel protein structures at the atomic resolution. This software package allows us to perform protein structure design with a flexible backbone. The backbone flexibility includes loop region relaxation as well as a secondary structure collective mode relaxation scheme. (Abstract shortened by UMI.)

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

    DEFF Research Database (Denmark)

    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...

  4. Including RNA secondary structures improves accuracy and robustness in reconstruction of phylogenetic trees.

    Science.gov (United States)

    Keller, Alexander; Förster, Frank; Müller, Tobias; Dandekar, Thomas; Schultz, Jörg; Wolf, Matthias

    2010-01-15

    In several studies, secondary structures of ribosomal genes have been used to improve the quality of phylogenetic reconstructions. An extensive evaluation of the benefits of secondary structure, however, is lacking. This is the first study to counter this deficiency. We inspected the accuracy and robustness of phylogenetics with individual secondary structures by simulation experiments for artificial tree topologies with up to 18 taxa and for divergency levels in the range of typical phylogenetic studies. We chose the internal transcribed spacer 2 of the ribosomal cistron as an exemplary marker region. Simulation integrated the coevolution process of sequences with secondary structures. Additionally, the phylogenetic power of marker size duplication was investigated and compared with sequence and sequence-structure reconstruction methods. The results clearly show that accuracy and robustness of Neighbor Joining trees are largely improved by structural information in contrast to sequence only data, whereas a doubled marker size only accounts for robustness. Individual secondary structures of ribosomal RNA sequences provide a valuable gain of information content that is useful for phylogenetics. Thus, the usage of ITS2 sequence together with secondary structure for taxonomic inferences is recommended. Other reconstruction methods as maximum likelihood, bayesian inference or maximum parsimony may equally profit from secondary structure inclusion. This article was reviewed by Shamil Sunyaev, Andrea Tanzer (nominated by Frank Eisenhaber) and Eugene V. Koonin. Reviewed by Shamil Sunyaev, Andrea Tanzer (nominated by Frank Eisenhaber) and Eugene V. Koonin. For the full reviews, please go to the Reviewers' comments section.

  5. Statistically significant dependence of the Xaa-Pro peptide bond conformation on secondary structure and amino acid sequence

    Directory of Open Access Journals (Sweden)

    Leitner Dietmar

    2005-04-01

    Full Text Available Abstract Background A reliable prediction of the Xaa-Pro peptide bond conformation would be a useful tool for many protein structure calculation methods. We have analyzed the Protein Data Bank and show that the combined use of sequential and structural information has a predictive value for the assessment of the cis versus trans peptide bond conformation of Xaa-Pro within proteins. For the analysis of the data sets different statistical methods such as the calculation of the Chou-Fasman parameters and occurrence matrices were used. Furthermore we analyzed the relationship between the relative solvent accessibility and the relative occurrence of prolines in the cis and in the trans conformation. Results One of the main results of the statistical investigations is the ranking of the secondary structure and sequence information with respect to the prediction of the Xaa-Pro peptide bond conformation. We observed a significant impact of secondary structure information on the occurrence of the Xaa-Pro peptide bond conformation, while the sequence information of amino acids neighboring proline is of little predictive value for the conformation of this bond. Conclusion In this work, we present an extensive analysis of the occurrence of the cis and trans proline conformation in proteins. Based on the data set, we derived patterns and rules for a possible prediction of the proline conformation. Upon adoption of the Chou-Fasman parameters, we are able to derive statistically relevant correlations between the secondary structure of amino acid fragments and the Xaa-Pro peptide bond conformation.

  6. A comparative method for finding and folding RNA secondary structures within protein-coding regions

    DEFF Research Database (Denmark)

    Pedersen, Jakob Skou; Meyer, Irmtraud Margret; Forsberg, Roald

    2004-01-01

    that RNA-DECODER's parameters can be automatically trained to successfully fold known secondary structures within the HCV genome. We scan the genomes of HCV and polio virus for conserved secondary-structure elements, and analyze performance as a function of available evolutionary information. On known...... secondary structures, RNA-DECODER shows a sensitivity similar to the programs MFOLD, PFOLD and RNAALIFOLD. When scanning the entire genomes of HCV and polio virus for structure elements, RNA-DECODER's results indicate a markedly higher specificity than MFOLD, PFOLD and RNAALIFOLD....

  7. Deciphering the shape and deformation of secondary structures through local conformation analysis

    Directory of Open Access Journals (Sweden)

    Camproux Anne-Claude

    2011-02-01

    Full Text Available Abstract Background Protein deformation has been extensively analysed through global methods based on RMSD, torsion angles and Principal Components Analysis calculations. Here we use a local approach, able to distinguish among the different backbone conformations within loops, α-helices and β-strands, to address the question of secondary structures' shape variation within proteins and deformation at interface upon complexation. Results Using a structural alphabet, we translated the 3 D structures of large sets of protein-protein complexes into sequences of structural letters. The shape of the secondary structures can be assessed by the structural letters that modeled them in the structural sequences. The distribution analysis of the structural letters in the three protein compartments (surface, core and interface reveals that secondary structures tend to adopt preferential conformations that differ among the compartments. The local description of secondary structures highlights that curved conformations are preferred on the surface while straight ones are preferred in the core. Interfaces display a mixture of local conformations either preferred in core or surface. The analysis of the structural letters transition occurring between protein-bound and unbound conformations shows that the deformation of secondary structure is tightly linked to the compartment preference of the local conformations. Conclusion The conformation of secondary structures can be further analysed and detailed thanks to a structural alphabet which allows a better description of protein surface, core and interface in terms of secondary structures' shape and deformation. Induced-fit modification tendencies described here should be valuable information to identify and characterize regions under strong structural constraints for functional reasons.

  8. Deciphering the shape and deformation of secondary structures through local conformation analysis.

    Science.gov (United States)

    Baussand, Julie; Camproux, Anne-Claude

    2011-02-01

    Protein deformation has been extensively analysed through global methods based on RMSD, torsion angles and Principal Components Analysis calculations. Here we use a local approach, able to distinguish among the different backbone conformations within loops, α-helices and β-strands, to address the question of secondary structures' shape variation within proteins and deformation at interface upon complexation. Using a structural alphabet, we translated the 3 D structures of large sets of protein-protein complexes into sequences of structural letters. The shape of the secondary structures can be assessed by the structural letters that modeled them in the structural sequences. The distribution analysis of the structural letters in the three protein compartments (surface, core and interface) reveals that secondary structures tend to adopt preferential conformations that differ among the compartments. The local description of secondary structures highlights that curved conformations are preferred on the surface while straight ones are preferred in the core. Interfaces display a mixture of local conformations either preferred in core or surface. The analysis of the structural letters transition occurring between protein-bound and unbound conformations shows that the deformation of secondary structure is tightly linked to the compartment preference of the local conformations. The conformation of secondary structures can be further analysed and detailed thanks to a structural alphabet which allows a better description of protein surface, core and interface in terms of secondary structures' shape and deformation. Induced-fit modification tendencies described here should be valuable information to identify and characterize regions under strong structural constraints for functional reasons.

  9. Visualizing RNA Secondary Structure Base Pair Binding Probabilities using Nested Concave Hulls

    OpenAIRE

    Sansen , Joris; Bourqui , Romain; Thebault , Patricia; Allali , Julien; Auber , David

    2015-01-01

    International audience; The challenge 1 of the BIOVIS 2015 design contest consists in designing an intuitive visual depiction of base pairs binding probabilities for secondary structure of ncRNA. Our representation depicts the potential nucleotide pairs binding using nested concave hulls over the computed MFE ncRNA secondary structure. Thus, it allows to identify regions with a high level of uncertainty in the MFE computation and the structures which seem to match to reality.

  10. Protein secondary structure assignment revisited: a detailed analysis of different assignment methods

    Directory of Open Access Journals (Sweden)

    de Brevern Alexandre G

    2005-09-01

    Full Text Available Abstract Background A number of methods are now available to perform automatic assignment of periodic secondary structures from atomic coordinates, based on different characteristics of the secondary structures. In general these methods exhibit a broad consensus as to the location of most helix and strand core segments in protein structures. However the termini of the segments are often ill-defined and it is difficult to decide unambiguously which residues at the edge of the segments have to be included. In addition, there is a "twilight zone" where secondary structure segments depart significantly from the idealized models of Pauling and Corey. For these segments, one has to decide whether the observed structural variations are merely distorsions or whether they constitute a break in the secondary structure. Methods To address these problems, we have developed a method for secondary structure assignment, called KAKSI. Assignments made by KAKSI are compared with assignments given by DSSP, STRIDE, XTLSSTR, PSEA and SECSTR, as well as secondary structures found in PDB files, on 4 datasets (X-ray structures with different resolution range, NMR structures. Results A detailed comparison of KAKSI assignments with those of STRIDE and PSEA reveals that KAKSI assigns slightly longer helices and strands than STRIDE in case of one-to-one correspondence between the segments. However, KAKSI tends also to favor the assignment of several short helices when STRIDE and PSEA assign longer, kinked, helices. Helices assigned by KAKSI have geometrical characteristics close to those described in the PDB. They are more linear than helices assigned by other methods. The same tendency to split long segments is observed for strands, although less systematically. We present a number of cases of secondary structure assignments that illustrate this behavior. Conclusion Our method provides valuable assignments which favor the regularity of secondary structure segments.

  11. The Globular State of the Single-Stranded RNA: Effect of the Secondary Structure Rearrangements

    Science.gov (United States)

    Grigoryan, Zareh A.; Karapetian, Armen T.

    2015-01-01

    The mutual influence of the slow rearrangements of secondary structure and fast collapse of the long single-stranded RNA (ssRNA) in approximation of coarse-grained model is studied with analytic calculations. It is assumed that the characteristic time of the secondary structure rearrangement is much longer than that for the formation of the tertiary structure. A nonequilibrium phase transition of the 2nd order has been observed. PMID:26345143

  12. The Globular State of the Single-Stranded RNA: Effect of the Secondary Structure Rearrangements

    Directory of Open Access Journals (Sweden)

    Zareh A. Grigoryan

    2015-01-01

    Full Text Available The mutual influence of the slow rearrangements of secondary structure and fast collapse of the long single-stranded RNA (ssRNA in approximation of coarse-grained model is studied with analytic calculations. It is assumed that the characteristic time of the secondary structure rearrangement is much longer than that for the formation of the tertiary structure. A nonequilibrium phase transition of the 2nd order has been observed.

  13. Structural protein descriptors in 1-dimension and their sequence-based predictions.

    Science.gov (United States)

    Kurgan, Lukasz; Disfani, Fatemeh Miri

    2011-09-01

    The last few decades observed an increasing interest in development and application of 1-dimensional (1D) descriptors of protein structure. These descriptors project 3D structural features onto 1D strings of residue-wise structural assignments. They cover a wide-range of structural aspects including conformation of the backbone, burying depth/solvent exposure and flexibility of residues, and inter-chain residue-residue contacts. We perform first-of-its-kind comprehensive comparative review of the existing 1D structural descriptors. We define, review and categorize ten structural descriptors and we also describe, summarize and contrast over eighty computational models that are used to predict these descriptors from the protein sequences. We show that the majority of the recent sequence-based predictors utilize machine learning models, with the most popular being neural networks, support vector machines, hidden Markov models, and support vector and linear regressions. These methods provide high-throughput predictions and most of them are accessible to a non-expert user via web servers and/or stand-alone software packages. We empirically evaluate several recent sequence-based predictors of secondary structure, disorder, and solvent accessibility descriptors using a benchmark set based on CASP8 targets. Our analysis shows that the secondary structure can be predicted with over 80% accuracy and segment overlap (SOV), disorder with over 0.9 AUC, 0.6 Matthews Correlation Coefficient (MCC), and 75% SOV, and relative solvent accessibility with PCC of 0.7 and MCC of 0.6 (0.86 when homology is used). We demonstrate that the secondary structure predicted from sequence without the use of homology modeling is as good as the structure extracted from the 3D folds predicted by top-performing template-based methods.

  14. Evidence of pervasive biologically functional secondary structures within the genomes of eukaryotic single-stranded DNA viruses.

    Science.gov (United States)

    Muhire, Brejnev Muhizi; Golden, Michael; Murrell, Ben; Lefeuvre, Pierre; Lett, Jean-Michel; Gray, Alistair; Poon, Art Y F; Ngandu, Nobubelo Kwanele; Semegni, Yves; Tanov, Emil Pavlov; Monjane, Adérito Luis; Harkins, Gordon William; Varsani, Arvind; Shepherd, Dionne Natalie; Martin, Darren Patrick

    2014-02-01

    Single-stranded DNA (ssDNA) viruses have genomes that are potentially capable of forming complex secondary structures through Watson-Crick base pairing between their constituent nucleotides. A few of the structural elements formed by such base pairings are, in fact, known to have important functions during the replication of many ssDNA viruses. Unknown, however, are (i) whether numerous additional ssDNA virus genomic structural elements predicted to exist by computational DNA folding methods actually exist and (ii) whether those structures that do exist have any biological relevance. We therefore computationally inferred lists of the most evolutionarily conserved structures within a diverse selection of animal- and plant-infecting ssDNA viruses drawn from the families Circoviridae, Anelloviridae, Parvoviridae, Nanoviridae, and Geminiviridae and analyzed these for evidence of natural selection favoring the maintenance of these structures. While we find evidence that is consistent with purifying selection being stronger at nucleotide sites that are predicted to be base paired than at sites predicted to be unpaired, we also find strong associations between sites that are predicted to pair with one another and site pairs that are apparently coevolving in a complementary fashion. Collectively, these results indicate that natural selection actively preserves much of the pervasive secondary structure that is evident within eukaryote-infecting ssDNA virus genomes and, therefore, that much of this structure is biologically functional. Lastly, we provide examples of various highly conserved but completely uncharacterized structural elements that likely have important functions within some of the ssDNA virus genomes analyzed here.

  15. CATHARE-2 prediction of large primary to secondary leakage (PRISE) at PSB-VVER experimental facility

    Energy Technology Data Exchange (ETDEWEB)

    Sabotinov, L.; Chevrier, P. [Institut de Radioprotection et de Surete Nucleaire, 92 - Fontenay aux Roses (France)

    2007-07-01

    The large primary to secondary leakage (PRISE) is a specific loss-of-coolant accident in VVER reactors, related to the break of the steam generator collector cover, leading to loss of primary mass inventory and possible direct radioactive release to atmosphere. The best estimate thermal-hydraulic computer code CATHARE-2 Version 2.5-1 was used for post-test analysis of a PRISE experiment, conducted at the large scale test facility PSB-VVER in Russia. The PSB rig is 1:300 scaled model of VVER-1000 NPP. The accident is calculated with a 1.4% break size, which corresponds to 100 mm leak from primary to secondary side in the real NPP. A computer model has been developed for CATHARE-2 V2.5-1, taking into account all important components of the PSB facility: reactor model (lower plenum, core, bypass, upper plenum, downcomer), 4 separate loops, pressurizer, horizontal multi-tube steam generators, break section. The secondary side is presented by recirculation model. A large number of sensitivity calculations has been performed regarding break modeling, reactor pressure vessel modeling, counter current flow modeling, hydraulic losses, heat losses, steam generator level regulation. Comparison between calculated and experimental results shows good prediction of the basic thermal-hydraulic phenomena and parameters such as primary and secondary pressures, temperatures, loop flows, etc. Some discrepancies were observed in the calculations of primary mass inventory and loop seal clearance. Nevertheless the final core heat up, which is one of the most important safety criteria, was correctly predicted. (authors)

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

    Directory of Open Access Journals (Sweden)

    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.

  17. Structure of nonevaporating sprays - Measurements and predictions

    Science.gov (United States)

    Solomon, A. S. P.; Shuen, J.-S.; Zhang, Q.-F.; Faeth, G. M.

    1984-01-01

    Structure measurements were completed within the dilute portion of axisymmetric nonevaporating sprays (SMD of 30 and 87 microns) injected into a still air environment, including: mean and fluctuating gas velocities and Reynolds stress using laser-Doppler anemometry; mean liquid fluxes using isokinetic sampling; drop sizes using slide impaction; and drop sizes and velocities using multiflash photography. The new measurements were used to evaluate three representative models of sprays: (1) a locally homogeneous flow (LHF) model, where slip between the phases was neglected; (2) a deterministic separated flow (DSF) model, where slip was considered but effects of drop interaction with turbulent fluctuations were ignored; and (3) a stochastic separated flow (SSF) model, where effects of both interphase slip and turbulent fluctuations were considered using random sampling for turbulence properties in conjunction with random-walk computations for drop motion. The LHF and DSF models were unsatisfactory for present test conditions-both underestimating flow widths and the rate of spread of drops. In contrast, the SSF model provided reasonably accurate predictions, including effects of enhanced spreading rates of sprays due to drop dispersion by turbulence, with all empirical parameters fixed from earlier work.

  18. Non-B DNA Secondary Structures and Their Resolution by RecQ Helicases

    Directory of Open Access Journals (Sweden)

    Sudha Sharma

    2011-01-01

    Full Text Available In addition to the canonical B-form structure first described by Watson and Crick, DNA can adopt a number of alternative structures. These non-B-form DNA secondary structures form spontaneously on tracts of repeat sequences that are abundant in genomes. In addition, structured forms of DNA with intrastrand pairing may arise on single-stranded DNA produced transiently during various cellular processes. Such secondary structures have a range of biological functions but also induce genetic instability. Increasing evidence suggests that genomic instabilities induced by non-B DNA secondary structures result in predisposition to diseases. Secondary DNA structures also represent a new class of molecular targets for DNA-interactive compounds that might be useful for targeting telomeres and transcriptional control. The equilibrium between the duplex DNA and formation of multistranded non-B-form structures is partly dependent upon the helicases that unwind (resolve these alternate DNA structures. With special focus on tetraplex, triplex, and cruciform, this paper summarizes the incidence of non-B DNA structures and their association with genomic instability and emphasizes the roles of RecQ-like DNA helicases in genome maintenance by resolution of DNA secondary structures. In future, RecQ helicases are anticipated to be additional molecular targets for cancer chemotherapeutics.

  19. Testing Mediation Using Multiple Regression and Structural Equation Modeling Analyses in Secondary Data

    Science.gov (United States)

    Li, Spencer D.

    2011-01-01

    Mediation analysis in child and adolescent development research is possible using large secondary data sets. This article provides an overview of two statistical methods commonly used to test mediated effects in secondary analysis: multiple regression and structural equation modeling (SEM). Two empirical studies are presented to illustrate the…

  20. Building a Better Fragment Library for De Novo Protein Structure Prediction

    Science.gov (United States)

    de Oliveira, Saulo H. P.; Shi, Jiye; Deane, Charlotte M.

    2015-01-01

    Fragment-based approaches are the current standard for de novo protein structure prediction. These approaches rely on accurate and reliable fragment libraries to generate good structural models. In this work, we describe a novel method for structure fragment library generation and its application in fragment-based de novo protein structure prediction. The importance of correct testing procedures in assessing the quality of fragment libraries is demonstrated. In particular, the exclusion of homologs to the target from the libraries to correctly simulate a de novo protein structure prediction scenario, something which surprisingly is not always done. We demonstrate that fragments presenting different predominant predicted secondary structures should be treated differently during the fragment library generation step and that exhaustive and random search strategies should both be used. This information was used to develop a novel method, Flib. On a validation set of 41 structurally diverse proteins, Flib libraries presents both a higher precision and coverage than two of the state-of-the-art methods, NNMake and HHFrag. Flib also achieves better precision and coverage on the set of 275 protein domains used in the two previous experiments of the the Critical Assessment of Structure Prediction (CASP9 and CASP10). We compared Flib libraries against NNMake libraries in a structure prediction context. Of the 13 cases in which a correct answer was generated, Flib models were more accurate than NNMake models for 10. “Flib is available for download at: http://www.stats.ox.ac.uk/research/proteins/resources”. PMID:25901595

  1. Building a better fragment library for de novo protein structure prediction.

    Directory of Open Access Journals (Sweden)

    Saulo H P de Oliveira

    Full Text Available Fragment-based approaches are the current standard for de novo protein structure prediction. These approaches rely on accurate and reliable fragment libraries to generate good structural models. In this work, we describe a novel method for structure fragment library generation and its application in fragment-based de novo protein structure prediction. The importance of correct testing procedures in assessing the quality of fragment libraries is demonstrated. In particular, the exclusion of homologs to the target from the libraries to correctly simulate a de novo protein structure prediction scenario, something which surprisingly is not always done. We demonstrate that fragments presenting different predominant predicted secondary structures should be treated differently during the fragment library generation step and that exhaustive and random search strategies should both be used. This information was used to develop a novel method, Flib. On a validation set of 41 structurally diverse proteins, Flib libraries presents both a higher precision and coverage than two of the state-of-the-art methods, NNMake and HHFrag. Flib also achieves better precision and coverage on the set of 275 protein domains used in the two previous experiments of the the Critical Assessment of Structure Prediction (CASP9 and CASP10. We compared Flib libraries against NNMake libraries in a structure prediction context. Of the 13 cases in which a correct answer was generated, Flib models were more accurate than NNMake models for 10. "Flib is available for download at: http://www.stats.ox.ac.uk/research/proteins/resources".

  2. Sheath structure transition controlled by secondary electron emission

    Science.gov (United States)

    Schweigert, I. V.; Langendorf, S. J.; Walker, M. L. R.; Keidar, M.

    2015-04-01

    In particle-in-cell Monte Carlo collision (PIC MCC) simulations and in an experiment we study sheath formation over an emissive floating Al2O3 plate in a direct current discharge plasma at argon gas pressure 10-4 Torr. The discharge glow is maintained by the beam electrons emitted from a negatively biased hot cathode. We observe three types of sheaths near the floating emissive plate and the transition between them is driven by changing the negative bias. The Debye sheath appears at lower voltages, when secondary electron emission is negligible. With increasing applied voltage, secondary electron emission switches on and a first transition to a new sheath type, beam electron emission (BEE), takes place. For the first time we find this specific regime of sheath operation near the floating emissive surface. In this regime, the potential drop over the plate sheath is about four times larger than the temperature of plasma electrons. The virtual cathode appears near the emissive plate and its modification helps to maintain the BEE regime within some voltage range. Further increase of the applied voltage U initiates the second smooth transition to the plasma electron emission sheath regime and the ratio Δφs/Te tends to unity with increasing U. The oscillatory behavior of the emissive sheath is analyzed in PIC MCC simulations. A plasmoid of slow electrons is formed near the plate and transported to the bulk plasma periodically with a frequency of about 25 kHz.

  3. CHSalign: A Web Server That Builds upon Junction-Explorer and RNAJAG for Pairwise Alignment of RNA Secondary Structures with Coaxial Helical Stacking.

    Directory of Open Access Journals (Sweden)

    Lei Hua

    Full Text Available RNA junctions are important structural elements of RNA molecules. They are formed when three or more helices come together in three-dimensional space. Recent studies have focused on the annotation and prediction of coaxial helical stacking (CHS motifs within junctions. Here we exploit such predictions to develop an efficient alignment tool to handle RNA secondary structures with CHS motifs. Specifically, we build upon our Junction-Explorer software for predicting coaxial stacking and RNAJAG for modelling junction topologies as tree graphs to incorporate constrained tree matching and dynamic programming algorithms into a new method, called CHSalign, for aligning the secondary structures of RNA molecules containing CHS motifs. Thus, CHSalign is intended to be an efficient alignment tool for RNAs containing similar junctions. Experimental results based on thousands of alignments demonstrate that CHSalign can align two RNA secondary structures containing CHS motifs more accurately than other RNA secondary structure alignment tools. CHSalign yields a high score when aligning two RNA secondary structures with similar CHS motifs or helical arrangement patterns, and a low score otherwise. This new method has been implemented in a web server, and the program is also made freely available, at http://bioinformatics.njit.edu/CHSalign/.

  4. DCJ-RNA - double cut and join for RNA secondary structures.

    Science.gov (United States)

    Badr, Ghada H; Al-Aqel, Haifa A

    2017-10-16

    Genome rearrangements are essential processes for evolution and are responsible for existing varieties of genome architectures. Many studies have been conducted to obtain an algorithm that identifies the minimum number of inversions that are necessary to transform one genome into another; this allows for genome sequence representation in polynomial time. Studies have not been conducted on the topic of rearranging a genome when it is represented as a secondary structure. Unlike sequences, the secondary structure preserves the functionality of the genome. Sequences can be different, but they all share the same structure and, therefore, the same functionality. This paper proposes a double cut and join for RNA secondary structures (DCJ-RNA) algorithm. This algorithm allows for the description of evolutionary scenarios that are based on secondary structures rather than sequences. The main aim of this paper is to suggest an efficient algorithm that can help researchers compare two ribonucleic acid (RNA) secondary structures based on rearrangement operations. The results, which are based on real datasets, show that the algorithm is able to count the minimum number of rearrangement operations, as well as to report an optimum scenario that can increase the similarity between the two structures. The algorithm calculates the distance between structures and reports a scenario based on the minimum rearrangement operations required to make the given structure similar to the other. DCJ-RNA can also be used to measure the distance between the two structures. This can help identify the common functionalities between different species.

  5. Induction of secondary and tertiary lymphoid structures in the skin.

    NARCIS (Netherlands)

    Cupedo, T.; Jansen, W.; Kraal, G.; Mebius, R.E.

    2004-01-01

    During embryogenesis a developmental program leading to the formation of lymph nodes and Peyer's patches is initiated. We now show that lymph node-like structures as well as tertiary lymphoid structures can ectopically be induced by intradermal injection of newborn lymph node-derived cells.

  6. Integration of QUARK and I-TASSER for Ab Initio Protein Structure Prediction in CASP11.

    Science.gov (United States)

    Zhang, Wenxuan; Yang, Jianyi; He, Baoji; Walker, Sara Elizabeth; Zhang, Hongjiu; Govindarajoo, Brandon; Virtanen, Jouko; Xue, Zhidong; Shen, Hong-Bin; Zhang, Yang

    2016-09-01

    We tested two pipelines developed for template-free protein structure prediction in the CASP11 experiment. First, the QUARK pipeline constructs structure models by reassembling fragments of continuously distributed lengths excised from unrelated proteins. Five free-modeling (FM) targets have the model successfully constructed by QUARK with a TM-score above 0.4, including the first model of T0837-D1, which has a TM-score = 0.736 and RMSD = 2.9 Å to the native. Detailed analysis showed that the success is partly attributed to the high-resolution contact map prediction derived from fragment-based distance-profiles, which are mainly located between regular secondary structure elements and loops/turns and help guide the orientation of secondary structure assembly. In the Zhang-Server pipeline, weakly scoring threading templates are re-ordered by the structural similarity to the ab initio folding models, which are then reassembled by I-TASSER based structure assembly simulations; 60% more domains with length up to 204 residues, compared to the QUARK pipeline, were successfully modeled by the I-TASSER pipeline with a TM-score above 0.4. The robustness of the I-TASSER pipeline can stem from the composite fragment-assembly simulations that combine structures from both ab initio folding and threading template refinements. Despite the promising cases, challenges still exist in long-range beta-strand folding, domain parsing, and the uncertainty of secondary structure prediction; the latter of which was found to affect nearly all aspects of FM structure predictions, from fragment identification, target classification, structure assembly, to final model selection. Significant efforts are needed to solve these problems before real progress on FM could be made. Proteins 2016; 84(Suppl 1):76-86. © 2015 Wiley Periodicals, Inc. © 2015 Wiley Periodicals, Inc.

  7. [Changes in the secondary and tertiary structure of serum albumin in interactions with ligands of various structures].

    Science.gov (United States)

    Trinus, F P; Braver-Chernobul'skaia, B S; Luĭk, A I; Boldeskul, A E; Velichko, A N

    1984-01-01

    High affinity interactions between blood serum albumin and five substances of various chemical structure, exhibiting distinct physiological activity, were accompanied by alterations in the protein tertiary structure, while the albumin secondary structure was involved in conformational transformation after less effective affinity binding.

  8. Inflatable Habitat with Integrated Primary and Secondary Structure, Phase I

    Data.gov (United States)

    National Aeronautics and Space Administration — Paragon Space Development Corp (Paragon) and Thin Red Line Aerospace (TRLA) proposes to explore the utilization of inflatable structures by designing a habitation...

  9. Density functional study of molecular interactions in secondary structures of proteins.

    Science.gov (United States)

    Takano, Yu; Kusaka, Ayumi; Nakamura, Haruki

    2016-01-01

    Proteins play diverse and vital roles in biology, which are dominated by their three-dimensional structures. The three-dimensional structure of a protein determines its functions and chemical properties. Protein secondary structures, including α-helices and β-sheets, are key components of the protein architecture. Molecular interactions, in particular hydrogen bonds, play significant roles in the formation of protein secondary structures. Precise and quantitative estimations of these interactions are required to understand the principles underlying the formation of three-dimensional protein structures. In the present study, we have investigated the molecular interactions in α-helices and β-sheets, using ab initio wave function-based methods, the Hartree-Fock method (HF) and the second-order Møller-Plesset perturbation theory (MP2), density functional theory, and molecular mechanics. The characteristic interactions essential for forming the secondary structures are discussed quantitatively.

  10. A comprehensive comparison of comparative RNA structure prediction approaches

    DEFF Research Database (Denmark)

    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...

  11. Landscape and variation of RNA secondary structure across the human transcriptome.

    OpenAIRE

    Wan, Y; Qu, K; Zhang, QC; Flynn, RA; Manor, O; Ouyang, Z; Zhang, J; Spitale, RC; Snyder, MP; Segal, E; Chang, HY

    2014-01-01

    In parallel to the genetic code for protein synthesis, a second layer of information is embedded in all RNA transcripts in the form of RNA structure. RNA structure influences practically every step in the gene expression program. However, the nature of most RNA structures or effects of sequence variation on structure are not known. Here we report the initial landscape and variation of RNA secondary structures (RSSs) in a human family trio (mother, father and their child). This provides a comp...

  12. Probing the glycosidic linkage: secondary structures in the gas phase

    Energy Technology Data Exchange (ETDEWEB)

    Simons, John P; Cristina Stanca-Kaposta, E; Cocinero, Emilio J; Liu, B [Chemistry Department, Physical and Theoretical Chemistry Laboratory, South Parks Road, Oxford OX1 3QZ (United Kingdom); Davis, Benjamin G; Gamblin, David P [Chemistry Department, Chemical Research Laboratory, 12 Mansfield Road, Oxford OX1 4TA (United Kingdom); Kroemer, Romano T [Sanofi-Aventis, CRVA, 13 quai Jules Guesde, BP14, 94403 Vitry-sur-Seine (France)], E-mail: John.Simons@chem.ox.ac.uk

    2008-10-15

    The functional importance of carbohydrates in biological processes, particularly those involving specific molecular recognition, is immense. Characterizing the three-dimensional (3D) structures of carbohydrates and glycoproteins, and their interactions with other molecules, not least the ubiquitous solvent, water, is a key starting point for understanding these processes. The combination of laser-based electronic and vibrational spectroscopy of mass-selected carbohydrate molecules and their hydrated complexes, conducted under molecular beam conditions, with ab initio computation is providing a uniquely powerful means of characterizing 3D carbohydrate conformations; the structures of their hydrated complexes, the hydrogen-bonded networks they support (or which support them); and the factors that determine their conformational and structural preferences.

  13. Probing the glycosidic linkage: secondary structures in the gas phase

    International Nuclear Information System (INIS)

    Simons, John P; Cristina Stanca-Kaposta, E; Cocinero, Emilio J; Liu, B; Davis, Benjamin G; Gamblin, David P; Kroemer, Romano T

    2008-01-01

    The functional importance of carbohydrates in biological processes, particularly those involving specific molecular recognition, is immense. Characterizing the three-dimensional (3D) structures of carbohydrates and glycoproteins, and their interactions with other molecules, not least the ubiquitous solvent, water, is a key starting point for understanding these processes. The combination of laser-based electronic and vibrational spectroscopy of mass-selected carbohydrate molecules and their hydrated complexes, conducted under molecular beam conditions, with ab initio computation is providing a uniquely powerful means of characterizing 3D carbohydrate conformations; the structures of their hydrated complexes, the hydrogen-bonded networks they support (or which support them); and the factors that determine their conformational and structural preferences.

  14. Structural properties of MHC class II ligands, implications for the prediction of MHC class II epitopes.

    Directory of Open Access Journals (Sweden)

    Kasper Winther Jørgensen

    2010-12-01

    Full Text Available Major Histocompatibility class II (MHC-II molecules sample peptides from the extracellular space allowing the immune system to detect the presence of foreign microbes from this compartment. Prediction of MHC class II ligands is complicated by the open binding cleft of the MHC class II molecule, allowing binding of peptides extending out of the binding groove. Furthermore, only a few HLA-DR alleles have been characterized with a sufficient number of peptides (100-200 peptides per allele to derive accurate description of their binding motif. Little work has been performed characterizing structural properties of MHC class II ligands. Here, we perform one such large-scale analysis. A large set of SYFPEITHI MHC class II ligands covering more than 20 different HLA-DR molecules was analyzed in terms of their secondary structure and surface exposure characteristics in the context of the native structure of the corresponding source protein. We demonstrated that MHC class II ligands are significantly more exposed and have significantly more coil content than other peptides in the same protein with similar predicted binding affinity. We next exploited this observation to derive an improved prediction method for MHC class II ligands by integrating prediction of MHC- peptide binding with prediction of surface exposure and protein secondary structure. This combined prediction method was shown to significantly outperform the state-of-the-art MHC class II peptide binding prediction method when used to identify MHC class II ligands. We also tried to integrate N- and O-glycosylation in our prediction methods but this additional information was found not to improve prediction performance. In summary, these findings strongly suggest that local structural properties influence antigen processing and/or the accessibility of peptides to the MHC class II molecule.

  15. GC content around splice sites affects splicing through pre-mRNA secondary structures

    Directory of Open Access Journals (Sweden)

    Chen Liang

    2011-01-01

    Full Text Available Abstract Background Alternative splicing increases protein diversity by generating multiple transcript isoforms from a single gene through different combinations of exons or through different selections of splice sites. It has been reported that RNA secondary structures are involved in alternative splicing. Here we perform a genomic study of RNA secondary structures around splice sites in humans (Homo sapiens, mice (Mus musculus, fruit flies (Drosophila melanogaster, and nematodes (Caenorhabditis elegans to further investigate this phenomenon. Results We observe that GC content around splice sites is closely associated with the splice site usage in multiple species. RNA secondary structure is the possible explanation, because the structural stability difference among alternative splice sites, constitutive splice sites, and skipped splice sites can be explained by the GC content difference. Alternative splice sites tend to be GC-enriched and exhibit more stable RNA secondary structures in all of the considered species. In humans and mice, splice sites of first exons and long exons tend to be GC-enriched and hence form more stable structures, indicating the special role of RNA secondary structures in promoter proximal splicing events and the splicing of long exons. In addition, GC-enriched exon-intron junctions tend to be overrepresented in tissue-specific alternative splice sites, indicating the functional consequence of the GC effect. Compared with regions far from splice sites and decoy splice sites, real splice sites are GC-enriched. We also found that the GC-content effect is much stronger than the nucleotide-order effect to form stable secondary structures. Conclusion All of these results indicate that GC content is related to splice site usage and it may mediate the splicing process through RNA secondary structures.

  16. Including RNA secondary structures improves accuracy and robustness in reconstruction of phylogenetic trees

    Directory of Open Access Journals (Sweden)

    Dandekar Thomas

    2010-01-01

    Full Text Available Abstract Background In several studies, secondary structures of ribosomal genes have been used to improve the quality of phylogenetic reconstructions. An extensive evaluation of the benefits of secondary structure, however, is lacking. Results This is the first study to counter this deficiency. We inspected the accuracy and robustness of phylogenetics with individual secondary structures by simulation experiments for artificial tree topologies with up to 18 taxa and for divergency levels in the range of typical phylogenetic studies. We chose the internal transcribed spacer 2 of the ribosomal cistron as an exemplary marker region. Simulation integrated the coevolution process of sequences with secondary structures. Additionally, the phylogenetic power of marker size duplication was investigated and compared with sequence and sequence-structure reconstruction methods. The results clearly show that accuracy and robustness of Neighbor Joining trees are largely improved by structural information in contrast to sequence only data, whereas a doubled marker size only accounts for robustness. Conclusions Individual secondary structures of ribosomal RNA sequences provide a valuable gain of information content that is useful for phylogenetics. Thus, the usage of ITS2 sequence together with secondary structure for taxonomic inferences is recommended. Other reconstruction methods as maximum likelihood, bayesian inference or maximum parsimony may equally profit from secondary structure inclusion. Reviewers This article was reviewed by Shamil Sunyaev, Andrea Tanzer (nominated by Frank Eisenhaber and Eugene V. Koonin. Open peer review Reviewed by Shamil Sunyaev, Andrea Tanzer (nominated by Frank Eisenhaber and Eugene V. Koonin. For the full reviews, please go to the Reviewers' comments section.

  17. Porous carbonaceous electrode structure and method for secondary electrochemical cell

    Science.gov (United States)

    Kaun, Thomas D.

    1977-03-08

    Positive and negative electrodes are provided as rigid, porous carbonaceous matrices with particulate active material fixedly embedded. Active material such as metal chalcogenides, solid alloys of alkali metal or alkaline earth metals along with other metals and their oxides in particulate form are blended with a thermosetting resin and a solid volatile to form a paste mixture. Various electrically conductive powders or current collector structures can be blended or embedded into the paste mixture which can be molded to the desired electrode shape. The molded paste is heated to a temperature at which the volatile transforms into vapor to impart porosity as the resin begins to cure into a rigid solid structure.

  18. Irradiation effects on secondary structure of protein induced by keV ions

    International Nuclear Information System (INIS)

    Cui, F.Z.; Lin, Y.B.; Zhang, D.M.; Tian, M.B.

    2001-01-01

    Protein secondary structure changes by low-energy ion irradiation are reported for the first time. The selected system is 30 keV N + irradiation on bovine serum albumin (BSA). After irradiation at increasing fluences from 1.0x10 15 to 2.5x10 16 ion/cm 2 , Fourier transform infrared spectra analysis was conducted. It was found that the secondary structures of BSA molecules were very sensitive to ion irradiation. Secondary conformations showed different trends of change during irradiation. With the increase of ion fluence from 0 to 2.5x10 16 ion/cm 2 , the fraction of α-helix and β-turns decreased from 17 to 12%, and from 40 to 31%, respectively, while that of random coil and β-sheet structure increased from 18 to 27%, and from 25 to 30%, respectively. Possible explanations for the secondary conformational changes of protein are proposed. (author)

  19. QCD dipole prediction for dis and diffractive structure functions

    International Nuclear Information System (INIS)

    Royon, CH.

    1996-01-01

    The F 2 , F G , R = F L /F T proton structure functions are derived in the QCD dipole picture of BFKL dynamics. We get a three parameter fit describing the 1994 H1 proton structure function F 2 data in the low x, moderate Q 2 range. Without any additional parameter, the gluon density and the longitudinal structure functions are predicted. The diffractive dissociation processes are also discussed, and a new prediction for the proton diffractive structure function is obtained. (author)

  20. Secondary Structure Adopted by the Gly-Gly-X Repetitive Regions of Dragline Spider Silk

    Directory of Open Access Journals (Sweden)

    Geoffrey M. Gray

    2016-12-01

    Full Text Available Solid-state NMR and molecular dynamics (MD simulations are presented to help elucidate the molecular secondary structure of poly(Gly-Gly-X, which is one of the most common structural repetitive motifs found in orb-weaving dragline spider silk proteins. The combination of NMR and computational experiments provides insight into the molecular secondary structure of poly(Gly-Gly-X segments and provides further support that these regions are disordered and primarily non-β-sheet. Furthermore, the combination of NMR and MD simulations illustrate the possibility for several secondary structural elements in the poly(Gly-Gly-X regions of dragline silks, including β-turns, 310-helicies, and coil structures with a negligible population of α-helix observed.

  1. Secondary structure of 5S RNA: NMR experiments on RNA molecules partially labeled with Nitrogen-15

    International Nuclear Information System (INIS)

    Gewirth, D.T.; Abo, S.R.; Leontis, N.B.; Moore, P.B.

    1987-01-01

    A method has been found for reassembling fragment 1 of Escherichia coli 5S RNA from mixtures containing strand III (bases 69-87) and the complex consisting of strand II (bases 89-120) and strand IV (bases 1-11). The reassembled molecule is identical with unreconstituted fragment 1. With this technique, fragment 1 molecules have been constructed 15 N-labeled either in strand III or in the strand II-strand IV complex. Spectroscopic data obtained with these partially labeled molecules show that the terminal helix of 5S RNA includes the GU and GC base pairs at positions 9 and 10 which the standard model for 5S secondary structure predicts but that these base pairs are unstable both in the fragment and in native 5S RNA. The data also assign three resonances to the helix V region of the molecule (bases 70-77 and 99-106). None of these resonances has a normal chemical shift even though two of them correspond to AU or GU base pairs in the standard model. The implications of these findings for the authors understanding of the structure of 5S RNA and its complex with ribosomal protein L25 are discussed

  2. CSI 3.0: a web server for identifying secondary and super-secondary structure in proteins using NMR chemical shifts.

    Science.gov (United States)

    Hafsa, Noor E; Arndt, David; Wishart, David S

    2015-07-01

    The Chemical Shift Index or CSI 3.0 (http://csi3.wishartlab.com) is a web server designed to accurately identify the location of secondary and super-secondary structures in protein chains using only nuclear magnetic resonance (NMR) backbone chemical shifts and their corresponding protein sequence data. Unlike earlier versions of CSI, which only identified three types of secondary structure (helix, β-strand and coil), CSI 3.0 now identifies total of 11 types of secondary and super-secondary structures, including helices, β-strands, coil regions, five common β-turns (type I, II, I', II' and VIII), β hairpins as well as interior and edge β-strands. CSI 3.0 accepts experimental NMR chemical shift data in multiple formats (NMR Star 2.1, NMR Star 3.1 and SHIFTY) and generates colorful CSI plots (bar graphs) and secondary/super-secondary structure assignments. The output can be readily used as constraints for structure determination and refinement or the images may be used for presentations and publications. CSI 3.0 uses a pipeline of several well-tested, previously published programs to identify the secondary and super-secondary structures in protein chains. Comparisons with secondary and super-secondary structure assignments made via standard coordinate analysis programs such as DSSP, STRIDE and VADAR on high-resolution protein structures solved by X-ray and NMR show >90% agreement between those made with CSI 3.0. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

  3. CSSI-PRO: a method for secondary structure type editing, assignment and estimation in proteins using linear combination of backbone chemical shifts

    International Nuclear Information System (INIS)

    Swain, Monalisa; Atreya, Hanudatta S.

    2009-01-01

    Estimation of secondary structure in polypeptides is important for studying their structure, folding and dynamics. In NMR spectroscopy, such information is generally obtained after sequence specific resonance assignments are completed. We present here a new methodology for assignment of secondary structure type to spin systems in proteins directly from NMR spectra, without prior knowledge of resonance assignments. The methodology, named Combination of Shifts for Secondary Structure Identification in Proteins (CSSI-PRO), involves detection of specific linear combination of backbone 1 H α and 13 C' chemical shifts in a two-dimensional (2D) NMR experiment based on G-matrix Fourier transform (GFT) NMR spectroscopy. Such linear combinations of shifts facilitate editing of residues belonging to α-helical/β-strand regions into distinct spectral regions nearly independent of the amino acid type, thereby allowing the estimation of overall secondary structure content of the protein. Comparison of the predicted secondary structure content with those estimated based on their respective 3D structures and/or the method of Chemical Shift Index for 237 proteins gives a correlation of more than 90% and an overall rmsd of 7.0%, which is comparable to other biophysical techniques used for structural characterization of proteins. Taken together, this methodology has a wide range of applications in NMR spectroscopy such as rapid protein structure determination, monitoring conformational changes in protein-folding/ligand-binding studies and automated resonance assignment

  4. Examination of factors predicting secondary students' interest in tertiary STEM education

    Science.gov (United States)

    Chachashvili-Bolotin, Svetlana; Milner-Bolotin, Marina; Lissitsa, Sabina

    2016-02-01

    Based on the Social Cognitive Career Theory (SCCT), the study aims to investigate factors that predict students' interest in pursuing science, technology, engineering, and mathematics (STEM) fields in tertiary education both in general and in relation to their gender and socio-economic background. The results of the analysis of survey responses of 2458 secondary public school students in the fifth-largest Israeli city indicate that STEM learning experience positively associates with students' interest in pursuing STEM fields in tertiary education as opposed to non-STEM fields. Moreover, studying advanced science courses at the secondary school level decreases (but does not eliminate) the gender gap and eliminates the effect of family background on students' interest in pursuing STEM fields in the future. Findings regarding outcome expectations and self-efficacy beliefs only partially support the SCCT model. Outcome expectations and self-efficacy beliefs positively correlate with students' entering tertiary education but did not differentiate between their interests in the fields of study.

  5. A crystal structure prediction enigma solved

    DEFF Research Database (Denmark)

    Hoser, Anna Agnieszka; Sovago, Ioana; Lanzac, A.

    2017-01-01

    The seemingly unpredictable structure of gallic acid monohydrate form IV has been investigated using accurate X-ray diffraction measurements at temperatures of 10 and 123 K. The measurements demonstrate that the structure is commensurately modulated at 10 K and disordered at higher temperatures...

  6. Predicting Career Advancement with Structural Equation Modelling

    Science.gov (United States)

    Heimler, Ronald; Rosenberg, Stuart; Morote, Elsa-Sofia

    2012-01-01

    Purpose: The purpose of this paper is to use the authors' prior findings concerning basic employability skills in order to determine which skills best predict career advancement potential. Design/methodology/approach: Utilizing survey responses of human resource managers, the employability skills showing the largest relationships to career…

  7. Predictive models for deposit accumulation and corrosion on secondary side of steam generators

    International Nuclear Information System (INIS)

    Choi, Samuel; Moroney, Velvet; Marks, Chuck; Kreider, Marc

    2012-09-01

    Experience demonstrates that deposit accumulation in steam generators (SGs) can lead to corrosion of tubes. To minimize the probability of this corrosion, utilities employ a variety of deposit control strategies. However, these processes can involve significant costs and potentially affect outage critical paths. Since there has been no model that quantifies tube degradation as a function of deposit accumulation, utilities have had to make decisions regarding deposit control strategies without a reliable quantitative basis. The objective of this study is to develop methods that utilities can use to quantify benefits of SG deposit control strategies with regard to rates of secondary-side tube corrosion. Two different methodologies are employed in this work. The first methodology is empirical and is involved an attempt to correlate degradation rates with deposit accumulation as indicated by sludge pile height. Because there has been relatively little tube degradation in currently operating steam generators, this correlation is developed using data for Alloy 600MA SG tubes. To increase the number of units that could be used for defect/deposit correlations, a method to relate the sludge pile deposit mass and the number of tubes with non-zero sludge height is developed. The second methodology is theoretical and is based on the use of calculated differences in temperature and chemistry to predict the effect of deposits on corrosion rates. Computational fluid dynamics (CFD) models are developed to simulate thermal-hydraulic conditions representative of conditions that are present within porous deposits formed at the top of tube sheet. This paper will discuss the development and application of the predictive models for deposit accumulation and corrosion on the secondary side of steam generators. (authors)

  8. Prediction of concrete strength in massive structures

    International Nuclear Information System (INIS)

    Sakamoto, T.; Makino, H.; Nakane, S.; Kawaguchi, T.; Ohike, T.

    1989-01-01

    Reinforced concrete structures of a nuclear power plant are mostly of mass concrete with cross-sectional dimensions larger than 1.0 m. The temperature of concrete inside after placement rises due to heat of hydration of cement. It is well known that concrete strengths of mass concrete structure subjected to such temperature hysteresis are generally not equal to strengths of cylinders subjected to standard curing. In order to construct a mass concrete structure of high reliability in which the specified concrete strength is satisfied by the specified age, it is necessary to have a thorough understanding of the strength gain property of concrete in the structure and its relationships with the water-cement ratio of the mix, strength of standard-cured cylinders and the internal temperature hysteresis. This report describes the result of studies on methods of controlling concrete strength in actual construction projects

  9. Secondary flow structures under stent-induced perturbations for cardiovascular flow in a curved artery model

    International Nuclear Information System (INIS)

    Glenn, Autumn L.; Bulusu, Kartik V.; Shu Fangjun; Plesniak, Michael W.

    2012-01-01

    Secondary flows within curved arteries with unsteady forcing result from amplified centrifugal instabilities and are expected to be driven by the rapid accelerations and decelerations inherent in physiological waveforms. These secondary flows may also affect the function of curved arteries through pro-atherogenic wall shear stresses, platelet residence time and other vascular response mechanisms. Planar PIV measurements were performed under multi-harmonic non-zero-mean and physiological carotid artery waveforms at various locations in a rigid bent-pipe curved artery model. Results revealed symmetric counter-rotating vortex pairs that developed during the acceleration phases of both multi-harmonic and physiological waveforms. An idealized stent model was placed upstream of the bend, which initiated flow perturbations under physiological inflow conditions. Changes in the secondary flow structures were observed during the systolic deceleration phase (t/T ≈ 0.20–0.50). Proper Orthogonal Decomposition (POD) analysis of the flow morphologies under unsteady conditions indicated similarities in the coherent secondary-flow structures and correlation with phase-averaged velocity fields. A regime map was created that characterizes the kaleidoscope of vortical secondary flows with multiple vortex pairs and interesting secondary flow morphologies. This regime map in the curved artery model was created by plotting the secondary Reynolds number against another dimensionless acceleration-based parameter marking numbered regions of vortex pairs.

  10. Secondary flow structures under stent-induced perturbations for cardiovascular flow in a curved artery model

    Energy Technology Data Exchange (ETDEWEB)

    Glenn, Autumn L.; Bulusu, Kartik V. [Department of Mechanical and Aerospace Engineering, George Washington University, 801 22nd Street, NW., Washington, DC 20052 (United States); Shu Fangjun [Department of Mechanical and Aerospace Engineering, New Mexico State University, MSC 3450, P.O. Box 30001, Las Cruces, NM 88003-8001 (United States); Plesniak, Michael W., E-mail: plesniak@gwu.edu [Department of Mechanical and Aerospace Engineering, George Washington University, 801 22nd Street, NW., Washington, DC 20052 (United States)

    2012-06-15

    Secondary flows within curved arteries with unsteady forcing result from amplified centrifugal instabilities and are expected to be driven by the rapid accelerations and decelerations inherent in physiological waveforms. These secondary flows may also affect the function of curved arteries through pro-atherogenic wall shear stresses, platelet residence time and other vascular response mechanisms. Planar PIV measurements were performed under multi-harmonic non-zero-mean and physiological carotid artery waveforms at various locations in a rigid bent-pipe curved artery model. Results revealed symmetric counter-rotating vortex pairs that developed during the acceleration phases of both multi-harmonic and physiological waveforms. An idealized stent model was placed upstream of the bend, which initiated flow perturbations under physiological inflow conditions. Changes in the secondary flow structures were observed during the systolic deceleration phase (t/T Almost-Equal-To 0.20-0.50). Proper Orthogonal Decomposition (POD) analysis of the flow morphologies under unsteady conditions indicated similarities in the coherent secondary-flow structures and correlation with phase-averaged velocity fields. A regime map was created that characterizes the kaleidoscope of vortical secondary flows with multiple vortex pairs and interesting secondary flow morphologies. This regime map in the curved artery model was created by plotting the secondary Reynolds number against another dimensionless acceleration-based parameter marking numbered regions of vortex pairs.

  11. Can Morphing Methods Predict Intermediate Structures?

    Science.gov (United States)

    Weiss, Dahlia R.; Levitt, Michael

    2009-01-01

    Movement is crucial to the biological function of many proteins, yet crystallographic structures of proteins can give us only a static snapshot. The protein dynamics that are important to biological function often happen on a timescale that is unattainable through detailed simulation methods such as molecular dynamics as they often involve crossing high-energy barriers. To address this coarse-grained motion, several methods have been implemented as web servers in which a set of coordinates is usually linearly interpolated from an initial crystallographic structure to a final crystallographic structure. We present a new morphing method that does not extrapolate linearly and can therefore go around high-energy barriers and which can produce different trajectories between the same two starting points. In this work, we evaluate our method and other established coarse-grained methods according to an objective measure: how close a coarse-grained dynamics method comes to a crystallographically determined intermediate structure when calculating a trajectory between the initial and final crystal protein structure. We test this with a set of five proteins with at least three crystallographically determined on-pathway high-resolution intermediate structures from the Protein Data Bank. For simple hinging motions involving a small conformational change, segmentation of the protein into two rigid sections outperforms other more computationally involved methods. However, large-scale conformational change is best addressed using a nonlinear approach and we suggest that there is merit in further developing such methods. PMID:18996395

  12. Detection of secondary structure elements in proteins by hydrophobic cluster analysis.

    Science.gov (United States)

    Woodcock, S; Mornon, J P; Henrissat, B

    1992-10-01

    Hydrophobic cluster analysis (HCA) is a protein sequence comparison method based on alpha-helical representations of the sequences where the size, shape and orientation of the clusters of hydrophobic residues are primarily compared. The effectiveness of HCA has been suggested to originate from its potential ability to focus on the residues forming the hydrophobic core of globular proteins. We have addressed the robustness of the bidimensional representation used for HCA in its ability to detect the regular secondary structure elements of proteins. Various parameters have been studied such as those governing cluster size and limits, the hydrophobic residues constituting the clusters as well as the potential shift of the cluster positions with respect to the position of the regular secondary structure elements. The following results have been found to support the alpha-helical bidimensional representation used in HCA: (i) there is a positive correlation (clearly above background noise) between the hydrophobic clusters and the regular secondary structure elements in proteins; (ii) the hydrophobic clusters are centred on the regular secondary structure elements; (iii) the pitch of the helical representation which gives the best correspondence is that of an alpha-helix. The correspondence between hydrophobic clusters and regular secondary structure elements suggests a way to implement variable gap penalties during the automatic alignment of protein sequences.

  13. Primary and secondary structure of U8 small nuclear RNA

    International Nuclear Information System (INIS)

    Reddy, R.; Henning, D.; Busch, H.

    1985-01-01

    U8 small nuclear RNA is a new, capped, 140 nucleotides long RNA species found in Novikoff hepatoma cells. Its sequence is: m3GpppAmUmCGUCAGGA GGUUAAUCCU UACCUGUCCC UCCUUUCGGA GGGCAGAUAG AAAAUGAUGA UUGGAGCUUG CAUGAUCUGC UGAUUAUAGC AUUUCCGUGU AAUCAGGACC UGACAACAUC CUGAUUGCUU CUAUCUGAUUOH. This RNA is present in approximately 25,000 copies/cell, and it is enriched in nucleolar preparations. Like U1, U2, U4/U6, and U5 RNAs, U8 RNA was also present as a ribonucleoprotein associated with the Sm antigen. The rat U8 RNA was highly homologous (greater than 90%) to a recently characterized 5.4 S RNA from mouse cells infected with spleen focus-forming virus. In addition to the U8 RNA, three other U small nuclear RNAs were found in anti-Sm antibody immunoprecipitates from labeled rat and HeLa cells. Each of these contained a m3GpppAm cap structure; their apparent chain lengths were 60, 130, and 65 nucleotides. These U small nuclear RNAs are designated U7, U9, and U10 RNAs, respectively

  14. THE PECULIARITIES OF NICKNAME STRUCTURE IN THE VICINITY OF VELIUONA: SECONDARY NICKNAMES

    Directory of Open Access Journals (Sweden)

    Ilona Mickienė

    2014-10-01

    Full Text Available The paper analyses 782 nicknames that were recorded at Veliuona vicinity during the project of the Institute of the Lithuanian Language “Modern Research of Geolinguistics in Lithuania: Optimisation of Network of Points and Interactive Spread of Dialectal Information”. The paper aims to identify the characteristic attributes of nickname structure. The analysis of the relations in derivation, i. e., tentatively distinguishing the derivation base and formant is the only way to talk about common word derivation. While researching the nicknames it is difficult to find such a universal criterion in derivation which would enable the distribution of nicknames into the primary and the secondary ones due to the fact that when a nickname and its appellative derivation motivation coincides the confusion arises. Thus, the paper invokes the structural analysis of nicknames to find universal criteria that would enable the distinction of nicknames into the primary and the secondary. The article eliminates the primary nicknames that do not differ from the motivational word, 241 secondary nickname is being researched ant structurally analysed. The structural analysis discloses a proper structure and common words being selected for nickname creation. Structurally analysing the secondary nicknames, the nicknames with suffix, inflection, mixed structure, compound, composite and phrasal nicknames were distinguished. It was determined that in vacinity of Veliuona the nicknames with suffix and inflection are mostly used.

  15. Characterization and visualization of RNA secondary structure Boltzmann ensemble via information theory.

    Science.gov (United States)

    Lin, Luan; McKerrow, Wilson H; Richards, Bryce; Phonsom, Chukiat; Lawrence, Charles E

    2018-03-05

    The nearest neighbor model and associated dynamic programming algorithms allow for the efficient estimation of the RNA secondary structure Boltzmann ensemble. However because a given RNA secondary structure only contains a fraction of the possible helices that could form from a given sequence, the Boltzmann ensemble is multimodal. Several methods exist for clustering structures and finding those modes. However less focus is given to exploring the underlying reasons for this multimodality: the presence of conflicting basepairs. Information theory, or more specifically mutual information, provides a method to identify those basepairs that are key to the secondary structure. To this end we find most informative basepairs and visualize the effect of these basepairs on the secondary structure. Knowing whether a most informative basepair is present tells us not only the status of the particular pair but also provides a large amount of information about which other pairs are present or not present. We find that a few basepairs account for a large amount of the structural uncertainty. The identification of these pairs indicates small changes to sequence or stability that will have a large effect on structure. We provide a novel algorithm that uses mutual information to identify the key basepairs that lead to a multimodal Boltzmann distribution. We then visualize the effect of these pairs on the overall Boltzmann ensemble.

  16. Determination of Endosperm Protein Secondary Structure in Hard Wheat Breeding Lines using Synchrotron Infrared Microspectroscopy

    International Nuclear Information System (INIS)

    Bonwell, E.; Fisher, T.; Fritz, A.; Wetzel, D.

    2008-01-01

    One molecular aspect of mature hard wheat protein quality for breadmaking is the relative amount of endosperm protein in the a-helix form compared with that in other secondary structure forms including β-sheet. Modeling of a-helix and β-sheet absorption bands that contribute to the amide I band at 1650 cm-1 was applied to more than 1500 spectra in this study. The microscopic view of wheat endosperm is dominated by many large starch granules with protein in between. The spectrum produced from in situ microspectroscopy of this mixture is dominated by carbohydrate bands from the large starch granules that fill up the field. The high spatial resolution achievable with synchrotron infrared microspectroscopy enables revealing good in situ spectra of the protein located interstitially. Synchrotron infrared microspectroscopic mapping of 4 μm thick frozen sections of endosperm in the subaleurone region provides spectra from a large number of pixels. Pixels with protein-dominated spectra are sorted out from among adjacent pixels to minimize the starch absorption and scattering contributions. Subsequent data treatment to extract information from the amide I band requires a high signal to noise ratio. Although spectral interference of the carbohydrate band on the amide band is not a problem, the scattering produced by the large starch granules diminishes the signal to noise ratio throughout the spectrum. High density mapping was done on beamlines U2B and U10B at the National Synchrotron Light Source at Brookhaven National Laboratory, Upton, NY. Mapping with a single masked spot size of 5.5 μm diameter or confocal 5 μm x 5 μm spot size, respectively, on the two beamlines used produced spectra for new breeding lines under current consideration. Appropriate data treatment allows calculation of a numerical estimate of the a-helix population relative to other secondary protein structures from the position and shape of the amide I absorption band. Current breeding lines show a

  17. VITAL NMR: using chemical shift derived secondary structure information for a limited set of amino acids to assess homology model accuracy

    Energy Technology Data Exchange (ETDEWEB)

    Brothers, Michael C.; Nesbitt, Anna E.; Hallock, Michael J. [University of Illinois at Urbana-Champaign, Department of Chemistry (United States); Rupasinghe, Sanjeewa G. [University of Illinois at Urbana-Champaign, Department of Cell and Developmental Biology (United States); Tang Ming [University of Illinois at Urbana-Champaign, Department of Chemistry (United States); Harris, Jason; Baudry, Jerome [University of Tennessee, Department of Biochemistry, Cellular and Molecular Biology (United States); Schuler, Mary A. [University of Illinois at Urbana-Champaign, Department of Cell and Developmental Biology (United States); Rienstra, Chad M., E-mail: rienstra@illinois.edu [University of Illinois at Urbana-Champaign, Department of Chemistry (United States)

    2012-01-15

    Homology modeling is a powerful tool for predicting protein structures, whose success depends on obtaining a reasonable alignment between a given structural template and the protein sequence being analyzed. In order to leverage greater predictive power for proteins with few structural templates, we have developed a method to rank homology models based upon their compliance to secondary structure derived from experimental solid-state NMR (SSNMR) data. Such data is obtainable in a rapid manner by simple SSNMR experiments (e.g., {sup 13}C-{sup 13}C 2D correlation spectra). To test our homology model scoring procedure for various amino acid labeling schemes, we generated a library of 7,474 homology models for 22 protein targets culled from the TALOS+/SPARTA+ training set of protein structures. Using subsets of amino acids that are plausibly assigned by SSNMR, we discovered that pairs of the residues Val, Ile, Thr, Ala and Leu (VITAL) emulate an ideal dataset where all residues are site specifically assigned. Scoring the models with a predicted VITAL site-specific dataset and calculating secondary structure with the Chemical Shift Index resulted in a Pearson correlation coefficient (-0.75) commensurate to the control (-0.77), where secondary structure was scored site specifically for all amino acids (ALL 20) using STRIDE. This method promises to accelerate structure procurement by SSNMR for proteins with unknown folds through guiding the selection of remotely homologous protein templates and assessing model quality.

  18. VITAL NMR: Using Chemical Shift Derived Secondary Structure Information for a Limited Set of Amino Acids to Assess Homology Model Accuracy

    Energy Technology Data Exchange (ETDEWEB)

    Brothers, Michael C [University of Illinois, Urbana-Champaign; Nesbitt, Anna E [University of Illinois, Urbana-Champaign; Hallock, Michael J [University of Illinois, Urbana-Champaign; Rupasinghe, Sanjeewa [University of Illinois, Urbana-Champaign; Tang, Ming [University of Illinois, Urbana-Champaign; Harris, Jason B [ORNL; Baudry, Jerome Y [ORNL; Schuler, Mary A [University of Illinois, Urbana-Champaign; Rienstra, Chad M [University of Illinois, Urbana-Champaign

    2011-01-01

    Homology modeling is a powerful tool for predicting protein structures, whose success depends on obtaining a reasonable alignment between a given structural template and the protein sequence being analyzed. In order to leverage greater predictive power for proteins with few structural templates, we have developed a method to rank homology models based upon their compliance to secondary structure derived from experimental solid-state NMR (SSNMR) data. Such data is obtainable in a rapid manner by simple SSNMR experiments (e.g., (13)C-(13)C 2D correlation spectra). To test our homology model scoring procedure for various amino acid labeling schemes, we generated a library of 7,474 homology models for 22 protein targets culled from the TALOS+/SPARTA+ training set of protein structures. Using subsets of amino acids that are plausibly assigned by SSNMR, we discovered that pairs of the residues Val, Ile, Thr, Ala and Leu (VITAL) emulate an ideal dataset where all residues are site specifically assigned. Scoring the models with a predicted VITAL site-specific dataset and calculating secondary structure with the Chemical Shift Index resulted in a Pearson correlation coefficient (-0.75) commensurate to the control (-0.77), where secondary structure was scored site specifically for all amino acids (ALL 20) using STRIDE. This method promises to accelerate structure procurement by SSNMR for proteins with unknown folds through guiding the selection of remotely homologous protein templates and assessing model quality.

  19. QCD dipole predictions for DIS and diffractive structure functions

    International Nuclear Information System (INIS)

    Royon, C.

    1997-01-01

    The proton structure function F 2 , the gluon density F G , and the longitudinal structure function F L are derived in the QCD dipole picture of BFKL dynamics. We use a three parameter fit to describe the 1994 H1 proton structure function F 2 data in the low x, moderate Q 2 range. Without any additional parameter, the gluon density and the longitudinal structure functions are predicted. The diffractive dissociation processes are also discussed within the same framework, and a new prediction for the proton diffractive structure function is obtained

  20. The secondary structure and the thermal unfolding parameters of the S-layer protein from Lactobacillus salivarius.

    Science.gov (United States)

    Lighezan, Liliana; Georgieva, Ralitsa; Neagu, Adrian

    2016-09-01

    Surface layer (S-layer) proteins have been identified in the cell envelope of many organisms, such as bacteria and archaea. They self-assemble, forming monomolecular crystalline arrays. Isolated S-layer proteins are able to recrystallize into regular lattices, which proved useful in biotechnology. Here we investigate the structure and thermal unfolding of the S-layer protein isolated from Lactobacillus salivarius 16 strain of human origin. Using circular dichroism (CD) spectroscopy, and the software CDSSTR from DICHROWEB, CONTINLL from CDPro, as well as CDNN, we assess the fractions of the protein's secondary structural elements at temperatures ranging between 10 and 90 °C, and predict the tertiary class of the protein. To study the thermal unfolding of the protein, we analyze the temperature dependence of the CD signal in the far- and near-UV domains. Fitting the experimental data by two- and three-state models of thermal unfolding, we infer the midpoint temperatures, the temperature dependence of the changes in Gibbs free energy, enthalpy, and entropy of the unfolding transitions in standard conditions, and the temperature dependence of the equilibrium constant. We also estimate the changes in heat capacity at constant pressure in standard conditions. The results indicate that the thermal unfolding of the S-layer protein from L. salivarius is highly cooperative, since changes in the secondary and tertiary structures occur simultaneously. The thermodynamic analysis predicts a "cold" transition, at about -3 °C, of both the secondary and tertiary structures. Our findings may be important for the use of S-layer proteins in biotechnology and in biomedical applications.

  1. Secondary metabolites of Mirabilis jalapa structurally inhibit Lactate Dehydrogenase A in silico: a potential cancer treatment

    Science.gov (United States)

    Kusumawati, R.; Nasrullah, A. H.; Pesik, R. N.; Muthmainah; Indarto, D.

    2018-03-01

    Altered energy metabolism from phosphorylated oxidation to aerobic glycolysis is one of the cancer hallmarks. Lactate dehydrogenase A (LDHA) is a major enzyme that catalyses pyruvate to lactate in such condition. The aim of this study was to explore LDHA inhibitors derived from Indonesian herbal plants. In this study, LDHA and oxamate molecular structures were obtained from protein data bank. As a standard ligand inhibitor, oxamate was molecularly re-validated using Autodock Vina 1.1.2 software and showed binding energy -4.26 ± 0.006 kcal/mol and interacted with LDHA at Gln99, Arg105, Asn137, Arg168, His192, and Thr247 residues. Molecular docking was used to visualize interaction between Indonesian phytochemicals and LDHA. Indonesian phytochemicals with the lowest binding energy and similar residues with standard ligand was Miraxanthin-III (-8.53 ± 0.006 kcal/mol), Vulgaxanthin-I (-8.46 ± 0.006 kcal/mol), Miraxanthin-II (-7.9 ± 0.2 kcal/mol) and Miraxanthin-V (-7.96 ± kcal/mol). Lower energy binding to LDHA and binding site at these residues was predicted to inhibit LDHA activity better than standard ligand. All phytochemicals were found in Mirabilis jalapa plant. Secondary metabolites in Mirabilis jalapa have LDHA inhibitor property in silico. Further in vitro study should be performed to confirm this result.

  2. Structure Prediction and Analysis of Neuraminidase Sequence Variants

    Science.gov (United States)

    Thayer, Kelly M.

    2016-01-01

    Analyzing protein structure has become an integral aspect of understanding systems of biochemical import. The laboratory experiment endeavors to introduce protein folding to ascertain structures of proteins for which the structure is unavailable, as well as to critically evaluate the quality of the prediction obtained. The model system used is the…

  3. QCD predictions for weak neutral current structure functions

    International Nuclear Information System (INIS)

    Wu Jimin

    1987-01-01

    Employing the analytic expression (to the next leading order) for non-singlet component of structure function which the author got from QCD theory and putting recent experiment result of neutral current structure function at Q 2 = 11 (GeV/C) 2 as input, the QCD prediction for neutral current structure function of their scaling violation behaviours was given

  4. Antibody structural modeling with prediction of immunoglobulin structure (PIGS)

    KAUST Repository

    Marcatili, Paolo; Olimpieri, Pier Paolo; Chailyan, Anna; Tramontano, Anna

    2014-01-01

    of antibodies with a very satisfactory accuracy. The strategy is completely automated and extremely fast, requiring only a few minutes (~10 min on average) to build a structural model of an antibody. It is based on the concept of canonical structures of antibody

  5. JABAWS 2.2 distributed web services for Bioinformatics: protein disorder, conservation and RNA secondary structure.

    Science.gov (United States)

    Troshin, Peter V; Procter, James B; Sherstnev, Alexander; Barton, Daniel L; Madeira, Fábio; Barton, Geoffrey J

    2018-06-01

    JABAWS 2.2 is a computational framework that simplifies the deployment of web services for Bioinformatics. In addition to the five multiple sequence alignment (MSA) algorithms in JABAWS 1.0, JABAWS 2.2 includes three additional MSA programs (Clustal Omega, MSAprobs, GLprobs), four protein disorder prediction methods (DisEMBL, IUPred, Ronn, GlobPlot), 18 measures of protein conservation as implemented in AACon, and RNA secondary structure prediction by the RNAalifold program. JABAWS 2.2 can be deployed on a variety of in-house or hosted systems. JABAWS 2.2 web services may be accessed from the Jalview multiple sequence analysis workbench (Version 2.8 and later), as well as directly via the JABAWS command line interface (CLI) client. JABAWS 2.2 can be deployed on a local virtual server as a Virtual Appliance (VA) or simply as a Web Application Archive (WAR) for private use. Improvements in JABAWS 2.2 also include simplified installation and a range of utility tools for usage statistics collection, and web services querying and monitoring. The JABAWS CLI client has been updated to support all the new services and allow integration of JABAWS 2.2 services into conventional scripts. A public JABAWS 2 server has been in production since December 2011 and served over 800 000 analyses for users worldwide. JABAWS 2.2 is made freely available under the Apache 2 license and can be obtained from: http://www.compbio.dundee.ac.uk/jabaws. g.j.barton@dundee.ac.uk.

  6. Two-dimensional dynamics of a free molecular chain with a secondary structure

    DEFF Research Database (Denmark)

    Zolotaryuk, Alexander; Christiansen, Peter Leth; Savin, A.V.

    1996-01-01

    A simple two-dimensional (2D) model of an isolated (free) molecular chain with primary and secondary structures has been suggested and investigated both analytically and numerically. This model can be considered as the simplest generalization of the well-known Fermi-Pasta-Ulam model of an anharmo......A simple two-dimensional (2D) model of an isolated (free) molecular chain with primary and secondary structures has been suggested and investigated both analytically and numerically. This model can be considered as the simplest generalization of the well-known Fermi-Pasta-Ulam model...

  7. Aromatic claw: A new fold with high aromatic content that evades structural prediction: Aromatic Claw

    Energy Technology Data Exchange (ETDEWEB)

    Sachleben, Joseph R. [Biomolecular NMR Core Facility, University of Chicago, Chicago Illinois; Adhikari, Aashish N. [Department of Chemistry, University of Chicago, Chicago Illinois; Gawlak, Grzegorz [Department of Biochemistry and Molecular Biology, University of Chicago, Chicago Illinois; Hoey, Robert J. [Department of Biochemistry and Molecular Biology, University of Chicago, Chicago Illinois; Liu, Gaohua [Northeast Structural Genomics Consortium (NESG), Department of Molecular Biology and Biochemistry, School of Arts and Sciences, and Department of Biochemistry and Molecular Biology, Robert Wood Johnson Medical School, and Center for Advanced Biotechnology and Medicine, Rutgers, The State University of New Jersey, Piscataway New Jersey; Joachimiak, Andrzej [Department of Biochemistry and Molecular Biology, University of Chicago, Chicago Illinois; Biological Sciences Division, Argonne National Laboratory, Argonne Illinois; Montelione, Gaetano T. [Northeast Structural Genomics Consortium (NESG), Department of Molecular Biology and Biochemistry, School of Arts and Sciences, and Department of Biochemistry and Molecular Biology, Robert Wood Johnson Medical School, and Center for Advanced Biotechnology and Medicine, Rutgers, The State University of New Jersey, Piscataway New Jersey; Sosnick, Tobin R. [Department of Biochemistry and Molecular Biology, University of Chicago, Chicago Illinois; Koide, Shohei [Department of Biochemistry and Molecular Biology, University of Chicago, Chicago Illinois; Department of Biochemistry and Molecular Pharmacology and the Perlmutter Cancer Center, New York University School of Medicine, New York New York

    2016-11-10

    We determined the NMR structure of a highly aromatic (13%) protein of unknown function, Aq1974 from Aquifex aeolicus (PDB ID: 5SYQ). The unusual sequence of this protein has a tryptophan content five times the normal (six tryptophan residues of 114 or 5.2% while the average tryptophan content is 1.0%) with the tryptophans occurring in a WXW motif. It has no detectable sequence homology with known protein structures. Although its NMR spectrum suggested that the protein was rich in β-sheet, upon resonance assignment and solution structure determination, the protein was found to be primarily α-helical with a small two-stranded β-sheet with a novel fold that we have termed an Aromatic Claw. As this fold was previously unknown and the sequence unique, we submitted the sequence to CASP10 as a target for blind structural prediction. At the end of the competition, the sequence was classified a hard template based model; the structural relationship between the template and the experimental structure was small and the predictions all failed to predict the structure. CSRosetta was found to predict the secondary structure and its packing; however, it was found that there was little correlation between CSRosetta score and the RMSD between the CSRosetta structure and the NMR determined one. This work demonstrates that even in relatively small proteins, we do not yet have the capacity to accurately predict the fold for all primary sequences. The experimental discovery of new folds helps guide the improvement of structural prediction methods.

  8. RNACompress: Grammar-based compression and informational complexity measurement of RNA secondary structure

    Directory of Open Access Journals (Sweden)

    Chen Chun

    2008-03-01

    Full Text Available Abstract Background With the rapid emergence of RNA databases and newly identified non-coding RNAs, an efficient compression algorithm for RNA sequence and structural information is needed for the storage and analysis of such data. Although several algorithms for compressing DNA sequences have been proposed, none of them are suitable for the compression of RNA sequences with their secondary structures simultaneously. This kind of compression not only facilitates the maintenance of RNA data, but also supplies a novel way to measure the informational complexity of RNA structural data, raising the possibility of studying the relationship between the functional activities of RNA structures and their complexities, as well as various structural properties of RNA based on compression. Results RNACompress employs an efficient grammar-based model to compress RNA sequences and their secondary structures. The main goals of this algorithm are two fold: (1 present a robust and effective way for RNA structural data compression; (2 design a suitable model to represent RNA secondary structure as well as derive the informational complexity of the structural data based on compression. Our extensive tests have shown that RNACompress achieves a universally better compression ratio compared with other sequence-specific or common text-specific compression algorithms, such as Gencompress, winrar and gzip. Moreover, a test of the activities of distinct GTP-binding RNAs (aptamers compared with their structural complexity shows that our defined informational complexity can be used to describe how complexity varies with activity. These results lead to an objective means of comparing the functional properties of heteropolymers from the information perspective. Conclusion A universal algorithm for the compression of RNA secondary structure as well as the evaluation of its informational complexity is discussed in this paper. We have developed RNACompress, as a useful tool

  9. Identifying secondary structures in proteins using NMR chemical shift 3D correlation maps

    Science.gov (United States)

    Kumari, Amrita; Dorai, Kavita

    2013-06-01

    NMR chemical shifts are accurate indicators of molecular environment and have been extensively used as aids in protein structure determination. This work focuses on creating empirical 3D correlation maps of backbone chemical shift nuclei for use as identifiers of secondary structure elements in proteins. A correlated database of backbone nuclei chemical shifts was constructed from experimental structural data gathered from entries in the Protein Data Bank (PDB) as well as isotropic chemical shift values from the RefDB database. Rigorous statistical analysis of the maps led to the conclusion that specific correlations between triplets of backbone chemical shifts are best able to differentiate between different secondary structures such as α-helices, β-strands and turns. The method is compared with similar techniques that use NMR chemical shift information as aids in biomolecular structure determination and performs well in tests done on experimental data determined for different types of proteins, including large multi-domain proteins and membrane proteins.

  10. FTIR study of secondary structure of bovine serum albumin and ovalbumin

    International Nuclear Information System (INIS)

    Abrosimova, K V; Shulenina, O V; Paston, S V

    2016-01-01

    Proteins structure is the critical factor for their functioning. Fourier transform infrared spectroscopy provides a possibility to obtain information about secondary structure of proteins in different states and also in a whole biological samples. Infrared spectra of egg white from the untreated and hard-boiled hen's egg, and also of chicken ovalbumin and bovine serum albumin in lyophilic form and in aqueous solution were studied. Lyophilization of investigated globular proteins is accompanied by the decrease of a-helix structures and the increase in amount of intermolecular β-sheets. Analysis of infrared spectrum of egg white allowed to make an estimation of OVA secondary structure and to observe α-to-β structural transformation as a result of the heat denaturation. (paper)

  11. EVA: continuous automatic evaluation of protein structure prediction servers.

    Science.gov (United States)

    Eyrich, V A; Martí-Renom, M A; Przybylski, D; Madhusudhan, M S; Fiser, A; Pazos, F; Valencia, A; Sali, A; Rost, B

    2001-12-01

    Evaluation of protein structure prediction methods is difficult and time-consuming. Here, we describe EVA, a web server for assessing protein structure prediction methods, in an automated, continuous and large-scale fashion. Currently, EVA evaluates the performance of a variety of prediction methods available through the internet. Every week, the sequences of the latest experimentally determined protein structures are sent to prediction servers, results are collected, performance is evaluated, and a summary is published on the web. EVA has so far collected data for more than 3000 protein chains. These results may provide valuable insight to both developers and users of prediction methods. http://cubic.bioc.columbia.edu/eva. eva@cubic.bioc.columbia.edu

  12. Predicting Secondary Agriculture Teachers' Job Stress from Selected Personal, Family, and Work-Related Characteristics

    Science.gov (United States)

    Torres, Robert M.; Lambert, Misty D.; Lawver, Rebecca G.

    2010-01-01

    The study sought to describe the characteristics and explain the current level of job stress among secondary agriculture teachers. The sample consisted of 370 secondary agriculture teachers. Data were collected using the Job Stress Survey (Spielberger & Vagg, 1999). From the findings it was concluded that the average secondary agriculture teacher…

  13. Predicting the glass transition temperature and viscosity of secondary organic material using molecular composition

    Directory of Open Access Journals (Sweden)

    W.-S. W. DeRieux

    2018-05-01

    Full Text Available Secondary organic aerosol (SOA accounts for a large fraction of submicron particles in the atmosphere. SOA can occur in amorphous solid or semi-solid phase states depending on chemical composition, relative humidity (RH, and temperature. The phase transition between amorphous solid and semi-solid states occurs at the glass transition temperature (Tg. We have recently developed a method to estimate Tg of pure compounds containing carbon, hydrogen, and oxygen atoms (CHO compounds with molar mass less than 450 g mol−1 based on their molar mass and atomic O : C ratio. In this study, we refine and extend this method for CH and CHO compounds with molar mass up to ∼ 1100 g mol−1 using the number of carbon, hydrogen, and oxygen atoms. We predict viscosity from the Tg-scaled Arrhenius plot of fragility (viscosity vs. Tg∕T as a function of the fragility parameter D. We compiled D values of organic compounds from the literature and found that D approaches a lower limit of ∼ 10 (±1.7 as the molar mass increases. We estimated the viscosity of α-pinene and isoprene SOA as a function of RH by accounting for the hygroscopic growth of SOA and applying the Gordon–Taylor mixing rule, reproducing previously published experimental measurements very well. Sensitivity studies were conducted to evaluate impacts of Tg, D, the hygroscopicity parameter (κ, and the Gordon–Taylor constant on viscosity predictions. The viscosity of toluene SOA was predicted using the elemental composition obtained by high-resolution mass spectrometry (HRMS, resulting in a good agreement with the measured viscosity. We also estimated the viscosity of biomass burning particles using the chemical composition measured by HRMS with two different ionization techniques: electrospray ionization (ESI and atmospheric pressure photoionization (APPI. Due to differences in detected organic compounds and signal intensity, predicted viscosities at low RH based on ESI and

  14. Predicting the glass transition temperature and viscosity of secondary organic material using molecular composition

    Science.gov (United States)

    Wong DeRieux, Wing-Sy; Li, Ying; Lin, Peng; Laskin, Julia; Laskin, Alexander; Bertram, Allan K.; Nizkorodov, Sergey A.; Shiraiwa, Manabu

    2018-05-01

    Secondary organic aerosol (SOA) accounts for a large fraction of submicron particles in the atmosphere. SOA can occur in amorphous solid or semi-solid phase states depending on chemical composition, relative humidity (RH), and temperature. The phase transition between amorphous solid and semi-solid states occurs at the glass transition temperature (Tg). We have recently developed a method to estimate Tg of pure compounds containing carbon, hydrogen, and oxygen atoms (CHO compounds) with molar mass less than 450 g mol-1 based on their molar mass and atomic O : C ratio. In this study, we refine and extend this method for CH and CHO compounds with molar mass up to ˜ 1100 g mol-1 using the number of carbon, hydrogen, and oxygen atoms. We predict viscosity from the Tg-scaled Arrhenius plot of fragility (viscosity vs. Tg/T) as a function of the fragility parameter D. We compiled D values of organic compounds from the literature and found that D approaches a lower limit of ˜ 10 (±1.7) as the molar mass increases. We estimated the viscosity of α-pinene and isoprene SOA as a function of RH by accounting for the hygroscopic growth of SOA and applying the Gordon-Taylor mixing rule, reproducing previously published experimental measurements very well. Sensitivity studies were conducted to evaluate impacts of Tg, D, the hygroscopicity parameter (κ), and the Gordon-Taylor constant on viscosity predictions. The viscosity of toluene SOA was predicted using the elemental composition obtained by high-resolution mass spectrometry (HRMS), resulting in a good agreement with the measured viscosity. We also estimated the viscosity of biomass burning particles using the chemical composition measured by HRMS with two different ionization techniques: electrospray ionization (ESI) and atmospheric pressure photoionization (APPI). Due to differences in detected organic compounds and signal intensity, predicted viscosities at low RH based on ESI and APPI measurements differ by 2-5 orders

  15. Effects prediction guidelines for structures subjected to ground motion

    International Nuclear Information System (INIS)

    1975-07-01

    Part of the planning for an underground nuclear explosion (UNE) is determining the effects of expected ground motion on exposed structures. Because of the many types of structures and the wide variation in ground motion intensity typically encountered, no single prediction method is both adequate and feasible for a complete evaluation. Furthermore, the nature and variability of ground motion and structure damage prescribe effects predictions that are made probabilistically. Initially, prediction for a UNE involves a preliminary assessment of damage to establish overall project feasibility. Subsequent efforts require more detailed damage evaluations, based on structure inventories and analyses of specific structures, so that safety problems can be identified and safety and remedial measures can be recommended. To cover this broad range of effects prediction needs for a typical UNE project, three distinct but interrelated methods have been developed and are described. First, the fundamental practical and theoretical aspects of predicting the effects of dynamic ground motion on structures are summarized. Next, experimentally derived and theoretically determined observations of the behavior of typical structures subjected to ground motion are presented. Then, based on these fundamental considerations and on the observed behavior of structures, the formulation of the three effects prediction procedures is described, along with guidelines regarding their applicability. Example damage predictions for hypothetical UNEs demonstrate these procedures. To aid in identifying the vibration properties of complex structures, one chapter discusses alternatives in vibration testing, instrumentation, and data analysis. Finally, operational guidelines regarding data acquisition procedures, safety criteria, and remedial measures involved in conducting structure effects evaluations are discussed. (U.S.)

  16. Mesoscopic structure prediction of nanoparticle assembly and coassembly: Theoretical foundation

    KAUST Repository

    Hur, Kahyun; Hennig, Richard G.; Escobedo, Fernando A.; Wiesner, Ulrich

    2010-01-01

    structures and interactions. We validate our approach by comparing its predictions with previous simulation results for model systems. We illustrate the flexibility of our approach by applying it to hybrid systems composed of block copolymers and ligand

  17. Framework for Structural Online Health Monitoring of Aging and Degradation of Secondary Systems due to some Aspects of Erosion

    Energy Technology Data Exchange (ETDEWEB)

    Gribok, Andrei [Idaho National Lab. (INL), Idaho Falls, ID (United States); Patnaik, Sobhan [Idaho National Lab. (INL), Idaho Falls, ID (United States); Williams, Christian [Idaho National Lab. (INL), Idaho Falls, ID (United States); Pattanaik, Marut [Idaho National Lab. (INL), Idaho Falls, ID (United States); Kanakala, Raghunath [Idaho National Lab. (INL), Idaho Falls, ID (United States)

    2016-09-01

    This report describes the current state of research related to critical aspects of erosion and selected aspects of degradation of secondary components in nuclear power plants. The report also proposes a framework for online health monitoring of aging and degradation of secondary components. The framework consists of an integrated multi-sensor modality system which can be used to monitor different piping configurations under different degradation conditions. The report analyses the currently known degradation mechanisms and available predictive models. Based on this analysis, the structural health monitoring framework is proposed. The Light Water Reactor Sustainability Program began to evaluate technologies that could be used to perform online monitoring of piping and other secondary system structural components in commercial NPPs. These online monitoring systems have the potential to identify when a more detailed inspection is needed using real-time measurements, rather than at a pre-determined inspection interval. This transition to condition-based, risk informed automated maintenance will contribute to a significant reduction of operations and maintenance costs that account for the majority of nuclear power generation costs. There is unanimous agreement between industry experts and academic researchers that identifying and prioritizing inspection locations in secondary piping systems (for example, in raw water piping or diesel piping) would eliminate many excessive in-service inspections. The proposed structural health monitoring framework takes aim at answering this challenge by combining long-range guided wave technologies with other monitoring techniques, which can significantly increase the inspection length and pinpoint the locations that degraded the most. More widely, the report suggests research efforts aimed at developing, validating, and deploying online corrosion monitoring techniques for complex geometries, which are pervasive in NPPs.

  18. Framework for Structural Online Health Monitoring of Aging and Degradation of Secondary Systems due to some Aspects of Erosion

    International Nuclear Information System (INIS)

    Gribok, Andrei; Patnaik, Sobhan; Williams, Christian; Pattanaik, Marut; Kanakala, Raghunath

    2016-01-01

    This report describes the current state of research related to critical aspects of erosion and selected aspects of degradation of secondary components in nuclear power plants. The report also proposes a framework for online health monitoring of aging and degradation of secondary components. The framework consists of an integrated multi-sensor modality system which can be used to monitor different piping configurations under different degradation conditions. The report analyses the currently known degradation mechanisms and available predictive models. Based on this analysis, the structural health monitoring framework is proposed. The Light Water Reactor Sustainability Program began to evaluate technologies that could be used to perform online monitoring of piping and other secondary system structural components in commercial NPPs. These online monitoring systems have the potential to identify when a more detailed inspection is needed using real-time measurements, rather than at a pre-determined inspection interval. This transition to condition-based, risk informed automated maintenance will contribute to a significant reduction of operations and maintenance costs that account for the majority of nuclear power generation costs. There is unanimous agreement between industry experts and academic researchers that identifying and prioritizing inspection locations in secondary piping systems (for example, in raw water piping or diesel piping) would eliminate many excessive in-service inspections. The proposed structural health monitoring framework takes aim at answering this challenge by combining long-range guided wave technologies with other monitoring techniques, which can significantly increase the inspection length and pinpoint the locations that degraded the most. More widely, the report suggests research efforts aimed at developing, validating, and deploying online corrosion monitoring techniques for complex geometries, which are pervasive in NPPs.

  19. Model Prediction of Secondary Soil Salinization in the Keriya Oasis, Northwest China

    Directory of Open Access Journals (Sweden)

    Jumeniyaz Seydehmet

    2018-02-01

    Full Text Available Significant anthropogenic and biophysical changes have caused fluctuations in the soil salinization area of the Keriya Oasis in China. The Driver-Pressure-State-Impact-Response (DPSIR sustainability framework and Bayesian networks (BNs were used to integrate information from anthropogenic and natural systems to model the trend of secondary soil salinization. The developed model predicted that light salinization (vegetation coverage of around 15–20%, soil salt 5–10 g/kg of the ecotone will increase in the near term but decelerate slightly in the future, and that farmland salinization will decrease in the near term. This trend is expected to accelerate in the future. Both trends are attributed to decreased water logging, increased groundwater exploitation, and decreased ratio of evaporation/precipitation. In contrast, severe salinization (vegetation coverage of around 2%, soil salt ≥20 g/kg of the ecotone will increase in the near term. This trend will accelerate in the future because decreased river flow will reduce the flushing of severely salinized soil crust. Anthropogenic factors have negative impacts and natural causes have positive impacts on light salinization of ecotones. In situations involving severe farmland salinization, anthropogenic factors have persistent negative impacts.

  20. Community-weighted mean of leaf traits and divergence of wood traits predict aboveground biomass in secondary subtropical forests.

    Science.gov (United States)

    Ali, Arshad; Yan, En-Rong; Chang, Scott X; Cheng, Jun-Yang; Liu, Xiang-Yu

    2017-01-01

    Subtropical forests are globally important in providing ecological goods and services, but it is not clear whether functional diversity and composition can predict aboveground biomass in such forests. We hypothesized that high aboveground biomass is associated with high functional divergence (FDvar, i.e., niche complementarity) and community-weighted mean (CWM, i.e., mass ratio; communities dominated by a single plant strategy) of trait values. Structural equation modeling was employed to determine the direct and indirect effects of stand age and the residual effects of CWM and FDvar on aboveground biomass across 31 plots in secondary forests in subtropical China. The CWM model accounted for 78, 20, 6 and 2% of the variation in aboveground biomass, nitrogen concentration in young leaf, plant height and specific leaf area of young leaf, respectively. The FDvar model explained 74, 13, 7 and 0% of the variation in aboveground biomass, plant height, twig wood density and nitrogen concentration in young leaf, respectively. The variation in aboveground biomass, CWM of leaf nitrogen concentration and specific leaf area, and FDvar of plant height, twig wood density and nitrogen concentration in young leaf explained by the joint model was 86, 20, 13, 7, 2 and 0%, respectively. Stand age had a strong positive direct effect but low indirect positive effects on aboveground biomass. Aboveground biomass was negatively related to CWM of nitrogen concentration in young leaf, but positively related to CWM of specific leaf area of young leaf and plant height, and FDvar of plant height, twig wood density and nitrogen concentration in young leaf. Leaf and wood economics spectra are decoupled in regulating the functionality of forests, communities with diverse species but high nitrogen conservative and light acquisitive strategies result in high aboveground biomass, and hence, supporting both the mass ratio and niche complementarity hypotheses in secondary subtropical forests

  1. Predicting nucleic acid binding interfaces from structural models of proteins.

    Science.gov (United States)

    Dror, Iris; Shazman, Shula; Mukherjee, Srayanta; Zhang, Yang; Glaser, Fabian; Mandel-Gutfreund, Yael

    2012-02-01

    The function of DNA- and RNA-binding proteins can be inferred from the characterization and accurate prediction of their binding interfaces. However, the main pitfall of various structure-based methods for predicting nucleic acid binding function is that they are all limited to a relatively small number of proteins for which high-resolution three-dimensional structures are available. In this study, we developed a pipeline for extracting functional electrostatic patches from surfaces of protein structural models, obtained using the I-TASSER protein structure predictor. The largest positive patches are extracted from the protein surface using the patchfinder algorithm. We show that functional electrostatic patches extracted from an ensemble of structural models highly overlap the patches extracted from high-resolution structures. Furthermore, by testing our pipeline on a set of 55 known nucleic acid binding proteins for which I-TASSER produces high-quality models, we show that the method accurately identifies the nucleic acids binding interface on structural models of proteins. Employing a combined patch approach we show that patches extracted from an ensemble of models better predicts the real nucleic acid binding interfaces compared with patches extracted from independent models. Overall, these results suggest that combining information from a collection of low-resolution structural models could be a valuable approach for functional annotation. We suggest that our method will be further applicable for predicting other functional surfaces of proteins with unknown structure. Copyright © 2011 Wiley Periodicals, Inc.

  2. Secondary structure of bovine albumin as studied by polarization-sensitive multiplex CARS spectroscopy

    NARCIS (Netherlands)

    Voroshilov, A.; Voroshilov, Artemy; Otto, Cornelis; Greve, Jan

    1996-01-01

    The first application of polarization-sensitive multiplex coherent anti-Stokes Raman spectroscopy (MCARS) in the absence of resonance enhancement to the resolution of the secondary structure of a protein in solution is reported. Polarization MCARS spectra of bovine albumin in D2O were obtained in

  3. Instruction in text-structure as a determinant of senior secondary ...

    African Journals Online (AJOL)

    The study determined the effectiveness of instruction in text-structure on achievement of students in English narrative text. The pretest-posttest control group quasi experimental design was adopted for the study. The participants were 120 students in intact classes from four purposively selected senior secondary schools in ...

  4. Molecular systematics of Barbatosphaeria (Sordariomycetes): multigene phylogeny and secondary ITS structure

    Czech Academy of Sciences Publication Activity Database

    Réblová, Martina; Réblová, K.; Štěpánek, Václav

    2015-01-01

    Roč. 35, December 2015 (2015), s. 21-38 ISSN 0031-5850 R&D Projects: GA ČR GAP506/12/0038 Institutional support: RVO:67985939 ; RVO:61388971 Keywords : Barbatosphaeria * molecular systematic * ITS secondary structures Subject RIV: EF - Botanics; EE - Microbiology, Virology (MBU-M) Impact factor: 5.725, year: 2015

  5. Interfacial ordering of thermotropic liquid crystals triggered by the secondary structures of oligopeptides.

    Science.gov (United States)

    Wang, Xiaoguang; Yang, Pei; Mondiot, Frederic; Li, Yaoxin; Miller, Daniel S; Chen, Zhan; Abbott, Nicholas L

    2015-12-07

    We report that assemblies formed by eight oligopeptides at phospholipid-decorated interfaces of thermotropic liquid crystals (LCs) trigger changes in ordering of the LCs that are dependent on the secondary structures of the oligopeptides (as characterized in situ using infrared-visible sum-frequency spectroscopy).

  6. Glassy transition in a disordered model for the RNA secondary structure

    International Nuclear Information System (INIS)

    Pagnani, A.; Parisi, G.; Ricci-Tersenghi, F.

    2000-04-01

    We numerically study a disordered model for the RNA secondary structure and we find that it undergoes a phase transition, with a breaking of the replica symmetry in the low temperature region (like in spin glasses). Our results are based on the exact evaluation of the partition function. (author)

  7. Tropical rain-forest matrix quality affects bat assemblage structure in secondary forest patches

    NARCIS (Netherlands)

    Vleut, I.; Levy-Tacher, I.; Galindo-Gonzalez, J.; Boer, de W.F.; Ramirez-Marcial, N.

    2012-01-01

    We studied Phyllostomidae bat assemblage structure in patches of secondary forest dominated by the pioneer tree Ochroma pyramidale, largely (.85%) or partially (,35%) surrounded by a matrix of tropical rain forest, to test 3 hypotheses: the highest bat diversity and richness is observed in the

  8. Secondary structures of rRNAs from all three domains of life.

    Directory of Open Access Journals (Sweden)

    Anton S Petrov

    Full Text Available Accurate secondary structures are important for understanding ribosomes, which are extremely large and highly complex. Using 3D structures of ribosomes as input, we have revised and corrected traditional secondary (2° structures of rRNAs. We identify helices by specific geometric and molecular interaction criteria, not by co-variation. The structural approach allows us to incorporate non-canonical base pairs on parity with Watson-Crick base pairs. The resulting rRNA 2° structures are up-to-date and consistent with three-dimensional structures, and are information-rich. These 2° structures are relatively simple to understand and are amenable to reproduction and modification by end-users. The 2° structures made available here broadly sample the phylogenetic tree and are mapped with a variety of data related to molecular interactions and geometry, phylogeny and evolution. We have generated 2° structures for both large subunit (LSU 23S/28S and small subunit (SSU 16S/18S rRNAs of Escherichia coli, Thermus thermophilus, Haloarcula marismortui (LSU rRNA only, Saccharomyces cerevisiae, Drosophila melanogaster, and Homo sapiens. We provide high-resolution editable versions of the 2° structures in several file formats. For the SSU rRNA, the 2° structures use an intuitive representation of the central pseudoknot where base triples are presented as pairs of base pairs. Both LSU and SSU secondary maps are available (http://apollo.chemistry.gatech.edu/RibosomeGallery. Mapping of data onto 2° structures was performed on the RiboVision server (http://apollo.chemistry.gatech.edu/RiboVision.

  9. Analysis of the secondary structure of ITS transcripts in peritrich ciliates (Ciliophora, Oligohymenophorea): implications for structural evolution and phylogenetic reconstruction.

    Science.gov (United States)

    Sun, Ping; Clamp, John C; Xu, Dapeng

    2010-07-01

    Despite extensive previous morphological work, little agreement has been reached about phylogenetic relationships among peritrich ciliates, making it difficult to study the evolution of the group in a phylogenetic framework. In this study, the nucleotide characteristics and secondary structures of internal transcribed spacers 1 and 2 (ITS1 and ITS2) of 26 peritrich ciliates in 12 genera were analyzed. Information from secondary structures of ITS1 and ITS2 then was used to perform the first systematic study of ITS regions in peritrich ciliates, including one species of Rhabdostyla for which no sequence has been reported previously. Lengths of ITS1 and ITS2 sequences varied relatively little among taxa studied, but their G+C content was highly variable. General secondary structure models of ITS1 and ITS2 were proposed for peritrich ciliates and their reliability was assessed by compensatory base changes. The secondary structure of ITS1 contains three major helices in peritrich ciliates and deviations from this basic structure were found in all taxa examined. The core structure of peritrich ITS2 includes four helices, with helix III as the longest and containing a motif 5'-MAC versus GUK-3' at its apex as well as a YU-UY mismatch in helix II. In addition, the structural motifs of both ITS secondary structures were identified. Phylogenetic analyses using ITS data were performed by means of Bayesian inference, maximum likelihood and neighbor joining methods. Trees had a consistent branching pattern that included the following features: (1) Rhabdostyla always clustered with members of the family Vorticellidae, instead of members of the family Epistylididae, in which it is now classified on the basis of morphology. (2) The systematically questionable genus Ophrydium closely associated with Carchesium, forming a clearly defined, monophyletic group within the Vorticellidae. This supported the hypothesis derived from previous study based on small subunit rRNA gene sequences

  10. Factors Predicting Burnout Among Chaplains: Compassion Satisfaction, Organizational Factors, and the Mediators of Mindful Self-Care and Secondary Traumatic Stress.

    Science.gov (United States)

    Hotchkiss, Jason T; Lesher, Ruth

    2018-06-01

    This study predicted Burnout from the self-care practices, compassion satisfaction, secondary traumatic stress, and organizational factors among chaplains who participated from all 50 states (N = 534). A hierarchical regression model indicated that the combined effect of compassion satisfaction, secondary traumatic stress, mindful self-care, demographic, and organizational factors explained 83.2% of the variance in Burnout. Chaplains serving in a hospital were slightly more at risk for Burnout than those in hospice or other settings. Organizational factors that most predicted Burnout were feeling bogged down by the "system" (25.7%) and an overwhelming caseload (19.9%). Each self-care category was a statistically significant protective factor against Burnout risk. The strongest protective factors against Burnout in order of strength were self-compassion and purpose, supportive structure, mindful self-awareness, mindful relaxation, supportive relationships, and physical care. For secondary traumatic stress, supportive structure, mindful self-awareness, and self-compassion and purpose were the strongest protective factors. Chaplains who engaged in multiple and frequent self-care strategies experienced higher professional quality of life and low Burnout risk. In the chaplain's journey toward wellness, a reflective practice of feeling good about doing good and mindful self-care are vital. The significance, implications, and limitations of the study were discussed.

  11. Secondary structure classification of amino-acid sequences using state-space modeling

    OpenAIRE

    Brunnert, Marcus; Krahnke, Tillmann; Urfer, Wolfgang

    2001-01-01

    The secondary structure classification of amino acid sequences can be carried out by a statistical analysis of sequence and structure data using state-space models. Aiming at this classification, a modified filter algorithm programmed in S is applied to data of three proteins. The application leads to correct classifications of two proteins even when using relatively simple estimation methods for the parameters of the state-space models. Furthermore, it has been shown that the assumed initial...

  12. Prediction of Seismic Damage-Based Degradation in RC Structures

    DEFF Research Database (Denmark)

    Kirkegaard, Poul Henning; Gupta, Vinay K.; Nielsen, Søren R.K.

    Estimation of structural damage from known increase in the fundamental period of a structure after an earthquake or prediction of degradation of stiffness and strength for known damage requires reliable correlations between these response functionals. This study proposes a modified Clough-Johnsto...

  13. Correlating Structural Order with Structural Rearrangement in Dusty Plasma Liquids: Can Structural Rearrangement be Predicted by Static Structural Information?

    Science.gov (United States)

    Su, Yen-Shuo; Liu, Yu-Hsuan; I, Lin

    2012-11-01

    Whether the static microstructural order information is strongly correlated with the subsequent structural rearrangement (SR) and their predicting power for SR are investigated experimentally in the quenched dusty plasma liquid with microheterogeneities. The poor local structural order is found to be a good alarm to identify the soft spot and predict the short term SR. For the site with good structural order, the persistent time for sustaining the structural memory until SR has a large mean value but a broad distribution. The deviation of the local structural order from that averaged over nearest neighbors serves as a good second alarm to further sort out the short time SR sites. It has the similar sorting power to that using the temporal fluctuation of the local structural order over a small time interval.

  14. Protein structure prediction using bee colony optimization metaheuristic

    DEFF Research Database (Denmark)

    Fonseca, Rasmus; Paluszewski, Martin; Winter, Pawel

    2010-01-01

    of the proteins structure, an energy potential and some optimization algorithm that ¿nds the structure with minimal energy. Bee Colony Optimization (BCO) is a relatively new approach to solving opti- mization problems based on the foraging behaviour of bees. Several variants of BCO have been suggested......Predicting the native structure of proteins is one of the most challenging problems in molecular biology. The goal is to determine the three-dimensional struc- ture from the one-dimensional amino acid sequence. De novo prediction algorithms seek to do this by developing a representation...... our BCO method to generate good solutions to the protein structure prediction problem. The results show that BCO generally ¿nds better solutions than simulated annealing which so far has been the metaheuristic of choice for this problem....

  15. Alignment-free comparative genomic screen for structured RNAs using coarse-grained secondary structure dot plots

    DEFF Research Database (Denmark)

    Kato, Yuki; Gorodkin, Jan; Havgaard, Jakob Hull

    2017-01-01

    . Methods: Here we present a fast and efficient method, DotcodeR, for detecting structurally similar RNAs in genomic sequences by comparing their corresponding coarse-grained secondary structure dot plots at string level. This allows us to perform an all-against-all scan of all window pairs from two genomes...... without alignment. Results: Our computational experiments with simulated data and real chromosomes demonstrate that the presented method has good sensitivity. Conclusions: DotcodeR can be useful as a pre-filter in a genomic comparative scan for structured RNAs....

  16. Affective Self-Regulation Trajectories during Secondary School Predict Substance Use among Urban Minority Young Adults

    Science.gov (United States)

    Griffin, Kenneth W.; Lowe, Sarah R.; Acevedo, Bianca P.; Botvin, Gilbert J.

    2015-01-01

    This study explored the relationship between trajectories of affective self-regulation skills during secondary school and young adult substance use in a large multiethnic, urban sample (N = 995). During secondary school, participants completed a measure of cognitive and behavioral skills used to control negative, unpleasant emotions or perceived…

  17. Blind Test of Physics-Based Prediction of Protein Structures

    Science.gov (United States)

    Shell, M. Scott; Ozkan, S. Banu; Voelz, Vincent; Wu, Guohong Albert; Dill, Ken A.

    2009-01-01

    We report here a multiprotein blind test of a computer method to predict native protein structures based solely on an all-atom physics-based force field. We use the AMBER 96 potential function with an implicit (GB/SA) model of solvation, combined with replica-exchange molecular-dynamics simulations. Coarse conformational sampling is performed using the zipping and assembly method (ZAM), an approach that is designed to mimic the putative physical routes of protein folding. ZAM was applied to the folding of six proteins, from 76 to 112 monomers in length, in CASP7, a community-wide blind test of protein structure prediction. Because these predictions have about the same level of accuracy as typical bioinformatics methods, and do not utilize information from databases of known native structures, this work opens up the possibility of predicting the structures of membrane proteins, synthetic peptides, or other foldable polymers, for which there is little prior knowledge of native structures. This approach may also be useful for predicting physical protein folding routes, non-native conformations, and other physical properties from amino acid sequences. PMID:19186130

  18. Reflection of the energy structure of a tungsten monocrystal nearsurface area in the secondary electron spectrum

    International Nuclear Information System (INIS)

    Artamonov, O.M.; Smirnov, O.M.; Terekhov, A.N.

    1982-01-01

    Formation of secondary electron energy spectrum during emission from the crystal layer near the surface has been considered, at that layer energy structure can be different from volumetric energy structure. Its thickness depends on the predominant mechanism of electron scattering and is determined by corresponding phenomenological parameters. It is shown that the structure in the secondary electron spectrum appears in the case when energy structure of emitting monocrystal layer can not be described in the approximation of almost free electron gas and, as experimental investigations show, approaches energy zone structure of its volume. It is also show that in the case when the energy structure of the emitting layer is satisfactorily described with the model of almost free electron gas, the SE spectrum is characterized with traditional cascade minimum. Experimental investigation of SE energy distribution was carried out for the W monocrystalline face (110). It was established that distinct structure in the SE spectrum appears only after electrochemical polishing of the specimen surface. It is related to the appearance of ''far'' order in the monocrystal emission layer on initially disturbed tungsten surface during such treatment. Disturbance of tungsten monocrystal surface structure on its oxidation in O 2 atmosphere results in the appearance of the cascade maximum and disappearance of distinct peculiarities in the SE spectrum

  19. A study on prediction of metal loss by flow-accelerated corrosion in the CANDU NPP secondary piping systems

    International Nuclear Information System (INIS)

    Shim, S. H.; Song, J. S.; Yoon, K. B.; Hwang, K. M.; Jin, T. E.; Lee, S. H.; Kim, W. S.

    2001-01-01

    Flow-Accelerated Corrosion(FAC) is a phenomenon that results in metal loss from piping, vessels, and equipment made of carbon steel. FAC occurs only under certain conditions of flow, chemistry, geometry, and material. Unfortunately, those conditions are in much of the high-energy piping in nuclear and fossil-fueled power plants. Also, for domestic NPP secondary pipings whose operating time become longer, more evidences of FAC have been reported. The authors are studying on FAC management using CHECWORKS, computer code developed by EPRI. This paper is on the prediction results of metal loss by FAC in the one of CANDU type NPP secondary piping systems

  20. A contribution to understanding the structure of amphivasal secondary bundles in monocotyledons

    Directory of Open Access Journals (Sweden)

    Joanna Jura-Morawiec

    2014-04-01

    Full Text Available Secondary growth of monocotyledonous plants is connected with the activity of the monocot cambium that accumulates most of the derivatives inner to the cambial cylinder. These derivatives differentiate into (a secondary bundles with the amphivasal arrangement, i.e. xylem composed of tracheids surrounds the phloem cells and (b the parenchymatous secondary conjunctive tissue in which the bundles are embedded. The amphivasal secondary bundles differ in the arrangement of xylem cells as visible on single cross sections through the secondary body of the monocots. Apart from the bundles with typical ring of tracheids also the bundles where tracheids do not quite surround the phloem are present. We aimed to elucidate the cross sectional anatomy of the amphivasal secondary bundles with the use of the serial sectioning method which allowed us to follow very precisely the bundle structure along its length. The studies were carried out with the samples of secondary tissues collected from the stem of Dracaena draco L. growing in the greenhouses of the Polish Academy of Sciences Botanical Garden – CBDC in Powsin and the Adam Mickiewicz University Botanical Garden. The material was fixed in a mixture of glycerol and ethanol (1:1; v/v, dehydrated stepwise with graded ethanol series and finally embedded in epon resin. Afterwards, the material was sectioned with microtome into continuous series of thin (3 μm sections, stained with PAS/toluidine blue and examined under the light microscope. The results, described in details in Jura‑Morawiec & Wiland-Szymańska (2014, revealed novel facts about tracheids arrangement. Each amphivasal bundle is composed of sectors where tracheids form a ring as well as of such where tracheids are separated by vascular parenchyma cells. We hypothesize that strands of vascular parenchyma cells locally separating the tracheids enable radial transport of assimilates from sieve elements of the bundle towards the sink tissues, e

  1. Practical use of chemical shift databases for protein solid-state NMR: 2D chemical shift maps and amino-acid assignment with secondary-structure information

    International Nuclear Information System (INIS)

    Fritzsching, K. J.; Yang, Y.; Schmidt-Rohr, K.; Hong Mei

    2013-01-01

    We introduce a Python-based program that utilizes the large database of 13 C and 15 N chemical shifts in the Biological Magnetic Resonance Bank to rapidly predict the amino acid type and secondary structure from correlated chemical shifts. The program, called PACSYlite Unified Query (PLUQ), is designed to help assign peaks obtained from 2D 13 C– 13 C, 15 N– 13 C, or 3D 15 N– 13 C– 13 C magic-angle-spinning correlation spectra. We show secondary-structure specific 2D 13 C– 13 C correlation maps of all twenty amino acids, constructed from a chemical shift database of 262,209 residues. The maps reveal interesting conformation-dependent chemical shift distributions and facilitate searching of correlation peaks during amino-acid type assignment. Based on these correlations, PLUQ outputs the most likely amino acid types and the associated secondary structures from inputs of experimental chemical shifts. We test the assignment accuracy using four high-quality protein structures. Based on only the Cα and Cβ chemical shifts, the highest-ranked PLUQ assignments were 40–60 % correct in both the amino-acid type and the secondary structure. For three input chemical shifts (CO–Cα–Cβ or N–Cα–Cβ), the first-ranked assignments were correct for 60 % of the residues, while within the top three predictions, the correct assignments were found for 80 % of the residues. PLUQ and the chemical shift maps are expected to be useful at the first stage of sequential assignment, for combination with automated sequential assignment programs, and for highly disordered proteins for which secondary structure analysis is the main goal of structure determination.

  2. Practical use of chemical shift databases for protein solid-state NMR: 2D chemical shift maps and amino-acid assignment with secondary-structure information

    Energy Technology Data Exchange (ETDEWEB)

    Fritzsching, K. J.; Yang, Y.; Schmidt-Rohr, K.; Hong Mei, E-mail: mhong@iastate.edu [Iowa State University, Department of Chemistry (United States)

    2013-06-15

    We introduce a Python-based program that utilizes the large database of {sup 13}C and {sup 15}N chemical shifts in the Biological Magnetic Resonance Bank to rapidly predict the amino acid type and secondary structure from correlated chemical shifts. The program, called PACSYlite Unified Query (PLUQ), is designed to help assign peaks obtained from 2D {sup 13}C-{sup 13}C, {sup 15}N-{sup 13}C, or 3D {sup 15}N-{sup 13}C-{sup 13}C magic-angle-spinning correlation spectra. We show secondary-structure specific 2D {sup 13}C-{sup 13}C correlation maps of all twenty amino acids, constructed from a chemical shift database of 262,209 residues. The maps reveal interesting conformation-dependent chemical shift distributions and facilitate searching of correlation peaks during amino-acid type assignment. Based on these correlations, PLUQ outputs the most likely amino acid types and the associated secondary structures from inputs of experimental chemical shifts. We test the assignment accuracy using four high-quality protein structures. Based on only the C{alpha} and C{beta} chemical shifts, the highest-ranked PLUQ assignments were 40-60 % correct in both the amino-acid type and the secondary structure. For three input chemical shifts (CO-C{alpha}-C{beta} or N-C{alpha}-C{beta}), the first-ranked assignments were correct for 60 % of the residues, while within the top three predictions, the correct assignments were found for 80 % of the residues. PLUQ and the chemical shift maps are expected to be useful at the first stage of sequential assignment, for combination with automated sequential assignment programs, and for highly disordered proteins for which secondary structure analysis is the main goal of structure determination.

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

    Science.gov (United States)

    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.

  4. Contingency Table Browser - prediction of early stage protein structure.

    Science.gov (United States)

    Kalinowska, Barbara; Krzykalski, Artur; Roterman, Irena

    2015-01-01

    The Early Stage (ES) intermediate represents the starting structure in protein folding simulations based on the Fuzzy Oil Drop (FOD) model. The accuracy of FOD predictions is greatly dependent on the accuracy of the chosen intermediate. A suitable intermediate can be constructed using the sequence-structure relationship information contained in the so-called contingency table - this table expresses the likelihood of encountering various structural motifs for each tetrapeptide fragment in the amino acid sequence. The limited accuracy with which such structures could previously be predicted provided the motivation for a more indepth study of the contingency table itself. The Contingency Table Browser is a tool which can visualize, search and analyze the table. Our work presents possible applications of Contingency Table Browser, among them - analysis of specific protein sequences from the point of view of their structural ambiguity.

  5. Prediction of degradation and fracture of structural materials

    International Nuclear Information System (INIS)

    Tomkins, B.

    1992-01-01

    Prediction of materials performance in an engineering integrity context requires the underpinning of predictive modelling tuned by inputs from design, fabrication, operating experience, and laboratory testing. In this regard, in addition to fracture resistance four important areas of time dependent degradation are considered - mechanical, environmental, irradiation and thermal. The status of prediction of materials performance is discussed in relation to a number of important components such as LWR reactor pressure vessels and steam generators, and Fast Reactor high temperature structures. In each case the role of materials modelling is examined and the balance of factors which contribute to the overall prediction of component integrity/reliability noted. Structural integrity arguments must follow a clear strategy if the required level of confidence is to be established. Various strategies and their evolution are discussed. (author)

  6. New tips for structure prediction by comparative modeling

    OpenAIRE

    Rayan, Anwar

    2009-01-01

    Comparative modelling is utilized to predict the 3-dimensional conformation of a given protein (target) based on its sequence alignment to experimentally determined protein structure (template). The use of such technique is already rewarding and increasingly widespread in biological research and drug development. The accuracy of the predictions as commonly accepted depends on the score of sequence identity of the target protein to the template. To assess the relationship between sequence iden...

  7. Ab-initio conformational epitope structure prediction using genetic algorithm and SVM for vaccine design.

    Science.gov (United States)

    Moghram, Basem Ameen; Nabil, Emad; Badr, Amr

    2018-01-01

    T-cell epitope structure identification is a significant challenging immunoinformatic problem within epitope-based vaccine design. Epitopes or antigenic peptides are a set of amino acids that bind with the Major Histocompatibility Complex (MHC) molecules. The aim of this process is presented by Antigen Presenting Cells to be inspected by T-cells. MHC-molecule-binding epitopes are responsible for triggering the immune response to antigens. The epitope's three-dimensional (3D) molecular structure (i.e., tertiary structure) reflects its proper function. Therefore, the identification of MHC class-II epitopes structure is a significant step towards epitope-based vaccine design and understanding of the immune system. In this paper, we propose a new technique using a Genetic Algorithm for Predicting the Epitope Structure (GAPES), to predict the structure of MHC class-II epitopes based on their sequence. The proposed Elitist-based genetic algorithm for predicting the epitope's tertiary structure is based on Ab-Initio Empirical Conformational Energy Program for Peptides (ECEPP) Force Field Model. The developed secondary structure prediction technique relies on Ramachandran Plot. We used two alignment algorithms: the ROSS alignment and TM-Score alignment. We applied four different alignment approaches to calculate the similarity scores of the dataset under test. We utilized the support vector machine (SVM) classifier as an evaluation of the prediction performance. The prediction accuracy and the Area Under Receiver Operating Characteristic (ROC) Curve (AUC) were calculated as measures of performance. The calculations are performed on twelve similarity-reduced datasets of the Immune Epitope Data Base (IEDB) and a large dataset of peptide-binding affinities to HLA-DRB1*0101. The results showed that GAPES was reliable and very accurate. We achieved an average prediction accuracy of 93.50% and an average AUC of 0.974 in the IEDB dataset. Also, we achieved an accuracy of 95

  8. RaptorX-Property: a web server for protein structure property prediction.

    Science.gov (United States)

    Wang, Sheng; Li, Wei; Liu, Shiwang; Xu, Jinbo

    2016-07-08

    RaptorX Property (http://raptorx2.uchicago.edu/StructurePropertyPred/predict/) is a web server predicting structure property of a protein sequence without using any templates. It outperforms other servers, especially for proteins without close homologs in PDB or with very sparse sequence profile (i.e. carries little evolutionary information). This server employs a powerful in-house deep learning model DeepCNF (Deep Convolutional Neural Fields) to predict secondary structure (SS), solvent accessibility (ACC) and disorder regions (DISO). DeepCNF not only models complex sequence-structure relationship by a deep hierarchical architecture, but also interdependency between adjacent property labels. Our experimental results show that, tested on CASP10, CASP11 and the other benchmarks, this server can obtain ∼84% Q3 accuracy for 3-state SS, ∼72% Q8 accuracy for 8-state SS, ∼66% Q3 accuracy for 3-state solvent accessibility, and ∼0.89 area under the ROC curve (AUC) for disorder prediction. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

  9. Protein Phosphorylation and Mineral Binding Affect the Secondary Structure of the Leucine-Rich Amelogenin Peptide

    Directory of Open Access Journals (Sweden)

    Hajime Yamazaki

    2017-06-01

    Full Text Available Previously, we have shown that serine-16 phosphorylation in native full-length porcine amelogenin (P173 and the Leucine-Rich Amelogenin Peptide (LRAP(+P, an alternative amelogenin splice product, affects protein assembly and mineralization in vitro. Notably, P173 and LRAP(+P stabilize amorphous calcium phosphate (ACP and inhibit hydroxyapatite (HA formation, while non-phosphorylated counterparts (rP172, LRAP(−P guide the growth of ordered bundles of HA crystals. Based on these findings, we hypothesize that the phosphorylation of full-length amelogenin and LRAP induces conformational changes that critically affect its capacity to interact with forming calcium phosphate mineral phases. To test this hypothesis, we have utilized Fourier transform infrared spectroscopy (FTIR to determine the secondary structure of LRAP(−P and LRAP(+P in the absence/presence of calcium and selected mineral phases relevant to amelogenesis; i.e., hydroxyapatite (HA: an enamel crystal prototype and (ACP: an enamel crystal precursor phase. Aqueous solutions of LRAP(−P or LRAP(+P were prepared with or without 7.5 mM of CaCl2 at pH 7.4. FTIR spectra of each solution were obtained using attenuated total reflectance, and amide-I peaks were analyzed to provide secondary structure information. Secondary structures of LRAP(+P and LRAP(−P were similarly assessed following incubation with suspensions of HA and pyrophosphate-stabilized ACP. Amide I spectra of LRAP(−P and LRAP(+P were found to be distinct from each other in all cases. Spectra analyses showed that LRAP(−P is comprised mostly of random coil and β-sheet, while LRAP(+P exhibits more β-sheet and α-helix with little random coil. With added Ca, the random coil content increased in LRAP(−P, while LRAP(+P exhibited a decrease in α-helix components. Incubation of LRAP(−P with HA or ACP resulted in comparable increases in β-sheet structure. Notably, however, LRAP(+P secondary structure was more affected by

  10. Control of Helical Chirality of Ferrocene-Dipeptide Conjugates by the Secondary Structure of Dipeptide Chains.

    Science.gov (United States)

    Moriuchi, Toshiyuki; Nishiyama, Taiki; Nobu, Masaki; Hirao, Toshikazu

    2017-09-18

    Controlling helical chirality and creating protein secondary structures in cyclic/acyclic ferrocene-dipeptide bioorganometallic conjugates were achieved by adjusting the conformational flexibility of the dipeptide chains. In systems reported to date, the helical chirality of a conjugate was determined by the absolute configuration of the adjacent amino acid reside. In contrast, it was possible to induce both M- and P-helical chirality, even when the configuration of the adjacent amino acid was the same. It is particularly interesting to note that M-helical chirality was produced in a cyclic ferrocene-dipeptide conjugate composed of the l-Ala-d-Pro-cystamine-d-Pro-l-Ala dipeptide sequence (1), in which a type II β-turn-like secondary structure was established. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

  11. [Peculiarities of secondary structure of serum albumin of some representatives of the animal kingdom].

    Science.gov (United States)

    Pekhymenko, G V; Kuchmerovskaia, T M

    2011-01-01

    Methods of infrared (IR) spectroscopy and circular dichroism (CD) are suitable techniques for detection of proteins structural changes. These methods were used for determinating peculiarities of the secondary structure of serum albumins in some representatives of two classes of reptiles: Horsfield's tortoise (Testudo horsfieldi), water snake (Natrix tessellata) and grass snake (Natrix natrix) and birds: domestic goose (Anser anser), domestic chicken (Gallus domesticus), domestic duck (Anas platyrhyncha) and dove colored (Columba livia). An analysis of IR spectra and spectra obtained by the method of CD of serum albumins of both classes representatives revealed that beta-folding structure and alpha-helical sections that form the alpha-conformation play an important role in conformational structure formation of polypeptide chain and also disordered sites of molecules of these proteins. It was observed that certain redistribution depending on animals species exists, in the formation of secondary structure of serum albumins of the investigated representatives of reptiles and birds classes between the content of beta-folding structure, alpha-helical sections and disordered sites in molecules of these proteins.

  12. Correlation between protein secondary structure, backbone bond angles, and side-chain orientations

    Science.gov (United States)

    Lundgren, Martin; Niemi, Antti J.

    2012-08-01

    We investigate the fine structure of the sp3 hybridized covalent bond geometry that governs the tetrahedral architecture around the central Cα carbon of a protein backbone, and for this we develop new visualization techniques to analyze high-resolution x-ray structures in the Protein Data Bank. We observe that there is a correlation between the deformations of the ideal tetrahedral symmetry and the local secondary structure of the protein. We propose a universal coarse-grained energy function to describe the ensuing side-chain geometry in terms of the Cβ carbon orientations. The energy function can model the side-chain geometry with a subatomic precision. As an example we construct the Cα-Cβ structure of HP35 chicken villin headpiece. We obtain a configuration that deviates less than 0.4 Å in root-mean-square distance from the experimental x-ray structure.

  13. Psychosis prediction in secondary mental health services. A broad, comprehensive approach to the "at risk mental state" syndrome.

    Science.gov (United States)

    Francesconi, M; Minichino, A; Carrión, R E; Delle Chiaie, R; Bevilacqua, A; Parisi, M; Rullo, S; Bersani, F Saverio; Biondi, M; Cadenhead, K

    2017-02-01

    Accuracy of risk algorithms for psychosis prediction in "at risk mental state" (ARMS) samples may differ according to the recruitment setting. Standardized criteria used to detect ARMS individuals may lack specificity if the recruitment setting is a secondary mental health service. The authors tested a modified strategy to predict psychosis conversion in this setting by using a systematic selection of trait-markers of the psychosis prodrome in a sample with a heterogeneous ARMS status. 138 non-psychotic outpatients (aged 17-31) were consecutively recruited in secondary mental health services and followed-up for up to 3 years (mean follow-up time, 2.2 years; SD=0.9). Baseline ARMS status, clinical, demographic, cognitive, and neurological soft signs measures were collected. Cox regression was used to derive a risk index. 48% individuals met ARMS criteria (ARMS-Positive, ARMS+). Conversion rate to psychosis was 21% for the overall sample, 34% for ARMS+, and 9% for ARMS-Negative (ARMS-). The final predictor model with a positive predictive validity of 80% consisted of four variables: Disorder of Thought Content, visuospatial/constructional deficits, sensory-integration, and theory-of-mind abnormalities. Removing Disorder of Thought Content from the model only slightly modified the predictive accuracy (-6.2%), but increased the sensitivity (+9.5%). These results suggest that in a secondary mental health setting the use of trait-markers of the psychosis prodrome may predict psychosis conversion with great accuracy despite the heterogeneity of the ARMS status. The use of the proposed predictive algorithm may enable a selective recruitment, potentially reducing duration of untreated psychosis and improving prognostic outcomes. Copyright © 2016 Elsevier Masson SAS. All rights reserved.

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

    Science.gov (United States)

    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

  15. (PS)2: protein structure prediction server version 3.0.

    Science.gov (United States)

    Huang, Tsun-Tsao; Hwang, Jenn-Kang; Chen, Chu-Huang; Chu, Chih-Sheng; Lee, Chi-Wen; Chen, Chih-Chieh

    2015-07-01

    Protein complexes are involved in many biological processes. Examining coupling between subunits of a complex would be useful to understand the molecular basis of protein function. Here, our updated (PS)(2) web server predicts the three-dimensional structures of protein complexes based on comparative modeling; furthermore, this server examines the coupling between subunits of the predicted complex by combining structural and evolutionary considerations. The predicted complex structure could be indicated and visualized by Java-based 3D graphics viewers and the structural and evolutionary profiles are shown and compared chain-by-chain. For each subunit, considerations with or without the packing contribution of other subunits cause the differences in similarities between structural and evolutionary profiles, and these differences imply which form, complex or monomeric, is preferred in the biological condition for the subunit. We believe that the (PS)(2) server would be a useful tool for biologists who are interested not only in the structures of protein complexes but also in the coupling between subunits of the complexes. The (PS)(2) is freely available at http://ps2v3.life.nctu.edu.tw/. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

  16. Child Support Payment: A Structural Model of Predictive Variables.

    Science.gov (United States)

    Wright, David W.; Price, Sharon J.

    A major area of concern in divorced families is compliance with child support payments. Aspects of the former spouse relationship that are predictive of compliance with court-ordered payment of child support were investigated in a sample of 58 divorced persons all of whom either paid or received child support. Structured interviews and…

  17. The prediction and discovery of Rayleigh line fine structure

    International Nuclear Information System (INIS)

    Fabelinskii, Immanuil L

    2000-01-01

    The history of the theoretical prediction and experimental discovery of the Rayleigh line fine structure (which belongs to one of the most important phenomena in optics and physics of condensed matter) is discussed along with the history of first publications concerning this topic. (from the history of physics)

  18. Towards a unified fatigue life prediction method for marine structures

    CERN Document Server

    Cui, Weicheng; Wang, Fang

    2014-01-01

    In order to apply the damage tolerance design philosophy to design marine structures, accurate prediction of fatigue crack growth under service conditions is required. Now, more and more people have realized that only a fatigue life prediction method based on fatigue crack propagation (FCP) theory has the potential to explain various fatigue phenomena observed. In this book, the issues leading towards the development of a unified fatigue life prediction (UFLP) method based on FCP theory are addressed. Based on the philosophy of the UFLP method, the current inconsistency between fatigue design and inspection of marine structures could be resolved. This book presents the state-of-the-art and recent advances, including those by the authors, in fatigue studies. It is designed to lead the future directions and to provide a useful tool in many practical applications. It is intended to address to engineers, naval architects, research staff, professionals and graduates engaged in fatigue prevention design and survey ...

  19. Structure life prediction at high temperature: present and future capabilities

    International Nuclear Information System (INIS)

    Chaboche, J.L.

    1987-01-01

    The life prediction techniques for high temperature conditions include several aspects which are considered successively in this article. Crack initiation criteria themselves, defined for the isolated volume element (the tension-compression specimen for example), including parametric relationships and continuous damage approaches and calculation of local stress and strain fields in the structure and their evolution under cyclic plasticity, which poses several difficult problems to obtain stabilized cyclic solutions are examined. The use of crack initiation criteria or damage rules from the result of the cyclic inelastic analysis and the prediction of crack growth in the structure are considered. Different levels are considered for the predictive tools: the classical approach, future methods presently under development and intermediate rules, which are already in use. Several examples are given on materials and components used either in the nuclear industry or in gas turbine engines. (author)

  20. I-TASSER server for protein 3D structure prediction

    Directory of Open Access Journals (Sweden)

    Zhang Yang

    2008-01-01

    Full Text Available Abstract Background Prediction of 3-dimensional protein structures from amino acid sequences represents one of the most important problems in computational structural biology. The community-wide Critical Assessment of Structure Prediction (CASP experiments have been designed to obtain an objective assessment of the state-of-the-art of the field, where I-TASSER was ranked as the best method in the server section of the recent 7th CASP experiment. Our laboratory has since then received numerous requests about the public availability of the I-TASSER algorithm and the usage of the I-TASSER predictions. Results An on-line version of I-TASSER is developed at the KU Center for Bioinformatics which has generated protein structure predictions for thousands of modeling requests from more than 35 countries. A scoring function (C-score based on the relative clustering structural density and the consensus significance score of multiple threading templates is introduced to estimate the accuracy of the I-TASSER predictions. A large-scale benchmark test demonstrates a strong correlation between the C-score and the TM-score (a structural similarity measurement with values in [0, 1] of the first models with a correlation coefficient of 0.91. Using a C-score cutoff > -1.5 for the models of correct topology, both false positive and false negative rates are below 0.1. Combining C-score and protein length, the accuracy of the I-TASSER models can be predicted with an average error of 0.08 for TM-score and 2 Å for RMSD. Conclusion The I-TASSER server has been developed to generate automated full-length 3D protein structural predictions where the benchmarked scoring system helps users to obtain quantitative assessments of the I-TASSER models. The output of the I-TASSER server for each query includes up to five full-length models, the confidence score, the estimated TM-score and RMSD, and the standard deviation of the estimations. The I-TASSER server is freely available

  1. Secbase: database module to retrieve secondary structure elements with ligand binding motifs.

    Science.gov (United States)

    Koch, Oliver; Cole, Jason; Block, Peter; Klebe, Gerhard

    2009-10-01

    Secbase is presented as a novel extension module of Relibase. It integrates the information about secondary structure elements into the retrieval facilities of Relibase. The data are accessible via the extended Relibase user interface, and integrated retrieval queries can be addressed using an extended version of Reliscript. The primary information about alpha-helices and beta-sheets is used as provided by the PDB. Furthermore, a uniform classification of all turn families, based on recent clustering methods, and a new helix assignment that is based on this turn classification has been included. Algorithms to analyze the geometric features of helices and beta-strands were also implemented. To demonstrate the performance of the Secbase implementation, some application examples are given. They provide new insights into the involvement of secondary structure elements in ligand binding. A survey of water molecules detected next to the N-terminus of helices is analyzed to show their involvement in ligand binding. Additionally, the parallel oriented NH groups at the alpha-helix N-termini provide special binding motifs to bind particular ligand functional groups with two adjacent oxygen atoms, e.g., as found in negatively charged carboxylate or phosphate groups, respectively. The present study also shows that the specific structure of the first turn of alpha-helices provides a suitable explanation for stabilizing charged structures. The magnitude of the overall helix macrodipole seems to have no or only a minor influence on binding. Furthermore, an overview of the involvement of secondary structure elements with the recognition of some important endogenous ligands such as cofactors shows some distinct preference for particular binding motifs and amino acids.

  2. Automatic prediction of facial trait judgments: appearance vs. structural models.

    Directory of Open Access Journals (Sweden)

    Mario Rojas

    Full Text Available Evaluating other individuals with respect to personality characteristics plays a crucial role in human relations and it is the focus of attention for research in diverse fields such as psychology and interactive computer systems. In psychology, face perception has been recognized as a key component of this evaluation system. Multiple studies suggest that observers use face information to infer personality characteristics. Interactive computer systems are trying to take advantage of these findings and apply them to increase the natural aspect of interaction and to improve the performance of interactive computer systems. Here, we experimentally test whether the automatic prediction of facial trait judgments (e.g. dominance can be made by using the full appearance information of the face and whether a reduced representation of its structure is sufficient. We evaluate two separate approaches: a holistic representation model using the facial appearance information and a structural model constructed from the relations among facial salient points. State of the art machine learning methods are applied to a derive a facial trait judgment model from training data and b predict a facial trait value for any face. Furthermore, we address the issue of whether there are specific structural relations among facial points that predict perception of facial traits. Experimental results over a set of labeled data (9 different trait evaluations and classification rules (4 rules suggest that a prediction of perception of facial traits is learnable by both holistic and structural approaches; b the most reliable prediction of facial trait judgments is obtained by certain type of holistic descriptions of the face appearance; and c for some traits such as attractiveness and extroversion, there are relationships between specific structural features and social perceptions.

  3. Predictive modeling of neuroanatomic structures for brain atrophy detection

    Science.gov (United States)

    Hu, Xintao; Guo, Lei; Nie, Jingxin; Li, Kaiming; Liu, Tianming

    2010-03-01

    In this paper, we present an approach of predictive modeling of neuroanatomic structures for the detection of brain atrophy based on cross-sectional MRI image. The underlying premise of applying predictive modeling for atrophy detection is that brain atrophy is defined as significant deviation of part of the anatomy from what the remaining normal anatomy predicts for that part. The steps of predictive modeling are as follows. The central cortical surface under consideration is reconstructed from brain tissue map and Regions of Interests (ROI) on it are predicted from other reliable anatomies. The vertex pair-wise distance between the predicted vertex and the true one within the abnormal region is expected to be larger than that of the vertex in normal brain region. Change of white matter/gray matter ratio within a spherical region is used to identify the direction of vertex displacement. In this way, the severity of brain atrophy can be defined quantitatively by the displacements of those vertices. The proposed predictive modeling method has been evaluated by using both simulated atrophies and MRI images of Alzheimer's disease.

  4. Teaching the foundations of quantum mechanics in secondary school: a proposed conceptual structure

    Directory of Open Access Journals (Sweden)

    Maria de los Angeles Fanaro

    2009-03-01

    Full Text Available This paper is part of a doctoral thesis that investigates Basic Quantum Mechanics (QM teaching in high school. A Conceptual Structure of Reference (CSR based on the Path Integral Method of Feynman (1965 was rebuilt and a Proposed Conceptual Structure for Teaching (PCST (Otero, 2006, 2007 the basics of Quantum Mechanics at secondary school was designed, analysed and carried out. This PCST does not follow the historical route and it is complementary to the canonical formalism. The concepts: probability distribution, quantum system, x(t alternative, amplitude of probability, sum of probability amplitude, action, Planck's constant, and classic-quantum transition were rebuilt with the students. Mathematical formalism was avoided by using simulation software assistance. The Proposed Conceptual Structure for Teaching (PCST is described and some results from the test carried out by the class group are discussed. This information allows the analysis of the Conceptual Structure Effectively Reconstructed (CSER to be initiated with the students.

  5. New tips for structure prediction by comparative modeling

    Science.gov (United States)

    Rayan, Anwar

    2009-01-01

    Comparative modelling is utilized to predict the 3-dimensional conformation of a given protein (target) based on its sequence alignment to experimentally determined protein structure (template). The use of such technique is already rewarding and increasingly widespread in biological research and drug development. The accuracy of the predictions as commonly accepted depends on the score of sequence identity of the target protein to the template. To assess the relationship between sequence identity and model quality, we carried out an analysis of a set of 4753 sequence and structure alignments. Throughout this research, the model accuracy was measured by root mean square deviations of Cα atoms of the target-template structures. Surprisingly, the results show that sequence identity of the target protein to the template is not a good descriptor to predict the accuracy of the 3-D structure model. However, in a large number of cases, comparative modelling with lower sequence identity of target to template proteins led to more accurate 3-D structure model. As a consequence of this study, we suggest new tips for improving the quality of omparative models, particularly for models whose target-template sequence identity is below 50%. PMID:19255646

  6. VMD-SS: A graphical user interface plug-in to calculate the protein secondary structure in VMD program.

    Science.gov (United States)

    Yahyavi, Masoumeh; Falsafi-Zadeh, Sajad; Karimi, Zahra; Kalatarian, Giti; Galehdari, Hamid

    2014-01-01

    The investigation on the types of secondary structure (SS) of a protein is important. The evolution of secondary structures during molecular dynamics simulations is a useful parameter to analyze protein structures. Therefore, it is of interest to describe VMD-SS (a software program) for the identification of secondary structure elements and its trajectories during simulation for known structures available at the Protein Data Bank (PDB). The program helps to calculate (1) percentage SS, (2) SS occurrence in each residue, (3) percentage SS during simulation, and (4) percentage residues in all SS types during simulation. The VMD-SS plug-in was designed using TCL script and stride to calculate secondary structure features. The database is available for free at http://science.scu.ac.ir/HomePage.aspx?TabID=13755.

  7. Pathways to Structure-Property Relationships of Peptide-Materials Interfaces: Challenges in Predicting Molecular Structures.

    Science.gov (United States)

    Walsh, Tiffany R

    2017-07-18

    An in-depth appreciation of how to manipulate the molecular-level recognition between peptides and aqueous materials interfaces, including nanoparticles, will advance technologies based on self-organized metamaterials for photonics and plasmonics, biosensing, catalysis, energy generation and harvesting, and nanomedicine. Exploitation of the materials-selective binding of biomolecules is pivotal to success in these areas and may be particularly key to producing new hierarchically structured biobased materials. These applications could be accomplished by realizing preferential adsorption of a given biomolecule onto one materials composition over another, one surface facet over another, or one crystalline polymorph over another. Deeper knowledge of the aqueous abiotic-biotic interface, to establish clear structure-property relationships in these systems, is needed to meet this goal. In particular, a thorough structural characterization of the surface-adsorbed peptides is essential for establishing these relationships but can often be challenging to accomplish via experimental approaches alone. In addition to myriad existing challenges associated with determining the detailed molecular structure of any molecule adsorbed at an aqueous interface, experimental characterization of materials-binding peptides brings new, complex challenges because many materials-binding peptides are thought to be intrinsically disordered. This means that these peptides are not amenable to experimental techniques that rely on the presence of well-defined secondary structure in the peptide when in the adsorbed state. To address this challenge, and in partnership with experiment, molecular simulations at the atomistic level can bring complementary and critical insights into the origins of this abiotic/biotic recognition and suggest routes for manipulating this phenomenon to realize new types of hybrid materials. For the reasons outlined above, molecular simulation approaches also face

  8. Three-dimensional protein structure prediction: Methods and computational strategies.

    Science.gov (United States)

    Dorn, Márcio; E Silva, Mariel Barbachan; Buriol, Luciana S; Lamb, Luis C

    2014-10-12

    A long standing problem in structural bioinformatics is to determine the three-dimensional (3-D) structure of a protein when only a sequence of amino acid residues is given. Many computational methodologies and algorithms have been proposed as a solution to the 3-D Protein Structure Prediction (3-D-PSP) problem. These methods can be divided in four main classes: (a) first principle methods without database information; (b) first principle methods with database information; (c) fold recognition and threading methods; and (d) comparative modeling methods and sequence alignment strategies. Deterministic computational techniques, optimization techniques, data mining and machine learning approaches are typically used in the construction of computational solutions for the PSP problem. Our main goal with this work is to review the methods and computational strategies that are currently used in 3-D protein prediction. Copyright © 2014 Elsevier Ltd. All rights reserved.

  9. Application of Functional Use Predictions to Aid in Structure ...

    Science.gov (United States)

    Humans are potentially exposed to thousands of anthropogenic chemicals in commerce. Recent work has shown that the bulk of this exposure may occur in near-field indoor environments (e.g., home, school, work, etc.). Advances in suspect screening analyses (SSA) now allow an improved understanding of the chemicals present in these environments. However, due to the nature of suspect screening techniques, investigators are often left with chemical formula predictions, with the possibility of many chemical structures matching to each formula. Here, newly developed quantitative structure-use relationship (QSUR) models are used to identify potential exposure sources for candidate structures. Previously, a suspect screening workflow was introduced and applied to house dust samples collected from the U.S. Department of Housing and Urban Development’s American Healthy Homes Survey (AHHS) [Rager, et al., Env. Int. 88 (2016)]. This workflow utilized the US EPA’s Distributed Structure-Searchable Toxicity (DSSTox) Database to link identified molecular features to molecular formulas, and ultimately chemical structures. Multiple QSUR models were applied to support the evaluation of candidate structures. These QSURs predict the likelihood of a chemical having a functional use commonly associated with consumer products having near-field use. For 3,228 structures identified as possible chemicals in AHHS house dust samples, we were able to obtain the required descriptors to appl

  10. Multi-Scale Modeling for Predicting the Stiffness and Strength of Hollow-Structured Metal Foams with Structural Hierarchy

    Directory of Open Access Journals (Sweden)

    Yong Yi

    2018-03-01

    Full Text Available This work was inspired by previous experiments which managed to establish an optimal template-dealloying route to prepare ultralow density metal foams. In this study, we propose a new analytical–numerical model of hollow-structured metal foams with structural hierarchy to predict its stiffness and strength. The two-level model comprises a main backbone and a secondary nanoporous structure. The main backbone is composed of hollow sphere-packing architecture, while the secondary one is constructed of a bicontinuous nanoporous network proposed to describe the nanoscale interactions in the shell. Firstly, two nanoporous models with different geometries are generated by Voronoi tessellation, then the scaling laws of the mechanical properties are determined as a function of relative density by finite volume simulation. Furthermore, the scaling laws are applied to identify the uniaxial compression behavior of metal foams. It is shown that the thickness and relative density highly influence the Young’s modulus and yield strength, and vacancy defect determines the foams being self-supported. The present study provides not only new insights into the mechanical behaviors of both nanoporous metals and metal foams, but also a practical guide for their fabrication and application.

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

    Directory of Open Access Journals (Sweden)

    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/.

  12. Benthic macrofaunal structure and secondary production in tropical estuaries on the Eastern Marine Ecoregion of Brazil.

    Science.gov (United States)

    Bissoli, Lorena B; Bernardino, Angelo F

    2018-01-01

    Tropical estuaries are highly productive and support diverse benthic assemblages within mangroves and tidal flats habitats. Determining differences and similarities of benthic assemblages within estuarine habitats and between regional ecosystems may provide scientific support for management of those ecosystems. Here we studied three tropical estuaries in the Eastern Marine Ecoregion of Brazil to assess the spatial variability of benthic assemblages from vegetated (mangroves) and unvegetated (tidal flats) habitats. A nested sampling design was used to determine spatial scales of variability in benthic macrofaunal density, biomass and secondary production. Habitat differences in benthic assemblage composition were evident, with mangrove forests being dominated by annelids (Oligochaeta and Capitellidae) whereas peracarid crustaceans were also abundant on tidal flats. Macrofaunal biomass, density and secondary production also differed between habitats and among estuaries. Those differences were related both to the composition of benthic assemblages and to random spatial variability, underscoring the importance of hierarchical sampling in estuarine ecological studies. Given variable levels of human impacts and predicted climate change effects on tropical estuarine assemblages in Eastern Brazil, our data support the use of benthic secondary production to address long-term changes and improved management of estuaries in Eastern Brazil.

  13. FRAMEWORK FOR STRUCTURAL ONLINE HEALTH MONITORING OF AGING AND DEGRADATION OF SECONDARY PIPING SYSTEMS DUE TO SOME ASPECTS OF EROSION

    Energy Technology Data Exchange (ETDEWEB)

    Gribok, Andrei V.; Agarwal, Vivek

    2017-06-01

    This paper describes the current state of research related to critical aspects of erosion and selected aspects of degradation of secondary components in nuclear power plants (NPPs). The paper also proposes a framework for online health monitoring of aging and degradation of secondary components. The framework consists of an integrated multi-sensor modality system, which can be used to monitor different piping configurations under different degradation conditions. The report analyses the currently known degradation mechanisms and available predictive models. Based on this analysis, the structural health monitoring framework is proposed. The Light Water Reactor Sustainability Program began to evaluate technologies that could be used to perform online monitoring of piping and other secondary system structural components in commercial NPPs. These online monitoring systems have the potential to identify when a more detailed inspection is needed using real time measurements, rather than at a pre-determined inspection interval. This transition to condition-based, risk-informed automated maintenance will contribute to a significant reduction of operations and maintenance costs that account for the majority of nuclear power generation costs. Furthermore, of the operations and maintenance costs in U.S. plants, approximately 80% are labor costs. To address the issue of rising operating costs and economic viability, in 2017, companies that operate the national nuclear energy fleet started the Delivering the Nuclear Promise Initiative, which is a 3 year program aimed at maintaining operational focus, increasing value, and improving efficiency. There is unanimous agreement between industry experts and academic researchers that identifying and prioritizing inspection locations in secondary piping systems (for example, in raw water piping or diesel piping) would eliminate many excessive in-service inspections. The proposed structural health monitoring framework takes aim at

  14. Does family structure matter? Comparing the life goals and aspirations of learners in secondary schools

    Directory of Open Access Journals (Sweden)

    Eugene Lee Davids

    2013-01-01

    Full Text Available The aim of this study was to compare the goals and aspirations of learners from single- and two-parent families. The study used a quantitative methodology with a cross-sectional comparative group design. The sample consisted of 853 Grade 11 learners from secondary schools in the Northern, Southern and Metro Central education districts in the Western Cape. The data were collected using the Aspirations Index and a short biographical questionnaire. The results suggest that there was a significant main effect of family structure on certain goals and aspirations of learners in secondary schools. These goals and aspirations included wealth, image, personal growth, relationships, and health. Furthermore, learners in single-parent families placed more emphasis on intrinsic goals.

  15. The Structures of the Alternative Conceptions of Preservice Secondary Teachers on Seasonal Changes

    Directory of Open Access Journals (Sweden)

    Junyoung Oh

    2005-03-01

    Full Text Available This study was to understand the components that influence preservice secondary teachers' conceptions about "seasonal changes". We selected 74 university science education students among whom 23 were in the second, 23 in the third, and 28 in the fourth year. The data collected from the paper-pencil test and individual interview with students. The results of this study show that the students had considerable apparent alternative conceptions, and that the 'distance theory' had most important effects on their alternative conceptions. It can be said that preservice secondary teachers' initial models of the seasonal change have their origin in their belief sets (specific theory related to 'seasonal change', on the basis of which they can interpret their observations and cultural information with the constraints of a naive framework of physics. The structures and possible sources of their alternative conceptions for overcoming these alternative conceptions were also discussed. Implications for preservice science teacher education related to the results were discussed.

  16. Landscape and variation of RNA secondary structure across the human transcriptome.

    Science.gov (United States)

    Wan, Yue; Qu, Kun; Zhang, Qiangfeng Cliff; Flynn, Ryan A; Manor, Ohad; Ouyang, Zhengqing; Zhang, Jiajing; Spitale, Robert C; Snyder, Michael P; Segal, Eran; Chang, Howard Y

    2014-01-30

    In parallel to the genetic code for protein synthesis, a second layer of information is embedded in all RNA transcripts in the form of RNA structure. RNA structure influences practically every step in the gene expression program. However, the nature of most RNA structures or effects of sequence variation on structure are not known. Here we report the initial landscape and variation of RNA secondary structures (RSSs) in a human family trio (mother, father and their child). This provides a comprehensive RSS map of human coding and non-coding RNAs. We identify unique RSS signatures that demarcate open reading frames and splicing junctions, and define authentic microRNA-binding sites. Comparison of native deproteinized RNA isolated from cells versus refolded purified RNA suggests that the majority of the RSS information is encoded within RNA sequence. Over 1,900 transcribed single nucleotide variants (approximately 15% of all transcribed single nucleotide variants) alter local RNA structure. We discover simple sequence and spacing rules that determine the ability of point mutations to impact RSSs. Selective depletion of 'riboSNitches' versus structurally synonymous variants at precise locations suggests selection for specific RNA shapes at thousands of sites, including 3' untranslated regions, binding sites of microRNAs and RNA-binding proteins genome-wide. These results highlight the potentially broad contribution of RNA structure and its variation to gene regulation.

  17. A multicontroller structure for teaching and designing predictive control strategies

    International Nuclear Information System (INIS)

    Hodouin, D.; Desbiens, A.

    1999-01-01

    The paper deals with the unification of the existing linear control algorithms in order to facilitate their transfer to the engineering students and to industry's engineers. The resulting control algorithm is the Global Predictive Control (GlobPC), which is now taught at the graduate and continuing education levels. GlobPC is based on an internal model framework where three independent control criteria are minimized: one for tracking, one for regulation and one for feedforward. This structure allows to obtain desired tracking, regulation and feedforward behaviors in an optimal way while keeping them perfectly separated. It also cleanly separates the deterministic and stochastic predictions of the process model output. (author)

  18. Mesoscopic structure prediction of nanoparticle assembly and coassembly: Theoretical foundation

    KAUST Repository

    Hur, Kahyun

    2010-01-01

    In this work, we present a theoretical framework that unifies polymer field theory and density functional theory in order to efficiently predict ordered nanostructure formation of systems having considerable complexity in terms of molecular structures and interactions. We validate our approach by comparing its predictions with previous simulation results for model systems. We illustrate the flexibility of our approach by applying it to hybrid systems composed of block copolymers and ligand coated nanoparticles. We expect that our approach will enable the treatment of multicomponent self-assembly with a level of molecular complexity that approaches experimental systems. © 2010 American Institute of Physics.

  19. Predicted crystal structures of molybdenum under high pressure

    Energy Technology Data Exchange (ETDEWEB)

    Wang, Bing; Zhang, Guang Biao [Institute for Computational Materials Science, School of Physics and Electronics, Henan University, Kaifeng 475004 (China); Wang, Yuan Xu, E-mail: wangyx@henu.edu.cn [Institute for Computational Materials Science, School of Physics and Electronics, Henan University, Kaifeng 475004 (China); Guizhou Provincial Key Laboratory of Computational Nano-Material Science, Institute of Applied Physics, Guizhou Normal College, Guiyang 550018 (China)

    2013-04-15

    Highlights: ► A double-hexagonal close-packed (dhcp) structure of molybdenum is predicted. ► Calculated acoustic velocity confirms the bcc–dhcp phase transition at 660 GPa. ► The valence electrons of dhcp Mo are mostly localized in the interstitial sites. -- Abstract: The high-pressure structures of molybdenum (Mo) at zero temperature have been extensively explored through the newly developed particle swarm optimization (PSO) algorithm on crystal structural prediction. All the experimental and earlier theoretical structures were successfully reproduced in certain pressure ranges, validating our methodology in application to Mo. A double-hexagonal close-packed (dhcp) structure found by Mikhaylushkin et al. (2008) [12] is confirmed by the present PSO calculations. The lattice parameters and physical properties of the dhcp phase were investigated based on first principles calculations. The phase transition occurs only from bcc phase to dhcp phase at 660 GPa and at zero temperature. The calculated acoustic velocities also indicate a transition from the bcc to dhcp phases for Mo. More intriguingly, the calculated density of states (DOS) shows that the dhcp structure remains metallic. The calculated electron density difference (EDD) reveals that its valence electrons are localized in the interstitial regions.

  20. Predicting protein structures with a multiplayer online game.

    Science.gov (United States)

    Cooper, Seth; Khatib, Firas; Treuille, Adrien; Barbero, Janos; Lee, Jeehyung; Beenen, Michael; Leaver-Fay, Andrew; Baker, David; Popović, Zoran; Players, Foldit

    2010-08-05

    People exert large amounts of problem-solving effort playing computer games. Simple image- and text-recognition tasks have been successfully 'crowd-sourced' through games, but it is not clear if more complex scientific problems can be solved with human-directed computing. Protein structure prediction is one such problem: locating the biologically relevant native conformation of a protein is a formidable computational challenge given the very large size of the search space. Here we describe Foldit, a multiplayer online game that engages non-scientists in solving hard prediction problems. Foldit players interact with protein structures using direct manipulation tools and user-friendly versions of algorithms from the Rosetta structure prediction methodology, while they compete and collaborate to optimize the computed energy. We show that top-ranked Foldit players excel at solving challenging structure refinement problems in which substantial backbone rearrangements are necessary to achieve the burial of hydrophobic residues. Players working collaboratively develop a rich assortment of new strategies and algorithms; unlike computational approaches, they explore not only the conformational space but also the space of possible search strategies. The integration of human visual problem-solving and strategy development capabilities with traditional computational algorithms through interactive multiplayer games is a powerful new approach to solving computationally-limited scientific problems.

  1. Predicting and validating protein interactions using network structure.

    Directory of Open Access Journals (Sweden)

    Pao-Yang Chen

    2008-07-01

    Full Text Available Protein interactions play a vital part in the function of a cell. As experimental techniques for detection and validation of protein interactions are time consuming, there is a need for computational methods for this task. Protein interactions appear to form a network with a relatively high degree of local clustering. In this paper we exploit this clustering by suggesting a score based on triplets of observed protein interactions. The score utilises both protein characteristics and network properties. Our score based on triplets is shown to complement existing techniques for predicting protein interactions, outperforming them on data sets which display a high degree of clustering. The predicted interactions score highly against test measures for accuracy. Compared to a similar score derived from pairwise interactions only, the triplet score displays higher sensitivity and specificity. By looking at specific examples, we show how an experimental set of interactions can be enriched and validated. As part of this work we also examine the effect of different prior databases upon the accuracy of prediction and find that the interactions from the same kingdom give better results than from across kingdoms, suggesting that there may be fundamental differences between the networks. These results all emphasize that network structure is important and helps in the accurate prediction of protein interactions. The protein interaction data set and the program used in our analysis, and a list of predictions and validations, are available at http://www.stats.ox.ac.uk/bioinfo/resources/PredictingInteractions.

  2. Phenomenological approach to precise creep life prediction by means of quantitative evaluation of strain rate acceleration in secondary creep

    International Nuclear Information System (INIS)

    Sato, Hiroyuki; Miyano, Takaya

    2010-01-01

    A method of creep life prediction by means of Strain-Acceleration-Parameter (SAP), α, is presented. The authors show that the shape of creep curve can be characterized by SAP that reflects magnitude of strain-rate change in secondary creep. The SAP-values, α are evaluated on magnesium-aluminium solution hardened alloys. Reconstruction of creep curves by combinations of SAP and minimum-creep rates are successfully performed, and the curves reasonably agree with experiments. The advantage of the proposed method is that the required parameters evaluated from individual creep curves are directly connected with the minimum creep rate. The predicted times-to-failure agree well with that obtained by experiments, and possibility of precise life time prediction by SAP is pronounced.

  3. Mechanical properties of amyloid-like fibrils defined by secondary structures

    Science.gov (United States)

    Bortolini, C.; Jones, N. C.; Hoffmann, S. V.; Wang, C.; Besenbacher, F.; Dong, M.

    2015-04-01

    Amyloid and amyloid-like fibrils represent a generic class of highly ordered nanostructures that are implicated in some of the most fatal neurodegenerative diseases. On the other hand, amyloids, by possessing outstanding mechanical robustness, have also been successfully employed as functional biomaterials. For these reasons, physical and chemical factors driving fibril self-assembly and morphology are extensively studied - among these parameters, the secondary structures and the pH have been revealed to be crucial, since a variation in pH changes the fibril morphology and net chirality during protein aggregation. It is important to quantify the mechanical properties of these fibrils in order to help the design of effective strategies for treating diseases related to the presence of amyloid fibrils. In this work, we show that by changing pH the mechanical properties of amyloid-like fibrils vary as well. In particular, we reveal that these mechanical properties are strongly related to the content of secondary structures. We analysed and estimated the Young's modulus (E) by comparing the persistence length (Lp) - measured from the observation of TEM images by using statistical mechanics arguments - with the mechanical information provided by peak force quantitative nanomechanical property mapping (PF-QNM). The secondary structure content and the chirality are investigated by means of synchrotron radiation circular dichroism (SR-CD). Results arising from this study could be fruitfully used as a protocol to investigate other medical or engineering relevant peptide fibrils.Amyloid and amyloid-like fibrils represent a generic class of highly ordered nanostructures that are implicated in some of the most fatal neurodegenerative diseases. On the other hand, amyloids, by possessing outstanding mechanical robustness, have also been successfully employed as functional biomaterials. For these reasons, physical and chemical factors driving fibril self-assembly and morphology

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

    Science.gov (United States)

    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

  5. The Interplay between Adolescent Needs and Secondary School Structures: Fostering Developmentally Responsive Middle and High School Environments across the Transition

    Science.gov (United States)

    Ellerbrock, Cheryl R.; Kiefer, Sarah M.

    2013-01-01

    Understanding the developmental responsiveness of secondary school environments may be an important factor in supporting students as they make the transition from one school to the next. Students' needs may or may not be met depending on the nature of the fit between their basic and developmental needs and secondary school structures at the middle…

  6. A quantitative analysis of secondary RNA structure using domination based parameters on trees

    Directory of Open Access Journals (Sweden)

    Zou Yue

    2006-03-01

    Full Text Available Abstract Background It has become increasingly apparent that a comprehensive database of RNA motifs is essential in order to achieve new goals in genomic and proteomic research. Secondary RNA structures have frequently been represented by various modeling methods as graph-theoretic trees. Using graph theory as a modeling tool allows the vast resources of graphical invariants to be utilized to numerically identify secondary RNA motifs. The domination number of a graph is a graphical invariant that is sensitive to even a slight change in the structure of a tree. The invariants selected in this study are variations of the domination number of a graph. These graphical invariants are partitioned into two classes, and we define two parameters based on each of these classes. These parameters are calculated for all small order trees and a statistical analysis of the resulting data is conducted to determine if the values of these parameters can be utilized to identify which trees of orders seven and eight are RNA-like in structure. Results The statistical analysis shows that the domination based parameters correctly distinguish between the trees that represent native structures and those that are not likely candidates to represent RNA. Some of the trees previously identified as candidate structures are found to be "very" RNA like, while others are not, thereby refining the space of structures likely to be found as representing secondary RNA structure. Conclusion Search algorithms are available that mine nucleotide sequence databases. However, the number of motifs identified can be quite large, making a further search for similar motif computationally difficult. Much of the work in the bioinformatics arena is toward the development of better algorithms to address the computational problem. This work, on the other hand, uses mathematical descriptors to more clearly characterize the RNA motifs and thereby reduce the corresponding search space. These

  7. Significance of uncertainties derived from settling tank model structure and parameters on predicting WWTP performance - A global sensitivity analysis study

    DEFF Research Database (Denmark)

    Ramin, Elham; Sin, Gürkan; Mikkelsen, Peter Steen

    2011-01-01

    Uncertainty derived from one of the process models – such as one-dimensional secondary settling tank (SST) models – can impact the output of the other process models, e.g., biokinetic (ASM1), as well as the integrated wastewater treatment plant (WWTP) models. The model structure and parameter...... and from the last aerobic bioreactor upstream to the SST (Garrett/hydraulic method). For model structure uncertainty, two one-dimensional secondary settling tank (1-D SST) models are assessed, including a first-order model (the widely used Takács-model), in which the feasibility of using measured...... uncertainty of settler models can therefore propagate, and add to the uncertainties in prediction of any plant performance criteria. Here we present an assessment of the relative significance of secondary settling model performance in WWTP simulations. We perform a global sensitivity analysis (GSA) based...

  8. AFM observation of silk fibroin on mica substrates: morphologies reflecting the secondary structures

    Energy Technology Data Exchange (ETDEWEB)

    Yamada, Kazushi; Tsuboi, Yasuyuki; Itaya, Akira

    2003-09-01

    Bombyx mori silk fibroin was fixed on mica substrates by cast of aqueous fibroin solutions, and the microscopic morphologies of the samples were revealed by means of atomic force microscopy. By adjusting the method used to prepare the solution, we succeeded in forming quasi-2-dimensional thin films in which a network of fibroin molecules developed over the substrate. The film network consisted of fibroin in a random coil structure. The morphology of the network changed after thermal or methanol treatments, which are known to convert the secondary structure of fibroin from the random coil to the {beta}-sheet type. In both of these cases, the network morphology disappeared and characteristic island-like morphologies appeared. On the other hand, temporally evolving gelation occurred in a fibroin solution due to the formation of {beta}-sheet crystals. Such islands were also observable in a specimen prepared by the cast of the gel-containing solution. Based on these results, it was concluded that the islands consist of {beta}-sheet crystals. Of particular interest is the observation that all of the islands had a common thickness value of 1.3 nm. These morphologies are discussed in terms of the secondary structure of fibroin.

  9. Secondary Structure Preferences of Mn2+ Binding Sites in Bacterial Proteins

    Directory of Open Access Journals (Sweden)

    Tatyana Aleksandrovna Khrustaleva

    2014-01-01

    Full Text Available 3D structures of proteins with coordinated Mn2+ ions from bacteria with low, average, and high genomic GC-content have been analyzed (149 PDB files were used. Major Mn2+ binders are aspartic acid (6.82% of Asp residues, histidine (14.76% of His residues, and glutamic acid (3.51% of Glu residues. We found out that the motif of secondary structure “beta strand-major binder-random coil” is overrepresented around all the three major Mn2+ binders. That motif may be followed by either alpha helix or beta strand. Beta strands near Mn2+ binding residues should be stable because they are enriched by such beta formers as valine and isoleucine, as well as by specific combinations of hydrophobic and hydrophilic amino acid residues characteristic to beta sheet. In the group of proteins from GC-rich bacteria glutamic acid residues situated in alpha helices frequently coordinate Mn2+ ions, probably, because of the decrease of Lys usage under the influence of mutational GC-pressure. On the other hand, the percentage of Mn2+ sites with at least one amino acid in the “beta strand-major binder-random coil” motif of secondary structure (77.88% does not depend on genomic GC-content.

  10. Virality Prediction and Community Structure in Social Networks

    Science.gov (United States)

    Weng, Lilian; Menczer, Filippo; Ahn, Yong-Yeol

    2013-08-01

    How does network structure affect diffusion? Recent studies suggest that the answer depends on the type of contagion. Complex contagions, unlike infectious diseases (simple contagions), are affected by social reinforcement and homophily. Hence, the spread within highly clustered communities is enhanced, while diffusion across communities is hampered. A common hypothesis is that memes and behaviors are complex contagions. We show that, while most memes indeed spread like complex contagions, a few viral memes spread across many communities, like diseases. We demonstrate that the future popularity of a meme can be predicted by quantifying its early spreading pattern in terms of community concentration. The more communities a meme permeates, the more viral it is. We present a practical method to translate data about community structure into predictive knowledge about what information will spread widely. This connection contributes to our understanding in computational social science, social media analytics, and marketing applications.

  11. Protein secondary structure and stability determined by combining exoproteolysis and matrix-assisted laser desorption/ionization time-of-flight mass spectrometry.

    Science.gov (United States)

    Villanueva, Josep; Villegas, Virtudes; Querol, Enrique; Avilés, Francesc X; Serrano, Luis

    2002-09-01

    In the post-genomic era, several projects focused on the massive experimental resolution of the three-dimensional structures of all the proteins of different organisms have been initiated. Simultaneously, significant progress has been made in the ab initio prediction of protein three-dimensional structure. One of the keys to the success of such a prediction is the use of local information (i.e. secondary structure). Here we describe a new limited proteolysis methodology, based on the use of unspecific exoproteases coupled with matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS), to map quickly secondary structure elements of a protein from both ends, the N- and C-termini. We show that the proteolytic patterns (mass spectra series) obtained can be interpreted in the light of the conformation and local stability of the analyzed proteins, a direct correlation being observed between the predicted and the experimentally derived protein secondary structure. Further, this methodology can be easily applied to check rapidly the folding state of a protein and characterize mutational effects on protein conformation and stability. Moreover, given global stability information, this methodology allows one to locate the protein regions of increased or decreased conformational stability. All of this can be done with a small fraction of the amount of protein required by most of the other methods for conformational analysis. Thus limited exoproteolysis, together with MALDI-TOF MS, can be a useful tool to achieve quickly the elucidation of protein structure and stability. Copyright 2002 John Wiley & Sons, Ltd.

  12. [Iatrogenic hyperthyroidism secondary to weight loss medication. Predictive factors for their precocious detention].

    Science.gov (United States)

    Goday, A; Recasens, A; Manresa, J M; Vila, J; Moix, S

    1998-05-01

    To establish the differential clinical characteristics between the Iatrogenic hyperthyroidism for not conventional medication for obesity treatment (weight losers) and the endogenous by Graves Basedow disease. Observational and analytical study, populational based, in the one which prospectively were compared cases with Iatrogenic hyperthyroidism (secondary to weight losers) with those with endogenous hyperthyroidism (Graves Basedow disease) as controls. Consisted of the variable clinical record of 100 correlative patients that consulted in specialized attention of endocrinology for Iatrogenic hyperthyroidism secondary to weight losers and for Graves Basedow disease. The differences observed between Iatrogenic hyperthyroidism (secondary to weight losers) (n = 43) as compared to endogenous hyperthyroidism (Graves Basedow disease) (n = 57) were: smaller age (31.8 +/- 10 as compared to 37.8 +/- 12.6 years), greater body mass index (27.6 +/- 7.2 as compared to 23.4 +/- 3.1), smaller goiter frequency (16.3% as compared to 84.2%) as well as absence of signs of ophthalmopathy (0% as compared to 57.9%). Both groups had low levels of TSH, and the difference rests in the values of free T4, low in the first group and increased in the endogenous hyperthyroidism. The odds ratio were: IMC > 27: 3.92 (0.91-16.72), age weight losers use was not selective of the first group, being detected in a 12.3% of cases of endogenous hyperthyroidism, though in periods of time remoter in relationship to the beginning of the clinic. In the differential diagnosis of a case of hyperthyroidism, it can be suspected Iatrogenic hyperthyroidism (secondary to weight losers) for medication for the obesity in patients of the feminine sex with overweight, without previous or familiar history of thyroid disease, and in those which in the physical exploration is not verified goiter neither ophthalmopathy.

  13. Structure of the secondary xylem of Aniba Aubl. species from the Brazilian Amazon

    Directory of Open Access Journals (Sweden)

    Cláudia Viana Urbinati

    2014-09-01

    Full Text Available The aim of this study was to characterize the wood of Aniba species from the Brazilian Amazon, on the basis of specimens in the wood collection of the Herbarium of the Museu Paraense Emílio Goeldi, in the city of Belém, Brazil. The species were found to present a homogeneous structure in the secondary xylem, as defined by the location of oil cells; the presence of tyloses and crystals; and singularities of the radial and axial parenchyma.

  14. Predicting protein structures with a multiplayer online game

    OpenAIRE

    Cooper, Seth; Khatib, Firas; Treuille, Adrien; Barbero, Janos; Lee, Jeehyung; Beenen, Michael; Leaver-Fay, Andrew; Baker, David; Popović, Zoran

    2010-01-01

    People exert significant amounts of problem solving effort playing computer games. Simple image- and text-recognition tasks have been successfully crowd-sourced through gamesi, ii, iii, but it is not clear if more complex scientific problems can be similarly solved with human-directed computing. Protein structure prediction is one such problem: locating the biologically relevant native conformation of a protein is a formidable computational challenge given the very large size of the search sp...

  15. Improved hybrid optimization algorithm for 3D protein structure prediction.

    Science.gov (United States)

    Zhou, Changjun; Hou, Caixia; Wei, Xiaopeng; Zhang, Qiang

    2014-07-01

    A new improved hybrid optimization algorithm - PGATS algorithm, which is based on toy off-lattice model, is presented for dealing with three-dimensional protein structure prediction problems. The algorithm combines the particle swarm optimization (PSO), genetic algorithm (GA), and tabu search (TS) algorithms. Otherwise, we also take some different improved strategies. The factor of stochastic disturbance is joined in the particle swarm optimization to improve the search ability; the operations of crossover and mutation that are in the genetic algorithm are changed to a kind of random liner method; at last tabu search algorithm is improved by appending a mutation operator. Through the combination of a variety of strategies and algorithms, the protein structure prediction (PSP) in a 3D off-lattice model is achieved. The PSP problem is an NP-hard problem, but the problem can be attributed to a global optimization problem of multi-extremum and multi-parameters. This is the theoretical principle of the hybrid optimization algorithm that is proposed in this paper. The algorithm combines local search and global search, which overcomes the shortcoming of a single algorithm, giving full play to the advantage of each algorithm. In the current universal standard sequences, Fibonacci sequences and real protein sequences are certified. Experiments show that the proposed new method outperforms single algorithms on the accuracy of calculating the protein sequence energy value, which is proved to be an effective way to predict the structure of proteins.

  16. High cycle fatigue analysis of vortex suppression plate and secondary core support structures

    International Nuclear Information System (INIS)

    Xue Guohong; Li Yuan; Zhao Feiyun; Feng Shaodong; Yu Hao

    2013-01-01

    Background: Reactor internals are important equipment s in the reactor coolant system, its structure design needs high reliability in the entire lifetime, Reactor internals have occurred breakdown and the damage event due to flow induced vibrations in the domestic and foreign nuclear power plants, which make immediate influence on reactor safe operation and economic efficiency. Purpose: In this work, the dynamic response of reactor internals-vortex suppression plate and secondary core support structure (SCSS) under the loading from pump induced vibrations and flow induced vibrations are studied. Methods: Based on the finite element model of SCSS, Spectrum analysis and the harmonious analysis are performed, in order to get the response of the structure under flow induced vibrations. Then, the high fatigue of the structure is assessed according to the ASME B and PV Code. Results: The results indicate that alternate stresses of all the components satisfy the limiting value in the correlative requirements. Conclusions: The structure of SCSS could bear the vibration induced from the flow and the pump, and the method used in this article provides the reference for other reactor internals structure analysis like this. (authors)

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

    Science.gov (United States)

    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.

  18. Protein Secondary Structures (α-helix and β-sheet) at a Cellular Level and Protein Fractions in Relation to Rumen Degradation Behaviours of Protein: A New Approach

    International Nuclear Information System (INIS)

    Yu, P.

    2007-01-01

    percentage of β-sheets (from 37.2% to 49.8%: S-FTIR absorption intensity) and reduced the α-helix to β-sheet ratio (from 0.3 to 0.7) in the golden flaxseeds, which indicated a negative effect of the roasting on protein values, utilisation and bioavailability. These results were proved by the Cornell Net Carbohydrate Protein System in situ animal trial, which also revealed that roasting increased the amount of protein bound to lignin, and well as of the Maillard reaction protein (both of which are poorly used by ruminants), and increased the level of indigestible and undegradable protein in ruminants. The present results demonstrate the potential of highly spatially resolved synchrotron-based infrared microspectroscopy to locate 'pure' protein in feed tissues, and reveal protein secondary structures and digestive behaviour, making a significant step forward in and an important contribution to protein nutritional research. Further study is needed to determine the sensitivities of protein secondary structures to various heat-processing conditions, and to quantify the relationship between protein secondary structures and the nutrient availability and digestive behaviour of various protein sources. Information from the present study arising from the synchrotron-based IR probing of the protein secondary structures of protein sources at the cellular level will be valuable as a guide to maintaining protein quality and predicting digestive behaviours

  19. Protein Secondary Structures (alpha-helix and beta-sheet) at a Cellular Levle and Protein Fractions in Relation to Rumen Degradation Behaviours of Protein: A New Approach

    Energy Technology Data Exchange (ETDEWEB)

    Yu,P.

    2007-01-01

    -FTIR absorption intensity), increased the percentage of {beta}-sheets (from 37.2% to 49.8%: S-FTIR absorption intensity) and reduced the {alpha}-helix to {beta}-sheet ratio (from 0.3 to 0.7) in the golden flaxseeds, which indicated a negative effect of the roasting on protein values, utilisation and bioavailability. These results were proved by the Cornell Net Carbohydrate Protein System in situ animal trial, which also revealed that roasting increased the amount of protein bound to lignin, and well as of the Maillard reaction protein (both of which are poorly used by ruminants), and increased the level of indigestible and undegradable protein in ruminants. The present results demonstrate the potential of highly spatially resolved synchrotron-based infrared microspectroscopy to locate 'pure' protein in feed tissues, and reveal protein secondary structures and digestive behaviour, making a significant step forward in and an important contribution to protein nutritional research. Further study is needed to determine the sensitivities of protein secondary structures to various heat-processing conditions, and to quantify the relationship between protein secondary structures and the nutrient availability and digestive behaviour of various protein sources. Information from the present study arising from the synchrotron-based IR probing of the protein secondary structures of protein sources at the cellular level will be valuable as a guide to maintaining protein quality and predicting digestive behaviours.

  20. Probabilistic approaches to life prediction of nuclear plant structural components

    International Nuclear Information System (INIS)

    Villain, B.; Pitner, P.; Procaccia, H.

    1996-01-01

    In the last decade there has been an increasing interest at EDF in developing and applying probabilistic methods for a variety of purposes. In the field of structural integrity and reliability they are used to evaluate the effect of deterioration due to aging mechanisms, mainly on major passive structural components such as steam generators, pressure vessels and piping in nuclear plants. Because there can be numerous uncertainties involved in a assessment of the performance of these structural components, probabilistic methods. The benefits of a probabilistic approach are the clear treatment of uncertainly and the possibility to perform sensitivity studies from which it is possible to identify and quantify the effect of key factors and mitigative actions. They thus provide information to support effective decisions to optimize In-Service Inspection planning and maintenance strategies and for realistic lifetime prediction or reassessment. The purpose of the paper is to discuss and illustrate the methods available at EDF for probabilistic component life prediction. This includes a presentation of software tools in classical, Bayesian and structural reliability, and an application on two case studies (steam generator tube bundle, reactor pressure vessel). (authors)

  1. Probabilistic approaches to life prediction of nuclear plant structural components

    International Nuclear Information System (INIS)

    Villain, B.; Pitner, P.; Procaccia, H.

    1996-01-01

    In the last decade there has been an increasing interest at EDF in developing and applying probabilistic methods for a variety of purposes. In the field of structural integrity and reliability they are used to evaluate the effect of deterioration due to aging mechanisms, mainly on major passive structural components such as steam generators, pressure vessels and piping in nuclear plants. Because there can be numerous uncertainties involved in an assessment of the performance of these structural components, probabilistic methods provide an attractive alternative or supplement to more conventional deterministic methods. The benefits of a probabilistic approach are the clear treatment of uncertainty and the possibility to perform sensitivity studies from which it is possible to identify and quantify the effect of key factors and mitigative actions. They thus provide information to support effective decisions to optimize In-Service Inspection planning and maintenance strategies and for realistic lifetime prediction or reassessment. The purpose of the paper is to discuss and illustrate the methods available at EDF for probabilistic component life prediction. This includes a presentation of software tools in classical, Bayesian and structural reliability, and an application on two case studies (steam generator tube bundle, reactor pressure vessel)

  2. Structure Elucidation of Unknown Metabolites in Metabolomics by Combined NMR and MS/MS Prediction.

    Science.gov (United States)

    Boiteau, Rene M; Hoyt, David W; Nicora, Carrie D; Kinmonth-Schultz, Hannah A; Ward, Joy K; Bingol, Kerem

    2018-01-17

    We introduce a cheminformatics approach that combines highly selective and orthogonal structure elucidation parameters; accurate mass, MS/MS (MS²), and NMR into a single analysis platform to accurately identify unknown metabolites in untargeted studies. The approach starts with an unknown LC-MS feature, and then combines the experimental MS/MS and NMR information of the unknown to effectively filter out the false positive candidate structures based on their predicted MS/MS and NMR spectra. We demonstrate the approach on a model mixture, and then we identify an uncatalogued secondary metabolite in Arabidopsis thaliana . The NMR/MS² approach is well suited to the discovery of new metabolites in plant extracts, microbes, soils, dissolved organic matter, food extracts, biofuels, and biomedical samples, facilitating the identification of metabolites that are not present in experimental NMR and MS metabolomics databases.

  3. Predicting Reactive Transport Dynamics in Carbonates using Initial Pore Structure

    Science.gov (United States)

    Menke, H. P.; Nunes, J. P. P.; Blunt, M. J.

    2017-12-01

    Understanding rock-fluid interaction at the pore-scale is imperative for accurate predictive modelling of carbon storage permanence. However, coupled reactive transport models are computationally expensive, requiring either a sacrifice of resolution or high performance computing to solve relatively simple geometries. Many recent studies indicate that initial pore structure many be the dominant mechanism in determining the dissolution regime. Here we investigate how well the initial pore structure is predictive of distribution and amount of dissolution during reactive flow using particle tracking on the initial image. Two samples of carbonate rock with varying initial pore space heterogeneity were reacted with reservoir condition CO2-saturated brine and scanned dynamically during reactive flow at a 4-μm resolution between 4 and 40 times using 4D X-ray micro-tomography over the course of 1.5 hours using μ-CT. Flow was modelled on the initial binarized image using a Navier-Stokes solver. Particle tracking was then run on the velocity fields, the streamlines were traced, and the streamline density was calculated both on a voxel-by-voxel and a channel-by-channel basis. The density of streamlines was then compared to the amount of dissolution in subsequent time steps during reaction. It was found that for the flow and transport regimes studied, the streamline density distribution in the initial image accurately predicted the dominant pathways of dissolution and gave good indicators of the type of dissolution regime that would later develop. This work suggests that the eventual reaction-induced changes in pore structure are deterministic rather than stochastic and can be predicted with high resolution imaging of unreacted rock.

  4. The incidence angle influence on the structure of secondary-emission characteristics of single crystals

    International Nuclear Information System (INIS)

    Gasanov, E.R.; Aliyev, B.Z.

    2012-01-01

    Full text : The dependences of Wand MO single crystals in different atom planes have been studied in this work. It is revealed that maximums are added to each dependency and also minimums of first and second degree. This fact is explained by diffraction dynamic theory. It is established that electron diffraction oriented not perpendicularly to crystal surface is the reason of appearance of second order structure on studied secondary-emission characteristics. In the present work being the continuation and development of SEE investigations of high-melting metal single crystals begun earlier by authors, the structure dependence of SEE main characteristics of angle has been studied. This angle has been chosen because as it is mentioned before the bad repeatability in different experiments for it is observed

  5. Structure and formation of convection of secondary rainbands in a simulated typhoon Jangmi (2008)

    Science.gov (United States)

    Xiao, Jing; Tan, Zhe-Min; Chow, Kim-Chiu

    2018-04-01

    Secondary rainbands in tropical cyclone are relatively transient compared with the quasi-stationary principle rainbands. To have a better understanding on their convective structure, a cloud-resolving scale numerical simulation of the super typhoon Jangmi (2008) was performed. The results suggest that the convections in secondary rainbands have some distinctive features that may not be seen in other types of rainbands in tropical cyclone. First, they have a front-like structure and are triggered to form above the boundary layer by the convergence of the above-boundary outflow from the inner side (warmer) and the descending inflow (colder) from the outer side. These elevated convections can be further confirmed by the three-dimensional backward trajectory calculations. Second, due to the release in baroclinic energy, the lower portion of the mid-level inflow from outside may penetrate into the bottom of the convection tower and may help accelerate the boundary layer inflow in the inner side. Third, the local maximum tangential wind is concentrated in the updraft region, with a lower portion which is dipping inward. Tangential wind budget analysis also suggests that the maxima are mainly contributed by the updraft advection, and can be advected cyclonically downstream by the tangential advection.

  6. Contribution of long-range interactions to the secondary structure of an unfolded globin.

    Science.gov (United States)

    Fedyukina, Daria V; Rajagopalan, Senapathy; Sekhar, Ashok; Fulmer, Eric C; Eun, Ye-Jin; Cavagnero, Silvia

    2010-09-08

    This work explores the effect of long-range tertiary contacts on the distribution of residual secondary structure in the unfolded state of an alpha-helical protein. N-terminal fragments of increasing length, in conjunction with multidimensional nuclear magnetic resonance, were employed. A protein representative of the ubiquitous globin fold was chosen as the model system. We found that, while most of the detectable alpha-helical population in the unfolded ensemble does not depend on the presence of the C-terminal region (corresponding to the native G and H helices), specific N-to-C long-range contacts between the H and A-B-C regions enhance the helical secondary structure content of the N terminus (A-B-C regions). The simple approach introduced here, based on the evaluation of N-terminal polypeptide fragments of increasing length, is of general applicability to identify the influence of long-range interactions in unfolded proteins. Copyright 2010 Biophysical Society. Published by Elsevier Inc. All rights reserved.

  7. Electromagnetic Fields Effects on the Secondary Structure of Lysozyme and Bioprotective Effectiveness of Trehalose

    Directory of Open Access Journals (Sweden)

    Emanuele Calabrò

    2012-01-01

    Full Text Available FTIR spectroscopy was used to investigate the effects of extremely low frequency (50 Hz electromagnetic field and of microwaves at 900 MHz on the secondary structure of a typical protein, the lysozyme, evaluating the bioprotective effectiveness of trehalose. Lysozyme in D2O solution (60 mg/ml was exposed to 50 Hz frequency electromagnetic field at 180 μT. The FTIR spectra indicated an increase of CH2 group at 1921 and 1853 cm−1 after 3 h of exposure. Such effect was not observed after the addition of trehalose (150 mg/mL at the same exposure conditions. Lysozyme dissolved in D2O at the concentration of 100 mg/mL was exposed up to 4 h to 900 MHz mobile phone microwaves at 25 mA/m. A significant increase in intensity of the amide I vibration band in the secondary structure of the protein was observed after 4 h exposure to microwaves. This effect was inhibited by the presence of trehalose at the concentration of 150 mg/mL. Fourier self-deconvolution spectral analysis of lysozyme in D2O solution after exposure to microwaves revealed an increase in intensity of the conformational components of amide I mode, particularly of β-sheet and turn that can be attributed to disorder and unfolding processes of the protein.

  8. Compensatory mutations cause excess of antagonistic epistasis in RNA secondary structure folding

    Directory of Open Access Journals (Sweden)

    Adami Christoph

    2003-02-01

    Full Text Available Background The rate at which fitness declines as an organism's genome accumulates random mutations is an important variable in several evolutionary theories. At an intuitive level, it might seem natural that random mutations should tend to interact synergistically, such that the rate of mean fitness decline accelerates as the number of random mutations is increased. However, in a number of recent studies, a prevalence of antagonistic epistasis (the tendency of multiple mutations to have a mitigating rather than reinforcing effect has been observed. Results We studied in silico the net amount and form of epistatic interactions in RNA secondary structure folding by measuring the fraction of neutral mutants as a function of mutational distance d. We found a clear prevalence of antagonistic epistasis in RNA secondary structure folding. By relating the fraction of neutral mutants at distance d to the average neutrality at distance d, we showed that this prevalence derives from the existence of many compensatory mutations at larger mutational distances. Conclusions Our findings imply that the average direction of epistasis in simple fitness landscapes is directly related to the density with which fitness peaks are distributed in these landscapes.

  9. Compensatory mutations cause excess of antagonistic epistasis in RNA secondary structure folding.

    Science.gov (United States)

    Wilke, Claus O; Lenski, Richard E; Adami, Christoph

    2003-02-05

    The rate at which fitness declines as an organism's genome accumulates random mutations is an important variable in several evolutionary theories. At an intuitive level, it might seem natural that random mutations should tend to interact synergistically, such that the rate of mean fitness decline accelerates as the number of random mutations is increased. However, in a number of recent studies, a prevalence of antagonistic epistasis (the tendency of multiple mutations to have a mitigating rather than reinforcing effect) has been observed. We studied in silico the net amount and form of epistatic interactions in RNA secondary structure folding by measuring the fraction of neutral mutants as a function of mutational distance d. We found a clear prevalence of antagonistic epistasis in RNA secondary structure folding. By relating the fraction of neutral mutants at distance d to the average neutrality at distance d, we showed that this prevalence derives from the existence of many compensatory mutations at larger mutational distances. Our findings imply that the average direction of epistasis in simple fitness landscapes is directly related to the density with which fitness peaks are distributed in these landscapes.

  10. Short Oligonucleotides Aligned in Stretched Humid Matrix: Secondary DNA Structure in Poly(vinyl alcohol) Environment

    KAUST Repository

    Hanczyc, Piotr

    2012-04-24

    We report that short, synthetic, double- as well as single-stranded DNA can be aligned in stretched humid poly(vinyl alcohol) (PVA) matrix, and the secondary structure (nucleobase orientation) can be characterized with linear dichroism (LD) spectroscopy. Oligonucleotides of lengths varying between 10 (3.4 nm) and 60 bases (20.4 nm) were investigated with respect to structural properties in the gel-like polymer environment. The DNA conformation as a function of relative humidity reveals a strong dependence of helical structure of DNA on PVA hydration level, results of relevance for nanotechnical studies of DNA-based supramolecular systems. Also, the PVA gel could provide possibilities to test models for nucleic acid interactions and distribution in cell contexts, including structural stability of genetic material in the cell and PVA-packaging for gene delivery. A method by which duplex oligonucleotides, with sequences designed to provide specific binding sites, become amenable to polarized-light spectroscopy opens up new possibilities for studying structure in DNA complexes with small adduct molecules as well as proteins. © 2012 American Chemical Society.

  11. Prediction of Cracking Induced by Indirect Actions in RC Structures

    Science.gov (United States)

    Anerdi, Costanza; Bertagnoli, Gabriele; Gino, Diego; Malavisi, Marzia; Mancini, Giuseppe

    2017-10-01

    Cracking of concrete plays a key role in reinforced concrete (RC) structures design, especially in serviceability conditions. A variety of reasons contribute to develop cracking and its presence in concrete structures is to be considered as almost unavoidable. Therefore, a good control of the phenomenon in order to provide durability is required. Cracking development is due to tensile stresses that arise in concrete structures as a result of the action of direct external loads or restrained endogenous deformations. This paper focuses on cracking induced by indirect actions. In fact, there is very limited literature regarding this particular phenomenon if compared to its high incidence in the construction practice. As a consequence, the correct prediction of the crack opening, width and position when structures are subjected to imposed deformations, such as massive castings or other highly restrained structures, becomes a compelling task, not so much for the structural capacity, as for their durability. However, this is only partially addressed by commonly used design methods, which are usually intended for direct actions. A set of non-linear analysis on simple tie models is performed using the Finite Element Method in order to study the cracking process under imposed deformations. Different concrete grades have been considered and analysed. The results of this study have been compared with the provisions of the most common codes.

  12. Bitter or not? BitterPredict, a tool for predicting taste from chemical structure.

    Science.gov (United States)

    Dagan-Wiener, Ayana; Nissim, Ido; Ben Abu, Natalie; Borgonovo, Gigliola; Bassoli, Angela; Niv, Masha Y

    2017-09-21

    Bitter taste is an innately aversive taste modality that is considered to protect animals from consuming toxic compounds. Yet, bitterness is not always noxious and some bitter compounds have beneficial effects on health. Hundreds of bitter compounds were reported (and are accessible via the BitterDB http://bitterdb.agri.huji.ac.il/dbbitter.php ), but numerous additional bitter molecules are still unknown. The dramatic chemical diversity of bitterants makes bitterness prediction a difficult task. Here we present a machine learning classifier, BitterPredict, which predicts whether a compound is bitter or not, based on its chemical structure. BitterDB was used as the positive set, and non-bitter molecules were gathered from literature to create the negative set. Adaptive Boosting (AdaBoost), based on decision trees machine-learning algorithm was applied to molecules that were represented using physicochemical and ADME/Tox descriptors. BitterPredict correctly classifies over 80% of the compounds in the hold-out test set, and 70-90% of the compounds in three independent external sets and in sensory test validation, providing a quick and reliable tool for classifying large sets of compounds into bitter and non-bitter groups. BitterPredict suggests that about 40% of random molecules, and a large portion (66%) of clinical and experimental drugs, and of natural products (77%) are bitter.

  13. Structural syntactic prediction measured with ELAN: evidence from ERPs.

    Science.gov (United States)

    Fonteneau, Elisabeth

    2013-02-08

    The current study used event-related potentials (ERPs) to investigate how and when argument structure information is used during the processing of sentences with a filler-gap dependency. We hypothesize that one specific property - animacy (living vs. non-living) - is used by the parser during the building of the syntactic structure. Participants heard sentences that were rated off-line as having an expected noun (Who did the Lion King chase the caravan with?) or an unexpected noun (Who did Lion King chase the animal with?). This prediction is based on the animacy properties relation between the wh-word and the noun in the object position. ERPs from the noun in the unexpected condition (animal) elicited a typical Early Left Anterior Negativity (ELAN)/P600 complex compared to the noun in the expected condition (caravan). Firstly, these results demonstrate that the ELAN reflects not only grammatical category violation but also animacy property expectations in filler-gap dependency. Secondly, our data suggests that the language comprehension system is able to make detailed predictions about aspects of the upcoming words to build up the syntactic structure. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

  14. [Vitamin D deficiency prediction by patient questionnaire and secondary hyperparathyroidism in a cohort of 526 healthy subjects in their fifties].

    Science.gov (United States)

    Laroche, Michel; Nigon, Delphine; Gennero, Isabelle; Lassoued, Slim; Pouilles, Jean-Michel; Trémolières, Florence; Vallet, Marion; Tack, Ivan

    2015-01-01

    Can vitamin D deficiency be predicted by patient questionnaire? Does it lead to secondary hyperparathyroidism that may cause excessive bone resorption? We studied non-osteoporotic subjects in their fifties, in whom vitamin D levels are often tested. Patients hospitalised for degenerative osteoarthritis or consulting for assessment of menopause, without renal failure and not treated with vitamin D, completed a questionnaire on sun exposure and underwent measurement of serum calcium, creatinine, 25OH vitamin D, PTH and CTX. Five hundred and twenty-six subjects, mean age 54.6 years (71% women), were investigated throughout the year. 25OH vitamin D levels were correlated with sun exposure and varied according to the month of the year, unlike PTH and CTX levels. From November to May, over 90% of subjects had 25OH vitamin D levelssecondary hyperparathyroidism, characterised by serum calcium65pg/mL, associated with increased CTX levels. Vitamin D deficiency can be predicted by patient questionnaire. It very rarely leads to secondary hyperparathyroidism. Copyright © 2015. Published by Elsevier Masson SAS.

  15. R2R - software to speed the depiction of aesthetic consensus RNA secondary structures

    Science.gov (United States)

    2011-01-01

    Background With continuing identification of novel structured noncoding RNAs, there is an increasing need to create schematic diagrams showing the consensus features of these molecules. RNA structural diagrams are typically made either with general-purpose drawing programs like Adobe Illustrator, or with automated or interactive programs specific to RNA. Unfortunately, the use of applications like Illustrator is extremely time consuming, while existing RNA-specific programs produce figures that are useful, but usually not of the same aesthetic quality as those produced at great cost in Illustrator. Additionally, most existing RNA-specific applications are designed for drawing single RNA molecules, not consensus diagrams. Results We created R2R, a computer program that facilitates the generation of aesthetic and readable drawings of RNA consensus diagrams in a fraction of the time required with general-purpose drawing programs. Since the inference of a consensus RNA structure typically requires a multiple-sequence alignment, the R2R user annotates the alignment with commands directing the layout and annotation of the RNA. R2R creates SVG or PDF output that can be imported into Adobe Illustrator, Inkscape or CorelDRAW. R2R can be used to create consensus sequence and secondary structure models for novel RNA structures or to revise models when new representatives for known RNA classes become available. Although R2R does not currently have a graphical user interface, it has proven useful in our efforts to create 100 schematic models of distinct noncoding RNA classes. Conclusions R2R makes it possible to obtain high-quality drawings of the consensus sequence and structural models of many diverse RNA structures with a more practical amount of effort. R2R software is available at http://breaker.research.yale.edu/R2R and as an Additional file. PMID:21205310

  16. R2R--software to speed the depiction of aesthetic consensus RNA secondary structures.

    Science.gov (United States)

    Weinberg, Zasha; Breaker, Ronald R

    2011-01-04

    With continuing identification of novel structured noncoding RNAs, there is an increasing need to create schematic diagrams showing the consensus features of these molecules. RNA structural diagrams are typically made either with general-purpose drawing programs like Adobe Illustrator, or with automated or interactive programs specific to RNA. Unfortunately, the use of applications like Illustrator is extremely time consuming, while existing RNA-specific programs produce figures that are useful, but usually not of the same aesthetic quality as those produced at great cost in Illustrator. Additionally, most existing RNA-specific applications are designed for drawing single RNA molecules, not consensus diagrams. We created R2R, a computer program that facilitates the generation of aesthetic and readable drawings of RNA consensus diagrams in a fraction of the time required with general-purpose drawing programs. Since the inference of a consensus RNA structure typically requires a multiple-sequence alignment, the R2R user annotates the alignment with commands directing the layout and annotation of the RNA. R2R creates SVG or PDF output that can be imported into Adobe Illustrator, Inkscape or CorelDRAW. R2R can be used to create consensus sequence and secondary structure models for novel RNA structures or to revise models when new representatives for known RNA classes become available. Although R2R does not currently have a graphical user interface, it has proven useful in our efforts to create 100 schematic models of distinct noncoding RNA classes. R2R makes it possible to obtain high-quality drawings of the consensus sequence and structural models of many diverse RNA structures with a more practical amount of effort. R2R software is available at http://breaker.research.yale.edu/R2R and as an Additional file.

  17. R2R - software to speed the depiction of aesthetic consensus RNA secondary structures

    Directory of Open Access Journals (Sweden)

    Weinberg Zasha

    2011-01-01

    Full Text Available Abstract Background With continuing identification of novel structured noncoding RNAs, there is an increasing need to create schematic diagrams showing the consensus features of these molecules. RNA structural diagrams are typically made either with general-purpose drawing programs like Adobe Illustrator, or with automated or interactive programs specific to RNA. Unfortunately, the use of applications like Illustrator is extremely time consuming, while existing RNA-specific programs produce figures that are useful, but usually not of the same aesthetic quality as those produced at great cost in Illustrator. Additionally, most existing RNA-specific applications are designed for drawing single RNA molecules, not consensus diagrams. Results We created R2R, a computer program that facilitates the generation of aesthetic and readable drawings of RNA consensus diagrams in a fraction of the time required with general-purpose drawing programs. Since the inference of a consensus RNA structure typically requires a multiple-sequence alignment, the R2R user annotates the alignment with commands directing the layout and annotation of the RNA. R2R creates SVG or PDF output that can be imported into Adobe Illustrator, Inkscape or CorelDRAW. R2R can be used to create consensus sequence and secondary structure models for novel RNA structures or to revise models when new representatives for known RNA classes become available. Although R2R does not currently have a graphical user interface, it has proven useful in our efforts to create 100 schematic models of distinct noncoding RNA classes. Conclusions R2R makes it possible to obtain high-quality drawings of the consensus sequence and structural models of many diverse RNA structures with a more practical amount of effort. R2R software is available at http://breaker.research.yale.edu/R2R and as an Additional file.

  18. Effects of truncation of the peptide chain on the secondary structure and bioactivities of palmitoylated anoplin.

    Science.gov (United States)

    Salas, Remmer L; Garcia, Jan Kathryne D L; Miranda, Ana Carmela R; Rivera, Windell L; Nellas, Ricky B; Sabido, Portia Mahal G

    2018-06-01

    Anoplin (GLLKRIKTLL-NH 2 ) is of current interest due to its short sequence and specificity towards bacteria. Recent studies on anoplin have shown that truncation and acylation compromises its antimicrobial activity and specificity, respectively. In this study, truncated analogues (pal-ano-9 to pal-ano-5) of palmitoylated anoplin (pal-anoplin) were synthesized to determine the effects of C-truncation on its bioactivities. Moreover, secondary structure of each analogue using circular dichroism (CD) spectroscopy was determined to correlate with bioactivities. Interestingly, pal-anoplin, pal-ano-9 and pal-ano-6 were helical in water, unlike anoplin. In contrast, pal-ano-8, pal-ano-7 and pal-ano-5, with polar amino acid residues at the C-terminus, were random coil in water. Nevertheless, all the peptides folded into helical structures in 30% trifluoroethanol/water (TFE/H 2 O) except for the shortest analogue pal-ano-5. Hydrophobicity played a significant role in the enhancement of activity against bacteria E. coli and S. aureus as all lipopeptides including the random coil pal-ano-5 were more active than the parent anoplin. Meanwhile, the greatest improvement in activity against the fungus C. albicans was observed for pal-anoplin analogues (pal-ano-9 and pal-ano-6) that were helical in water. Although, hydrophobicity is a major factor in the secondary structure and antimicrobial activity, it appears that the nature of amino acids at the C-terminus also influence folding of lipopeptides in water and its antifungal activity. Moreover, the hemolytic activity of the analogues was found to correlate with hydrophobicity, except for the least hemolytic, pal-ano-5. Since most of the analogues are more potent and shorter than anoplin, they are promising drug candidates for further development. Copyright © 2018. Published by Elsevier Inc.

  19. Alt a 1 allergen homologs from Alternaria and related taxa: analysis of phylogenetic content and secondary structure.

    Science.gov (United States)

    Hong, Soon Gyu; Cramer, Robert A; Lawrence, Christopher B; Pryor, Barry M

    2005-02-01

    A gene for the Alternaria major allergen, Alt a 1, was amplified from 52 species of Alternaria and related genera, and sequence information was used for phylogenetic study. Alt a 1 gene sequences evolved 3.8 times faster and contained 3.5 times more parsimony-informative sites than glyceraldehyde-3-phosphate dehydrogenase (gpd) sequences. Analyses of Alt a 1 gene and gpd exon sequences strongly supported grouping of Alternaria spp. and related taxa into several species-groups described in previous studies, especially the infectoria, alternata, porri, brassicicola, and radicina species-groups and the Embellisia group. The sonchi species-group was newly suggested in this study. Monophyly of the Nimbya group was moderately supported, and monophyly of the Ulocladium group was weakly supported. Relationships among species-groups and among closely related species of the same species-group were not fully resolved. However, higher resolution could be obtained using Alt a 1 sequences or a combined dataset than using gpd sequences alone. Despite high levels of variation in amino acid sequences, results of in silico prediction of protein secondary structure for Alt a 1 demonstrated a high degree of structural similarity for most of the species suggesting a conservation of function.

  20. The sequential structure of brain activation predicts skill.

    Science.gov (United States)

    Anderson, John R; Bothell, Daniel; Fincham, Jon M; Moon, Jungaa

    2016-01-29

    In an fMRI study, participants were trained to play a complex video game. They were scanned early and then again after substantial practice. While better players showed greater activation in one region (right dorsal striatum) their relative skill was better diagnosed by considering the sequential structure of whole brain activation. Using a cognitive model that played this game, we extracted a characterization of the mental states that are involved in playing a game and the statistical structure of the transitions among these states. There was a strong correspondence between this measure of sequential structure and the skill of different players. Using multi-voxel pattern analysis, it was possible to recognize, with relatively high accuracy, the cognitive states participants were in during particular scans. We used the sequential structure of these activation-recognized states to predict the skill of individual players. These findings indicate that important features about information-processing strategies can be identified from a model-based analysis of the sequential structure of brain activation. Copyright © 2015 Elsevier Ltd. All rights reserved.

  1. Protein Loop Structure Prediction Using Conformational Space Annealing.

    Science.gov (United States)

    Heo, Seungryong; Lee, Juyong; Joo, Keehyoung; Shin, Hang-Cheol; Lee, Jooyoung

    2017-05-22

    We have developed a protein loop structure prediction method by combining a new energy function, which we call E PLM (energy for protein loop modeling), with the conformational space annealing (CSA) global optimization algorithm. The energy function includes stereochemistry, dynamic fragment assembly, distance-scaled finite ideal gas reference (DFIRE), and generalized orientation- and distance-dependent terms. For the conformational search of loop structures, we used the CSA algorithm, which has been quite successful in dealing with various hard global optimization problems. We assessed the performance of E PLM with two widely used loop-decoy sets, Jacobson and RAPPER, and compared the results against the DFIRE potential. The accuracy of model selection from a pool of loop decoys as well as de novo loop modeling starting from randomly generated structures was examined separately. For the selection of a nativelike structure from a decoy set, E PLM was more accurate than DFIRE in the case of the Jacobson set and had similar accuracy in the case of the RAPPER set. In terms of sampling more nativelike loop structures, E PLM outperformed E DFIRE for both decoy sets. This new approach equipped with E PLM and CSA can serve as the state-of-the-art de novo loop modeling method.

  2. Offspring social network structure predicts fitness in families.

    Science.gov (United States)

    Royle, Nick J; Pike, Thomas W; Heeb, Philipp; Richner, Heinz; Kölliker, Mathias

    2012-12-22

    Social structures such as families emerge as outcomes of behavioural interactions among individuals, and can evolve over time if families with particular types of social structures tend to leave more individuals in subsequent generations. The social behaviour of interacting individuals is typically analysed as a series of multiple dyadic (pair-wise) interactions, rather than a network of interactions among multiple individuals. However, in species where parents feed dependant young, interactions within families nearly always involve more than two individuals simultaneously. Such social networks of interactions at least partly reflect conflicts of interest over the provision of costly parental investment. Consequently, variation in family network structure reflects variation in how conflicts of interest are resolved among family members. Despite its importance in understanding the evolution of emergent properties of social organization such as family life and cooperation, nothing is currently known about how selection acts on the structure of social networks. Here, we show that the social network structure of broods of begging nestling great tits Parus major predicts fitness in families. Although selection at the level of the individual favours large nestlings, selection at the level of the kin-group primarily favours families that resolve conflicts most effectively.

  3. Optimal neural networks for protein-structure prediction

    International Nuclear Information System (INIS)

    Head-Gordon, T.; Stillinger, F.H.

    1993-01-01

    The successful application of neural-network algorithms for prediction of protein structure is stymied by three problem areas: the sparsity of the database of known protein structures, poorly devised network architectures which make the input-output mapping opaque, and a global optimization problem in the multiple-minima space of the network variables. We present a simplified polypeptide model residing in two dimensions with only two amino-acid types, A and B, which allows the determination of the global energy structure for all possible sequences of pentamer, hexamer, and heptamer lengths. This model simplicity allows us to compile a complete structural database and to devise neural networks that reproduce the tertiary structure of all sequences with absolute accuracy and with the smallest number of network variables. These optimal networks reveal that the three problem areas are convoluted, but that thoughtful network designs can actually deconvolute these detrimental traits to provide network algorithms that genuinely impact on the ability of the network to generalize or learn the desired mappings. Furthermore, the two-dimensional polypeptide model shows sufficient chemical complexity so that transfer of neural-network technology to more realistic three-dimensional proteins is evident

  4. Mapping monomeric threading to protein-protein structure prediction.

    Science.gov (United States)

    Guerler, Aysam; Govindarajoo, Brandon; Zhang, Yang

    2013-03-25

    The key step of template-based protein-protein structure prediction is the recognition of complexes from experimental structure libraries that have similar quaternary fold. Maintaining two monomer and dimer structure libraries is however laborious, and inappropriate library construction can degrade template recognition coverage. We propose a novel strategy SPRING to identify complexes by mapping monomeric threading alignments to protein-protein interactions based on the original oligomer entries in the PDB, which does not rely on library construction and increases the efficiency and quality of complex template recognitions. SPRING is tested on 1838 nonhomologous protein complexes which can recognize correct quaternary template structures with a TM score >0.5 in 1115 cases after excluding homologous proteins. The average TM score of the first model is 60% and 17% higher than that by HHsearch and COTH, respectively, while the number of targets with an interface RMSD benchmark proteins. Although the relative performance of SPRING and ZDOCK depends on the level of homology filters, a combination of the two methods can result in a significantly higher model quality than ZDOCK at all homology thresholds. These data demonstrate a new efficient approach to quaternary structure recognition that is ready to use for genome-scale modeling of protein-protein interactions due to the high speed and accuracy.

  5. Translation of the flavivirus kunjin NS3 gene in cis but not its RNA sequence or secondary structure is essential for efficient RNA packaging.

    Science.gov (United States)

    Pijlman, Gorben P; Kondratieva, Natasha; Khromykh, Alexander A

    2006-11-01

    Our previous studies using trans-complementation analysis of Kunjin virus (KUN) full-length cDNA clones harboring in-frame deletions in the NS3 gene demonstrated the inability of these defective complemented RNAs to be packaged into virus particles (W. J. Liu, P. L. Sedlak, N. Kondratieva, and A. A. Khromykh, J. Virol. 76:10766-10775). In this study we aimed to establish whether this requirement for NS3 in RNA packaging is determined by the secondary RNA structure of the NS3 gene or by the essential role of the translated NS3 gene product. Multiple silent mutations of three computer-predicted stable RNA structures in the NS3 coding region of KUN replicon RNA aimed at disrupting RNA secondary structure without affecting amino acid sequence did not affect RNA replication and packaging into virus-like particles in the packaging cell line, thus demonstrating that the predicted conserved RNA structures in the NS3 gene do not play a role in RNA replication and/or packaging. In contrast, double frameshift mutations in the NS3 coding region of full-length KUN RNA, producing scrambled NS3 protein but retaining secondary RNA structure, resulted in the loss of ability of these defective RNAs to be packaged into virus particles in complementation experiments in KUN replicon-expressing cells. Furthermore, the more robust complementation-packaging system based on established stable cell lines producing large amounts of complemented replicating NS3-deficient replicon RNAs and infection with KUN virus to provide structural proteins also failed to detect any secreted virus-like particles containing packaged NS3-deficient replicon RNAs. These results have now firmly established the requirement of KUN NS3 protein translated in cis for genome packaging into virus particles.

  6. Structural and Function Prediction of Musa acuminata subsp. Malaccensis Protein

    Directory of Open Access Journals (Sweden)

    Anum Munir

    2016-03-01

    Full Text Available Hypothetical proteins (HPs are the proteins whose presence has been anticipated, yet in vivo function has not been built up. Illustrating the structural and functional privileged insights of these HPs might likewise prompt a superior comprehension of the protein-protein associations or networks in diverse types of life. Bananas (Musa acuminata spp., including sweet and cooking types, are giant perennial monocotyledonous herbs of the order Zingiberales, a sister grouped to the all-around considered Poales, which incorporate oats. Bananas are crucial for nourishment security in numerous tropical and subtropical nations and the most prominent organic product in industrialized nations. In the present study, the hypothetical protein of M. acuminata (Banana was chosen for analysis and modeling by distinctive bioinformatics apparatuses and databases. As indicated by primary and secondary structure analysis, XP_009393594.1 is a stable hydrophobic protein containing a noteworthy extent of α-helices; Homology modeling was done utilizing SWISS-MODEL server where the templates identity with XP_009393594.1 protein was less which demonstrated novelty of our protein. Ab initio strategy was conducted to produce its 3D structure. A few evaluations of quality assessment and validation parameters determined the generated protein model as stable with genuinely great quality. Functional analysis was completed by ProtFun 2.2, and KEGG (KAAS, recommended that the hypothetical protein is a transcription factor with cytoplasmic domain as zinc finger. The protein was observed to be vital for translation process, involved in metabolism, signaling and cellular processes, genetic information processing and Zinc ion binding. It is suggested that further test approval would help to anticipate the structures and functions of other uncharacterized proteins of different plants and living being.

  7. Secondary α-deuterium isotope effects as a probe to the relationship between structure and mechanism of pyrolysis of secondary azoalkanes

    International Nuclear Information System (INIS)

    Grizzle, P.L.

    1975-01-01

    This study was carried out to investigate the mechanism of azoalkane thermolysis and the effect of molecular structure on the potential-energy hypersurface for pyrolysis utilizing secondary α-deuterium isotope effects. Since the magnitude of the α-effect for 1,1'-diphenylazoethane is of singular importance in the interpretation of those for related compounds, it has been redetermined. To investigate the effect of molecular structure on the potential-energy hypersurface for thermolysis, α-effects have been determined for 2,2,2',2'-tetramethyl-1,1'-diphenylazoethane and (2,2-dimethyl-1-phenylpropyl)azomethane; the inability to prepare these compounds by conventional methods necessitated the development of a new method for synthesis of secondary azoalkanes. A convenient synthesis of secondary azo compounds is reported. Secondary α-deuterium isotope effects were obtained for the thermal decomposition of 1,1'-diphenylazoethane (III) and 1,1'-diphenylazoethane-1,1'-d 2 (III-d 2 ). The isotope effect is entirely consistent with a simultaneous one-step thermolysis mechanism. Secondary α-deuterium isotope effects and activation parameters were obtained in the thermolysis of 2,2,2',2'-tetramethyl-1,1'-diphenylazopropane (VIII) and (2,2-dimethyl-1-phenylpropyl)azomethane (IX). The data for VIII is considered in terms of both a one- and two-step thermolysis mechanism. The α-effect and activation energy for VIII are not obviously reconcilable with a one-step mechanism. The α-effects, activation energies, and rates of thermolysis for VIII, IX, and (1-phenylethyl)azomethane are most easily rationalized by a two-step mechanism

  8. A probabilistic fragment-based protein structure prediction algorithm.

    Directory of Open Access Journals (Sweden)

    David Simoncini

    Full Text Available Conformational sampling is one of the bottlenecks in fragment-based protein structure prediction approaches. They generally start with a coarse-grained optimization where mainchain atoms and centroids of side chains are considered, followed by a fine-grained optimization with an all-atom representation of proteins. It is during this coarse-grained phase that fragment-based methods sample intensely the conformational space. If the native-like region is sampled more, the accuracy of the final all-atom predictions may be improved accordingly. In this work we present EdaFold, a new method for fragment-based protein structure prediction based on an Estimation of Distribution Algorithm. Fragment-based approaches build protein models by assembling short fragments from known protein structures. Whereas the probability mass functions over the fragment libraries are uniform in the usual case, we propose an algorithm that learns from previously generated decoys and steers the search toward native-like regions. A comparison with Rosetta AbInitio protocol shows that EdaFold is able to generate models with lower energies and to enhance the percentage of near-native coarse-grained decoys on a benchmark of [Formula: see text] proteins. The best coarse-grained models produced by both methods were refined into all-atom models and used in molecular replacement. All atom decoys produced out of EdaFold's decoy set reach high enough accuracy to solve the crystallographic phase problem by molecular replacement for some test proteins. EdaFold showed a higher success rate in molecular replacement when compared to Rosetta. Our study suggests that improving low resolution coarse-grained decoys allows computational methods to avoid subsequent sampling issues during all-atom refinement and to produce better all-atom models. EdaFold can be downloaded from http://www.riken.jp/zhangiru/software.html [corrected].

  9. Salient design features of secondary containment structure of Narora Atomic Power Project

    International Nuclear Information System (INIS)

    Rahalkar, B.D.

    1975-01-01

    Design of the secondary containment structure for Narora Atomic Power Project is an improvement over the two earlier structures at of Rajasthan and Kalpakkam wherein Candu-type of reactors are involved. The major improvements envisaged are : to limit the leakage through the double containment envelope to 0.1% of volume of the building per day as against 0.1% per hour achieved for earlier stations; to separate heavy water atmosphere from that of light water for effective heavy water recovery; and better man-rem budgetting by limiting inner containment structure upto boiler room floor level and making boiler room area accessible during normal operation for servicing of light water system equipment. Narora Atomic Power Station is located in the Indo-Gangetic alluvial plains in seismically active zone IV. Comprehensive soil investigation, including dynamic properties of soil is required to be undertaken as the foundation level of the containment structure is 17 M below the ground level. The salient results of this investigation relevant to the foundations as well as type of foundation proposed are presented in brief. Double containment concept similar to that adopted for Kalpakkam station is provided for this station also. However, necessary changes in design to withstand large earthquake forces are required to be made. These design problems are discussed in brief. (author)

  10. De novo prediction of structured RNAs from genomic sequences

    DEFF Research Database (Denmark)

    Gorodkin, Jan; Hofacker, Ivo L.; Þórarinsson, Elfar

    2010-01-01

    currently available, because evolutionary conservation highlights functionally important regions. Conserved secondary structure, rather than primary sequence, is the hallmark of many functionally important RNAs, because compensatory substitutions in base-paired regions preserve structure. Unfortunately...

  11. SU-E-T-479: Development and Validation of Analytical Models Predicting Secondary Neutron Radiation in Proton Therapy Applications

    International Nuclear Information System (INIS)

    Farah, J; Bonfrate, A; Donadille, L; Martinetti, F; Trompier, F; Clairand, I; De Olivera, A; Delacroix, S; Herault, J; Piau, S; Vabre, I

    2014-01-01

    : Analytical models predicting secondary neutrons in proton therapy represent a promising solution that substitute for time-consuming MC calculations

  12. [Establishment of prescription research technology system in Chinese medicine secondary exploitation based on "component structure" theory].

    Science.gov (United States)

    Cheng, Xu-Dong; Feng, Liang; Gu, Jun-Fei; Zhang, Ming-Hua; Jia, Xiao-Bin

    2014-11-01

    Chinese medicine prescriptions are the wisdom outcomes of traditional Chinese medicine (TCM) clinical treatment determinations which based on differentiation of symptoms and signs. Chinese medicine prescriptions are also the basis of secondary exploitation of TCM. The study on prescription helps to understand the material basis of its efficacy, pharmacological mechanism, which is an important guarantee for the modernization of traditional Chinese medicine. Currently, there is not yet dissertation n the method and technology system of basic research on the prescription of Chinese medicine. This paper focuses on how to build an effective system of prescription research technology. Based on "component structure" theory, a technology system contained four-step method that "prescription analysis, the material basis screening, the material basis of analysis and optimization and verify" was proposed. The technology system analyzes the material basis of the three levels such as Chinese medicine pieces, constituents and the compounds which could respect the overall efficacy of Chinese medicine. Ideas of prescription optimization, remodeling are introduced into the system. The technology system is the combination of the existing research and associates with new techniques and methods, which used for explore the research thought suitable for material basis research and prescription remodeling. The system provides a reference for the secondary development of traditional Chinese medicine, and industrial upgrading.

  13. Secondary flow structures in a 180∘ elastic curved vessel with torsion under steady and pulsatile inflow conditions

    Science.gov (United States)

    Najjari, Mohammad Reza; Plesniak, Michael W.

    2017-11-01

    Secondary flow vortical structures were investigated in an elastic 180° curved pipe with and without torsion under steady and pulsatile flow using particle image velocimetry (PIV). The elastic thin-walled curved pipes were constructed using Sylgard 184, and inserted into a bath of refractive index matched fluid to perform PIV. A vortex identification method was employed to identify various vortical structures in the flow. The secondary flow structures in the planar compliant model with dilatation of 0.61%-3.23% under pulsatile flow rate were compared with the rigid vessel model results, and it was found that local vessel compliance has a negligible effect on secondary flow morphology. The secondary flow structures were found to be more sensitive to out of plane curvature (torsion) than to vessel compliance. Torsion distorts the symmetry of secondary flow and results in more complex vortical structures in both steady and pulsatile flows. In high Re number steady flow with torsion, a single dominant vortical structure can be detected at the middle of the 90° cross section. In pulsatile flow with torsion, the split-Dean and Lyne-type vortices with same rotation direction originating from opposite sides of the cross section tend to merge together. supported by GW Center for Biomimetics and Bioinspired Engineering.

  14. Predicting binding within disordered protein regions to structurally characterised peptide-binding domains.

    Directory of Open Access Journals (Sweden)

    Waqasuddin Khan

    Full Text Available Disordered regions of proteins often bind to structured domains, mediating interactions within and between proteins. However, it is difficult to identify a priori the short disordered regions involved in binding. We set out to determine if docking such peptide regions to peptide binding domains would assist in these predictions.We assembled a redundancy reduced dataset of SLiM (Short Linear Motif containing proteins from the ELM database. We selected 84 sequences which had an associated PDB structures showing the SLiM bound to a protein receptor, where the SLiM was found within a 50 residue region of the protein sequence which was predicted to be disordered. First, we investigated the Vina docking scores of overlapping tripeptides from the 50 residue SLiM containing disordered regions of the protein sequence to the corresponding PDB domain. We found only weak discrimination of docking scores between peptides involved in binding and adjacent non-binding peptides in this context (AUC 0.58.Next, we trained a bidirectional recurrent neural network (BRNN using as input the protein sequence, predicted secondary structure, Vina docking score and predicted disorder score. The results were very promising (AUC 0.72 showing that multiple sources of information can be combined to produce results which are clearly superior to any single source.We conclude that the Vina docking score alone has only modest power to define the location of a peptide within a larger protein region known to contain it. However, combining this information with other knowledge (using machine learning methods clearly improves the identification of peptide binding regions within a protein sequence. This approach combining docking with machine learning is primarily a predictor of binding to peptide-binding sites, and is not intended as a predictor of specificity of binding to particular receptors.

  15. [Partially unfolded state of lysozyme with a developed secondary structure in dimethylsulfoxide].

    Science.gov (United States)

    Timchenko, A A; Kirkitadze, M D; Prokhorov, D A; Potekhin, S A; Serdiuk, I N

    1996-06-01

    The conformation of a chicken egg lysozyme molecule (dimensions, stoichiometry of its associates, and the degree of helicity) in DMSO was studied by small-angle neutron scattering, dynamic light scattering, and optical rotatory dispersion in the visible region of the spectrum. At high DMSO concentrations (70%), the protein was shown to exist as a dimer. The monomer molecules in the dimer adopt a partially unfolded conformation, with dimensions substantially greater than those in the native state and a high content of secondary structure (the degree of helicity is close to that of native lysozyme). This approach provides a unique possibility to assess the compactness of molecules in associates, which may be very useful in studying protein self-organization.

  16. Molecular and crystal structure of the antibiotic enniatin B, a secondary microbial metabolite

    International Nuclear Information System (INIS)

    Zhukhlistova, N.E.; Tishchenko, G.N.; Tolstykh, I.V.; Zenkova, V.A.

    1999-01-01

    Single crystals of the secondary microbial metabolite C 33 H 57 N 3 O 9 ·1(2/3)H 2 O with the known molecular weight were studied by the method of X-ray diffraction analysis, where a=b=15.102(3) A, c=14.548(3) A, sp. gr.R3, R=0.057. In the course of the structure determination, it was established that the substance is a natural antibiotic, namely, enniatin B. The conformation of its molecule is similar to that of the known synthetic antibiotic. The main difference between the natural and synthesized forms reduces to the different numbers of water molecules and their arrangement in the cavity of the antibiotic molecule

  17. Modeling of a New Structure of Precision Air Conditioning System Using Secondary Condenser for Rh Regulation

    Directory of Open Access Journals (Sweden)

    Aries Subiantoro

    2012-05-01

    Full Text Available A dynamic mathematical model for a new structure of precision air conditioning (PAC has been developed. The proposed PAC uses an additional secondary condenser for relative humidity regulation compared to a basic refrigeration system. The work mechanism for this system and a vapour-compression cycle process of the system are illustrated using psychrometric chart and pressure-enthalpy diagram. A non-linear system model is derived based on the conservation of mass and energy balance principles and then linearized at steady state operating point for developing a 8th-order state space model suited for multivariable controller design. The quality of linearized model is analyzed in terms of transient response, controllability, observability, and interaction between input-output variables. The developed model is verified through simulation showing its ability for imitating the nonlinear behavior and the interaction of input-output variables.

  18. Facial Structure Predicts Sexual Orientation in Both Men and Women.

    Science.gov (United States)

    Skorska, Malvina N; Geniole, Shawn N; Vrysen, Brandon M; McCormick, Cheryl M; Bogaert, Anthony F

    2015-07-01

    Biological models have typically framed sexual orientation in terms of effects of variation in fetal androgen signaling on sexual differentiation, although other biological models exist. Despite marked sex differences in facial structure, the relationship between sexual orientation and facial structure is understudied. A total of 52 lesbian women, 134 heterosexual women, 77 gay men, and 127 heterosexual men were recruited at a Canadian campus and various Canadian Pride and sexuality events. We found that facial structure differed depending on sexual orientation; substantial variation in sexual orientation was predicted using facial metrics computed by a facial modelling program from photographs of White faces. At the univariate level, lesbian and heterosexual women differed in 17 facial features (out of 63) and four were unique multivariate predictors in logistic regression. Gay and heterosexual men differed in 11 facial features at the univariate level, of which three were unique multivariate predictors. Some, but not all, of the facial metrics differed between the sexes. Lesbian women had noses that were more turned up (also more turned up in heterosexual men), mouths that were more puckered, smaller foreheads, and marginally more masculine face shapes (also in heterosexual men) than heterosexual women. Gay men had more convex cheeks, shorter noses (also in heterosexual women), and foreheads that were more tilted back relative to heterosexual men. Principal components analysis and discriminant functions analysis generally corroborated these results. The mechanisms underlying variation in craniofacial structure--both related and unrelated to sexual differentiation--may thus be important in understanding the development of sexual orientation.

  19. PROCARB: A Database of Known and Modelled Carbohydrate-Binding Protein Structures with Sequence-Based Prediction Tools

    Directory of Open Access Journals (Sweden)

    Adeel Malik

    2010-01-01

    Full Text Available Understanding of the three-dimensional structures of proteins that interact with carbohydrates covalently (glycoproteins as well as noncovalently (protein-carbohydrate complexes is essential to many biological processes and plays a significant role in normal and disease-associated functions. It is important to have a central repository of knowledge available about these protein-carbohydrate complexes as well as preprocessed data of predicted structures. This can be significantly enhanced by tools de novo which can predict carbohydrate-binding sites for proteins in the absence of structure of experimentally known binding site. PROCARB is an open-access database comprising three independently working components, namely, (i Core PROCARB module, consisting of three-dimensional structures of protein-carbohydrate complexes taken from Protein Data Bank (PDB, (ii Homology Models module, consisting of manually developed three-dimensional models of N-linked and O-linked glycoproteins of unknown three-dimensional structure, and (iii CBS-Pred prediction module, consisting of web servers to predict carbohydrate-binding sites using single sequence or server-generated PSSM. Several precomputed structural and functional properties of complexes are also included in the database for quick analysis. In particular, information about function, secondary structure, solvent accessibility, hydrogen bonds and literature reference, and so forth, is included. In addition, each protein in the database is mapped to Uniprot, Pfam, PDB, and so forth.

  20. Protein Function Prediction Based on Sequence and Structure Information

    KAUST Repository

    Smaili, Fatima Z.

    2016-05-25

    The number of available protein sequences in public databases is increasing exponentially. However, a significant fraction of these sequences lack functional annotation which is essential to our understanding of how biological systems and processes operate. In this master thesis project, we worked on inferring protein functions based on the primary protein sequence. In the approach we follow, 3D models are first constructed using I-TASSER. Functions are then deduced by structurally matching these predicted models, using global and local similarities, through three independent enzyme commission (EC) and gene ontology (GO) function libraries. The method was tested on 250 “hard” proteins, which lack homologous templates in both structure and function libraries. The results show that this method outperforms the conventional prediction methods based on sequence similarity or threading. Additionally, our method could be improved even further by incorporating protein-protein interaction information. Overall, the method we use provides an efficient approach for automated functional annotation of non-homologous proteins, starting from their sequence.

  1. Engineered, highly reactive substrates of microbial transglutaminase enable protein labeling within various secondary structure elements.

    Science.gov (United States)

    Rachel, Natalie M; Quaglia, Daniela; Lévesque, Éric; Charette, André B; Pelletier, Joelle N

    2017-11-01

    Microbial transglutaminase (MTG) is a practical tool to enzymatically form isopeptide bonds between peptide or protein substrates. This natural approach to crosslinking the side-chains of reactive glutamine and lysine residues is solidly rooted in food and textile processing. More recently, MTG's tolerance for various primary amines in lieu of lysine have revealed its potential for site-specific protein labeling with aminated compounds, including fluorophores. Importantly, MTG can label glutamines at accessible positions in the body of a target protein, setting it apart from most labeling enzymes that react exclusively at protein termini. To expand its applicability as a labeling tool, we engineered the B1 domain of Protein G (GB1) to probe the selectivity and enhance the reactivity of MTG toward its glutamine substrate. We built a GB1 library where each variant contained a single glutamine at positions covering all secondary structure elements. The most reactive and selective variants displayed a >100-fold increase in incorporation of a recently developed aminated benzo[a]imidazo[2,1,5-cd]indolizine-type fluorophore, relative to native GB1. None of the variants were destabilized. Our results demonstrate that MTG can react readily with glutamines in α-helical, β-sheet, and unstructured loop elements and does not favor one type of secondary structure. Introducing point mutations within MTG's active site further increased reactivity toward the most reactive substrate variant, I6Q-GB1, enhancing MTG's capacity to fluorescently label an engineered, highly reactive glutamine substrate. This work demonstrates that MTG-reactive glutamines can be readily introduced into a protein domain for fluorescent labeling. © 2017 The Protein Society.

  2. Examining the dimensional structure models of secondary traumatic stress based on DSM-5 symptoms.

    Science.gov (United States)

    Mordeno, Imelu G; Go, Geraldine P; Yangson-Serondo, April

    2017-02-01

    Latent factor structure of Secondary Traumatic Stress (STS) has been examined using Diagnostic Statistic Manual-IV (DSM-IV)'s Posttraumatic Stress Disorder (PTSD) nomenclature. With the advent of Diagnostic Statistic Manual-5 (DSM-5), there is an impending need to reexamine STS using DSM-5 symptoms in light of the most updated PTSD models in the literature. The study investigated and determined the best fitted PTSD models using DSM-5 PTSD criteria symptoms. Confirmatory factor analysis (CFA) was conducted to examine model fit using the Secondary Traumatic Stress Scale in 241 registered and practicing Filipino nurses (166 females and 75 males) who worked in the Philippines and gave direct nursing services to patients. Based on multiple fit indices, the results showed the 7-factor hybrid model, comprising of intrusion, avoidance, negative affect, anhedonia, externalizing behavior, anxious arousal, and dysphoric arousal factors has excellent fit to STS. This model asserts that: (1) hyperarousal criterion needs to be divided into anxious and dysphoric arousal factors; (2) symptoms characterizing negative and positive affect need to be separated to two separate factors, and; (3) a new factor would categorize externalized, self-initiated impulse and control-deficit behaviors. Comparison of nested and non-nested models showed Hybrid model to have superior fit over other models. The specificity of the symptom structure of STS based on DSM-5 PTSD criteria suggests having more specific interventions addressing the more elaborate symptom-groupings that would alleviate the condition of nurses exposed to STS on a daily basis. Copyright © 2016 Elsevier B.V. All rights reserved.

  3. Interaction Of Calcium Phosphate Nanoparticles With Human Chorionic Gonadotropin Modifies Secondary And Tertiary Protein Structure

    Directory of Open Access Journals (Sweden)

    Al-Hakeim Hussein K

    2015-12-01

    Full Text Available Calcium phosphate nanoparticles (CaPNP have good biocompatibility and bioactivity inside human body. In this study, the interaction between CaPNP and human chorionic gonadotropin (hCG was analyzed to determine the changes in the protein structure in the presence of CaPNP and the quantity of protein adsorbed on the CaPNP surface. The results showed a significant adsorption of hCG on the CaPNP nanoparticle surface. The optimal fit was achieved using the Sips isotherm equation with a maximum adsorption capacity of 68.23 µg/mg. The thermodynamic parameters, including ∆H° and ∆G°, of the adsorption process are positive, whereas ∆S° is negative. The circular dichroism results of the adsorption of hCG on CaPNP showed the changes in its secondary structure; such changes include the decomposition of α-helix strand and the increase in β-pleated sheet and random coil percentages. Fluorescence study indicated minimal changes in the tertiary structure near the microenvironment of the aromatic amino acids such as tyrosine and phenyl alanine caused by the interaction forces between the CaPNP and hCG protein. The desorption process showed that the quantity of the hCG desorbed significantly increases as temperature increases, which indicates the weak forces between hCG and the surface.

  4. Prediction of Protein Structural Classes for Low-Similarity Sequences Based on Consensus Sequence and Segmented PSSM

    Directory of Open Access Journals (Sweden)

    Yunyun Liang

    2015-01-01

    Full Text Available Prediction of protein structural classes for low-similarity sequences is useful for understanding fold patterns, regulation, functions, and interactions of proteins. It is well known that feature extraction is significant to prediction of protein structural class and it mainly uses protein primary sequence, predicted secondary structure sequence, and position-specific scoring matrix (PSSM. Currently, prediction solely based on the PSSM has played a key role in improving the prediction accuracy. In this paper, we propose a novel method called CSP-SegPseP-SegACP by fusing consensus sequence (CS, segmented PsePSSM, and segmented autocovariance transformation (ACT based on PSSM. Three widely used low-similarity datasets (1189, 25PDB, and 640 are adopted in this paper. Then a 700-dimensional (700D feature vector is constructed and the dimension is decreased to 224D by using principal component analysis (PCA. To verify the performance of our method, rigorous jackknife cross-validation tests are performed on 1189, 25PDB, and 640 datasets. Comparison of our results with the existing PSSM-based methods demonstrates that our method achieves the favorable and competitive performance. This will offer an important complementary to other PSSM-based methods for prediction of protein structural classes for low-similarity sequences.

  5. Influence of Secondary Cooling Mode on Solidification Structure and Macro-segregation Behavior for High-carbon Continuous Casting Bloom

    Science.gov (United States)

    Dou, Kun; Yang, Zhenguo; Liu, Qing; Huang, Yunhua; Dong, Hongbiao

    2017-07-01

    A cellular automaton-finite element coupling model for high-carbon continuously cast bloom of GCr15 steel is established to simulate the solidification structure and to investigate the influence of different secondary cooling modes on characteristic parameters such as equiaxed crystal ratio, grain size and secondary dendrite arm spacing, in which the effect of phase transformation and electromagnetic stirring is taken into consideration. On this basis, evolution of carbon macro-segregation for GCr15 steel bloom is researched correspondingly via industrial tests. Based on above analysis, the relationship among secondary cooling modes, characteristic parameters for solidification structure as well as carbon macro-segregation is illustrated to obtain optimum secondary cooling strategy and alleviate carbon macro-segregation degree for GCr15 steel bloom in continuous casting process. The evaluating method for element macro-segregation is applicable in various steel types.

  6. Factors that Affect Mathematics-Science (MS) Scores in the Secondary Education Institutional Exam: An Application of Structural Equation Modeling

    Science.gov (United States)

    Yavuz, Mustafa

    2009-01-01

    Discovering what determines students' success in the Secondary Education Institutional Exam is very important to parents and it is also critical for students, teachers, directors, and researchers. Research was carried out by studying the related literature and structural equation modeling techniques. A structural model was created that consisted…

  7. Structure and properties of silver sulfate complexes derived from dipyridyl methylthio ligands with secondary donor site

    Energy Technology Data Exchange (ETDEWEB)

    Chen, Wen-Hua; Yan, Hao-Jie; Chen, Hui; Liu, Rui-Heng; Li, Ai-Min; Wang, Guo [Beijing Key Laboratory for Optical Materials and Photonic Devices, Department of Chemistry, Capital Normal University, Beijing 100048 (China); Wan, Chong-Qing, E-mail: wancq@cnu.edu.cn [Beijing Key Laboratory for Optical Materials and Photonic Devices, Department of Chemistry, Capital Normal University, Beijing 100048 (China); State Key Laboratory of Structural Chemistry in China, Fujian Institute of Research on the Structure of Matter, Chinese Academy of Sciences, Fuzhou, Fujian 350002 (China)

    2017-06-15

    Dipyridyl sulphide ligands 4-(pyridin-4-ylmethylthio)pyridine (abbreviated as L1) and 3-(pyridin-4-ylmethylthio)pyridine (abbreviated as L2) have been designed and used as μ-{sub N},{sub N}-bridging linkages to construct coordination polymers with free –S–CH{sub 2}– groups as secondary donor sites. By use solvent control method, coordination polymers ([Ag{sub 3}SO{sub 4}(L1){sub 3}](Cl)·4.5H{sub 2}O){sub ∞}(1), ([Ag{sub 2}SO{sub 4}(L1){sub 2}]·6H{sub 2}O·2CH{sub 3}OH){sub ∞}(2), ([Ag{sub 2}SO{sub 4}(L2){sub 2}]·H{sub 2}O){sub ∞}(3) and ([Ag{sub 4}(SO{sub 4}){sub 2}(L2){sub 4}]·5H{sub 2}O){sub ∞}(4) with different architectures were obtained. Complexes 1, 3 and 4 feature 1D channel with different sizes and structures. Complex 1 exhibits guest exchange by THF and 1,4-dioxane, and Hg{sup 2+} sorption ability from solution due to its relative larger channel and available bonding sites of –S– exposed to the channel region. All complexes have been characterized through single-crystal and powder X-ray diffraction (PXRD), FT-IR spectra, X-ray photoelectron spectroscopy (XPS), elemental and thermogravimetric analyses. The guest exchange and Hg{sup 2+} sorption were monitored and identified, and the structure-property relationship of coordination polymers 1–4 are discussed. - Graphical abstract: Coordination polymers of silver(I) sulfate with secondary donor sites are shown guest exchange property and Hg{sup 2+} absorb ability from solution. This work provides a new method to construct functional materials with potential application. - Highlights: • New example of constructing functional coordination polymer with secondary donor methylthio group. • Guest exchange and interesting Hg(II) absorb ability from solution are investigated. • New method to construct functional materials with potential application.

  8. An Extreme-ultraviolet Wave Generating Upward Secondary Waves in a Streamer-like Solar Structure

    Science.gov (United States)

    Zheng, Ruisheng; Chen, Yao; Feng, Shiwei; Wang, Bing; Song, Hongqiang

    2018-05-01

    Extreme-ultraviolet (EUV) waves, spectacular horizontally propagating disturbances in the low solar corona, always trigger horizontal secondary waves (SWs) when they encounter the ambient coronal structure. We present the first example of upward SWs in a streamer-like structure after the passing of an EUV wave. This event occurred on 2017 June 1. The EUV wave happened during a typical solar eruption including a filament eruption, a coronal mass ejection (CME), and a C6.6 flare. The EUV wave was associated with quasi-periodic fast propagating (QFP) wave trains and a type II radio burst that represented the existence of a coronal shock. The EUV wave had a fast initial velocity of ∼1000 km s‑1, comparable to high speeds of the shock and the QFP wave trains. Intriguingly, upward SWs rose slowly (∼80 km s‑1) in the streamer-like structure after the sweeping of the EUV wave. The upward SWs seemed to originate from limb brightenings that were caused by the EUV wave. All of the results show that the EUV wave is a fast-mode magnetohydrodynamic (MHD) shock wave, likely triggered by the flare impulses. We suggest that part of the EUV wave was probably trapped in the closed magnetic fields of the streamer-like structure, and upward SWs possibly resulted from the release of slow-mode trapped waves. It is believed that the interplay of the strong compression of the coronal shock and the configuration of the streamer-like structure is crucial for the formation of upward SWs.

  9. Predictive Factors of Secondary Normocalcemic Hyperparathyroidism after Roux-en-Y Gastric Bypass

    Directory of Open Access Journals (Sweden)

    Claudio Casella

    2018-01-01

    Full Text Available Objective. Aim of this study is to evaluate determinants of secondary normocalcemic hyperparathyroidism (SNHPT persistence in patients who have undergone Roux-en-Y gastric bypass on vertical-banded gastroplasty. Methods. 226 consecutive patients submitted to bariatric surgery were prospectively enrolled and divided in two groups on the basis of preoperative presence of SNHPT. For each patient, we evaluated anthropometric and laboratory parameters. Calcium metabolism (calcemia, PTH, and 25-hydroxy vitamin D serum levels was studied before surgery and at 6-month intervals (6, 12, and 18 months as surgical follow-up. Results. Based on presurgical SNHPT presence or absence, we defined group 1—201 patients and group 2—25 patients, respectively. Among the group 1, 153 (76% recovered from this endocrinopathy within 6 months after surgery (group 3, while the remaining 48 patients (24% had persistent SNHPT (group 4. Comparing the anthropometric and laboratory data of group 3 with group 2, the only statistically significant factor was the elapsed time since a prior effective medically controlled diet that led to a steady and substantial weight loss. We found also a statistically significant difference (p<0.05 between group 3 and group 4 in term of % of weight loss and PTH levels. Conclusions. Patients suitable for bariatric surgery must have history of at least one efficient medically controlled diet, not dating back more than 5 years before surgery. This elapsed time represent the cut-off time within which it is possible to recover from SNHPT in the first semester after Roux-en-Y gastric bypass on vertical-banded gastroplasty. The treatment of vitamin D insufficiency and the evaluation of SNHPT before bariatric surgery should be recommended. The clinical significance of preoperative SNHPT and in particular SNHPT after bariatric surgery remains undefined and further studies are required.

  10. Prediction of Chloride Diffusion in Concrete Structure Using Meshless Methods

    Directory of Open Access Journals (Sweden)

    Ling Yao

    2016-01-01

    Full Text Available Degradation of RC structures due to chloride penetration followed by reinforcement corrosion is a serious problem in civil engineering. The numerical simulation methods at present mainly involve finite element methods (FEM, which are based on mesh generation. In this study, element-free Galerkin (EFG and meshless weighted least squares (MWLS methods are used to solve the problem of simulation of chloride diffusion in concrete. The range of a scaling parameter is presented using numerical examples based on meshless methods. One- and two-dimensional numerical examples validated the effectiveness and accuracy of the two meshless methods by comparing results obtained by MWLS with results computed by EFG and FEM and results calculated by an analytical method. A good agreement is obtained among MWLS and EFG numerical simulations and the experimental data obtained from an existing marine concrete structure. These results indicate that MWLS and EFG are reliable meshless methods that can be used for the prediction of chloride ingress in concrete structures.

  11. The extended evolutionary synthesis: its structure, assumptions and predictions

    Science.gov (United States)

    Laland, Kevin N.; Uller, Tobias; Feldman, Marcus W.; Sterelny, Kim; Müller, Gerd B.; Moczek, Armin; Jablonka, Eva; Odling-Smee, John

    2015-01-01

    Scientific activities take place within the structured sets of ideas and assumptions that define a field and its practices. The conceptual framework of evolutionary biology emerged with the Modern Synthesis in the early twentieth century and has since expanded into a highly successful research program to explore the processes of diversification and adaptation. Nonetheless, the ability of that framework satisfactorily to accommodate the rapid advances in developmental biology, genomics and ecology has been questioned. We review some of these arguments, focusing on literatures (evo-devo, developmental plasticity, inclusive inheritance and niche construction) whose implications for evolution can be interpreted in two ways—one that preserves the internal structure of contemporary evolutionary theory and one that points towards an alternative conceptual framework. The latter, which we label the ‘extended evolutionary synthesis' (EES), retains the fundaments of evolutionary theory, but differs in its emphasis on the role of constructive processes in development and evolution, and reciprocal portrayals of causation. In the EES, developmental processes, operating through developmental bias, inclusive inheritance and niche construction, share responsibility for the direction and rate of evolution, the origin of character variation and organism–environment complementarity. We spell out the structure, core assumptions and novel predictions of the EES, and show how it can be deployed to stimulate and advance research in those fields that study or use evolutionary biology. PMID:26246559

  12. The experimental search for new predicted binary-alloy structures

    Science.gov (United States)

    Erb, K. C.; Richey, Lauren; Lang, Candace; Campbell, Branton; Hart, Gus

    2010-10-01

    Predicting new ordered phases in metallic alloys is a productive line of inquiry because configurational ordering in an alloy can dramatically alter their useful material properties. One is able to infer the existence of an ordered phase in an alloy using first-principles calculated formation enthalpies.ootnotetextG. L. W. Hart, ``Where are Nature's missing structures?,'' Nature Materials 6 941-945 2007 Using this approach, we have been able to identify stable (i.e. lowest energy) orderings in a variety of binary metallic alloys. Many of these phases have been observed experimentally in the past, though others have not. In pursuit of several of the missing structures, we have characterized potential orderings in PtCd, PtPd and PtMo alloys using synchrotron x-ray powder diffraction and symmetry-analysis tools.ootnotetextB. J. Campbell, H. T. Stokes, D. E. Tanner, and D. M. Hatch, ``ISODISPLACE: a web-based tool for exploring structural distortions,'' J. Appl. Cryst. 39, 607-614 (2006)

  13. Secondary School Students' LLL Competencies, and Their Relation with Classroom Structure and Achievement.

    Science.gov (United States)

    Klug, Julia; Lüftenegger, Marko; Bergsmann, Evelyn; Spiel, Christiane; Schober, Barbara

    2016-01-01

    There is a strong urge to foster lifelong learning (LLL) competencies with its key components - motivation and self-regulated learning - from early on in the education system. School in general is presently not considered to be successful in systematically imparting motivation and self-regulated learning strategies. There is strong evidence that decisive motivational determinants decrease the longer students stay in school. At present, the central sources of information about the situation in Austria are international monitoring studies, which only examine selected aspects of specific target groups, and their interpretability concerning mean values is constricted due to cultural differences. Thus, it is important to conduct additional and more differentiated national surveys of the actual state. This is why this study aimed at answering the following questions: (1) how well are Austrian students equipped for the future, in terms of their lifelong learning competencies, (2) can perceived classroom structure predict students' LLL, and (3) is there a correlation of students' LLL with their achievement in the school subjects math and German language. 5366 students (52.1% female) from 36 Austrian schools took part in the online-questionnaire (mean age 15.35 years, SD = 2.45), which measured their perceived LLL competencies in the subjects math and German language, their perceived classroom structure and their achievement. Results showed that the great majority of Austrian students - independent from domain and sex - know and are able to apply cognitive as well as metacognitive learning strategies. With regard to motivation the picture is less satisfactory: whilst students' self-efficacy is not the problem, there is a lack of interest in the school subjects and they often report to follow performance approach goals. Classroom structure positively predicted students' goals, interest, self-efficacy and learning strategies. Self-efficacy, performance approach goals, meta

  14. Secondary school students' LLL competencies, and their relation with classroom structure and achievement

    Directory of Open Access Journals (Sweden)

    Julia eKlug

    2016-05-01

    Full Text Available There is a strong urge to foster lifelong learning (LLL competencies with its key components - motivation and self-regulated learning - from early on in the education system. School in general is presently not considered to be successful in systematically imparting motivation and self-regulated learning strategies. There is strong evidence that decisive motivational determinants decrease the longer students stay in school. At present, the central sources of information about the situation in Austria are international monitoring studies, which only examine selected aspects of specific target groups, and their interpretability concerning mean values is constricted due to cultural differences. Thus, it is important to conduct additional and more differentiated national surveys of the actual state. This is why this study aimed at answering the following questions: (1 how well are Austrian students equipped for the future, in terms of their lifelong learning competencies, (2 can perceived classroom structure predict students’ LLL, and (3 is there a correlation of students’ LLL with their achievement in the school subjects math and German language. 5366 students (52.1% female from Thirty-six Austrian schools took part in the online-questionnaire (mean age 15.35 years, SD=2.45, which measured their perceived LLL competencies in the subjects math and German language, their perceived classroom structure and their achievement. Results showed that the great majority of Austrian students – independent from domain and sex - know and are able to apply cognitive as well as metacognitive learning strategies. With regard to motivation the picture is less satisfactory: whilst students’ self-efficacy is not the problem, there is a lack of interest in the school subjects and they often report to follow performance approach goals. Classroom structure positively predicted students’ goals, interest, self-efficacy and learning strategies. Self

  15. Secondary School Students’ LLL Competencies, and Their Relation with Classroom Structure and Achievement

    Science.gov (United States)

    Klug, Julia; Lüftenegger, Marko; Bergsmann, Evelyn; Spiel, Christiane; Schober, Barbara

    2016-01-01

    There is a strong urge to foster lifelong learning (LLL) competencies with its key components – motivation and self-regulated learning – from early on in the education system. School in general is presently not considered to be successful in systematically imparting motivation and self-regulated learning strategies. There is strong evidence that decisive motivational determinants decrease the longer students stay in school. At present, the central sources of information about the situation in Austria are international monitoring studies, which only examine selected aspects of specific target groups, and their interpretability concerning mean values is constricted due to cultural differences. Thus, it is important to conduct additional and more differentiated national surveys of the actual state. This is why this study aimed at answering the following questions: (1) how well are Austrian students equipped for the future, in terms of their lifelong learning competencies, (2) can perceived classroom structure predict students’ LLL, and (3) is there a correlation of students’ LLL with their achievement in the school subjects math and German language. 5366 students (52.1% female) from 36 Austrian schools took part in the online-questionnaire (mean age 15.35 years, SD = 2.45), which measured their perceived LLL competencies in the subjects math and German language, their perceived classroom structure and their achievement. Results showed that the great majority of Austrian students – independent from domain and sex – know and are able to apply cognitive as well as metacognitive learning strategies. With regard to motivation the picture is less satisfactory: whilst students’ self-efficacy is not the problem, there is a lack of interest in the school subjects and they often report to follow performance approach goals. Classroom structure positively predicted students’ goals, interest, self-efficacy and learning strategies. Self-efficacy, performance

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

    Science.gov (United States)

    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

  17. Enzyme stability, thermodynamics and secondary structures of α-amylase as probed by the CD spectroscopy.

    Science.gov (United States)

    Kikani, B A; Singh, S P

    2015-11-01

    An amylase of a thermophilic bacterium, Bacillus sp. TSSC-3 (GenBank Number, EU710557) isolated from the Tulsi Shyam hot spring reservoir (Gujarat, India) was purified to the homogeneity in a single step on phenyl sepharose 6FF. The molecular weight of the enzyme was 25kD, while the temperature and pH optima for the enzyme catalysis were 80°C and 7, respectively. The purified enzyme was highly thermostable with broad pH stability and displayed remarkable resistance against surfactants, chelators, urea, guanidine HCl and various solvents as well. The stability and changes in the secondary structure of the enzyme under various extreme conditions were determined by the circular dichroism (CD) spectroscopy. The stability trends and the changes in the α-helices and β-sheets were analyzed by Mean Residual Ellipticity (MRE) and K2D3. The CD data confirmed the structural stability of the enzyme under various harsh conditions, yet it indicated reduced α-helix content and increased β-sheets upon denaturation. The thermodynamic parameters; deactivation rate constant, half-life, changes in entropy, enthalpy, activation energy and Gibb's free energy indicated that the enzyme-substrate reactions were highly stable. The overall profile of the enzyme: high thermostability, alkalitolerance, calcium independent nature, dextrose equivalent values and resistance against chemical denaturants, solvents and surfactants suggest its commercial applications. Copyright © 2015 Elsevier B.V. All rights reserved.

  18. A comparative analysis of primary and secondary Gleason pattern predictive ability for positive surgical margins after radical prostatectomy.

    Science.gov (United States)

    Sfoungaristos, S; Kavouras, A; Kanatas, P; Polimeros, N; Perimenis, P

    2011-01-01

    To compare the predictive ability of primary and secondary Gleason pattern for positive surgical margins in patients with clinically localized prostate cancer and a preoperative Gleason score ≤ 6. A retrospective analysis of the medical records of patients undergone a radical prostatectomy between January 2005 and October 2010 was conducted. Patients' age, prostate volume, preoperative PSA, biopsy Gleason score, the 1st and 2nd Gleason pattern were entered a univariate and multivariate analysis. The 1st and 2nd pattern were tested for their ability to predict positive surgical margins using receiver operating characteristic curves. Positive surgical margins were noticed in 56 cases (38.1%) out of 147 studied patients. The 2nd pattern was significantly greater in those with positive surgical margins while the 1st pattern was not significantly different between the 2 groups of patients. ROC analysis revealed that area under the curve was 0.53 (p=0.538) for the 1st pattern and 0.60 (p=0.048) for the 2nd pattern. Concerning the cases with PSA <10 ng/ml, it was also found that only the 2nd pattern had a predictive ability (p=0.050). When multiple logistic regression analysis was conducted it was found that the 2nd pattern was the only independent predictor. The second Gleason pattern was found to be of higher value than the 1st one for the prediction of positive surgical margins in patients with preoperative Gleason score ≤ 6 and this should be considered especially when a neurovascular bundle sparing radical prostatectomy is planned, in order not to harm the oncological outcome.

  19. Upper mantle velocity structure beneath Italy from direct and secondary P-wave teleseismic tomography

    Directory of Open Access Journals (Sweden)

    P. De Gori

    1997-06-01

    Full Text Available High-quality teleseismic data digitally recorded by the National Seismic Network during 1988-1995 have been analysed to tomographically reconstruct the aspherical velocity structure of the upper mantle beneath the Italian region. To improve the quality and the reliability of the tomographic images, both direct (P, PKPdf and secondary (pP,sP,PcP,PP,PKPbc,PKPab travel-time data were used in the inversion. Over 7000 relative residuals were computed with respect to the IASP91 Earth velocity model and inverted using a modified version of the ACH technique. Incorporation of data of secondary phases resulted in a significant improvement of the sampling of the target volume and of the spatial resolution of the heterogeneous zones. The tomographic images show that most of the lateral variations in the velocity field are confined in the first ~250 km of depth. Strong low velocity anomalies are found beneath the Po plain, Tuscany and Eastern Sicily in the depth range between 35 and 85 km. High velocity anomalies dominate the upper mantle beneath the Central-Western Alps, Northern-Central Apennines and Southern Tyrrhenian sea at lithospheric depths between 85 and 150 km. At greater depth, positive anomalies are still observed below the northernmost part of the Apenninic chain and Southern Tyrrhenian sea. Deeper anomalies present in the 3D velocity model computed by inverting only the first arrivals dataset, generally appear less pronounced in the new tomographic reconstructions. We interpret this as the result of the ray sampling improvement on the reduction of the vertical smearing effects.

  20. Structural Acoustic Prediction and Interior Noise Control Technology

    Science.gov (United States)

    Mathur, G. P.; Chin, C. L.; Simpson, M. A.; Lee, J. T.; Palumbo, Daniel L. (Technical Monitor)

    2001-01-01

    This report documents the results of Task 14, "Structural Acoustic Prediction and Interior Noise Control Technology". The task was to evaluate the performance of tuned foam elements (termed Smart Foam) both analytically and experimentally. Results taken from a three-dimensional finite element model of an active, tuned foam element are presented. Measurements of sound absorption and sound transmission loss were taken using the model. These results agree well with published data. Experimental performance data were taken in Boeing's Interior Noise Test Facility where 12 smart foam elements were applied to a 757 sidewall. Several configurations were tested. Noise reductions of 5-10 dB were achieved over the 200-800 Hz bandwidth of the controller. Accelerometers mounted on the panel provided a good reference for the controller. Configurations with far-field error microphones outperformed near-field cases.

  1. Simple neural substrate predicts complex rhythmic structure in duetting birds

    Science.gov (United States)

    Amador, Ana; Trevisan, M. A.; Mindlin, G. B.

    2005-09-01

    Horneros (Furnarius Rufus) are South American birds well known for their oven-looking nests and their ability to sing in couples. Previous work has analyzed the rhythmic organization of the duets, unveiling a mathematical structure behind the songs. In this work we analyze in detail an extended database of duets. The rhythms of the songs are compatible with the dynamics presented by a wide class of dynamical systems: forced excitable systems. Compatible with this nonlinear rule, we build a biologically inspired model for how the neural and the anatomical elements may interact to produce the observed rhythmic patterns. This model allows us to synthesize songs presenting the acoustic and rhythmic features observed in real songs. We also make testable predictions in order to support our hypothesis.

  2. RNAsnp: efficient detection of local RNA secondary structure changes induced by SNPs

    DEFF Research Database (Denmark)

    Radhakrishnan, Sabarinathan; Tafer, Hakim; Seemann, Ernst Stefan

    2013-01-01

    into structural effects of SNPs. The global measures employed so far suffer from limited accuracy of folding programs on large RNAs and are computationally too demanding for genome-wide applications. Here, we present a strategy that focuses on the local regions of maximal structural change between mutant and wild......-type. These local regions are approximated in a "screening mode" that is intended for genome-wide applications. Furthermore, localized regions are identified as those with maximal discrepancy. The mutation effects are quantified in terms of empirical P values. To this end, the RNAsnp software uses extensive...... precomputed tables of the distribution of SNP effects as function of length and GC content. RNAsnp thus achieves both a noise reduction and speed-up of several orders of magnitude over shuffling-based approaches. On a data set comprising 501 SNPs associated with human-inherited diseases, we predict 54 to have...

  3. 3D CAFE modeling of grain structures: application to primary dendritic and secondary eutectic solidification

    International Nuclear Information System (INIS)

    Carozzani, T; Digonnet, H; Gandin, Ch-A

    2012-01-01

    A three-dimensional model is presented for the prediction of grain structures formed in casting. It is based on direct tracking of grain boundaries using a cellular automaton (CA) method. The model is fully coupled with a solution of the heat flow computed with a finite element (FE) method. Several unique capabilities are implemented including (i) the possibility to track the development of several types of grain structures, e.g. dendritic and eutectic grains, (ii) a coupling scheme that permits iterations between the FE method and the CA method, and (iii) tabulated enthalpy curves for the solid and liquid phases that offer the possibility to work with multicomponent alloys. The present CAFE model is also fully parallelized and runs on a cluster of computers. Demonstration is provided by direct comparison between simulated and recorded cooling curves for a directionally solidified aluminum–7 wt% silicon alloy

  4. Predicting DNA-binding proteins and binding residues by complex structure prediction and application to human proteome.

    Directory of Open Access Journals (Sweden)

    Huiying Zhao

    Full Text Available As more and more protein sequences are uncovered from increasingly inexpensive sequencing techniques, an urgent task is to find their functions. This work presents a highly reliable computational technique for predicting DNA-binding function at the level of protein-DNA complex structures, rather than low-resolution two-state prediction of DNA-binding as most existing techniques do. The method first predicts protein-DNA complex structure by utilizing the template-based structure prediction technique HHblits, followed by binding affinity prediction based on a knowledge-based energy function (Distance-scaled finite ideal-gas reference state for protein-DNA interactions. A leave-one-out cross validation of the method based on 179 DNA-binding and 3797 non-binding protein domains achieves a Matthews correlation coefficient (MCC of 0.77 with high precision (94% and high sensitivity (65%. We further found 51% sensitivity for 82 newly determined structures of DNA-binding proteins and 56% sensitivity for the human proteome. In addition, the method provides a reasonably accurate prediction of DNA-binding residues in proteins based on predicted DNA-binding complex structures. Its application to human proteome leads to more than 300 novel DNA-binding proteins; some of these predicted structures were validated by known structures of homologous proteins in APO forms. The method [SPOT-Seq (DNA] is available as an on-line server at http://sparks-lab.org.

  5. Assessment of CASP7 structure predictions for template free targets.

    Science.gov (United States)

    Jauch, Ralf; Yeo, Hock Chuan; Kolatkar, Prasanna R; Clarke, Neil D

    2007-01-01

    In CASP7, protein structure prediction targets that lacked substantial similarity to a protein in the PDB at the time of assessment were considered to be free modeling targets (FM). We assessed predictions for 14 FM targets as well as four other targets that were deemed to be on the borderline between FM targets and template based modeling targets (TBM/FM). GDT_TS was used as one measure of model quality. Model quality was also assessed by visual inspection. Visual inspection was performed by three independent assessors who were blinded to GDT_TS scores and other quantitative measures of model quality. The best models by visual inspection tended to rank among the top few percent by GDT_TS, but were typically not the highest scoring models. Thus, visual inspection remains an essential component of assessment for FM targets. Overall, group TS020 (Baker) performed best, but success on individual targets was widely distributed among many groups. Among these other groups, TS024 and TS025 (Zhang and Zhang server) performed notably well without exceptionally large computing resources. This should be considered encouraging for future CASPs. There was a sense of progress in template FM relative to CASP6, but we were unable to demonstrate this progress objectively. (c) 2007 Wiley-Liss, Inc.

  6. Lifetime prediction of structures submitted to thermal fatigue loadings

    International Nuclear Information System (INIS)

    Amiable, S.

    2006-01-01

    The aim of this work is to predict the lifetime of structures submitted to thermal fatigue loadings. This work lies within the studies undertaken by the CEA on the thermal fatigue problems from the french reactor of Civaux. In particular we study the SPLASH test: a specimen is heated continuously and cyclically cooled down by a water spray. This loading generates important temperature gradients in space and time and leads to the initiation and the propagation of a crack network. We propose a new thermo-mechanical model to simulate the SPLASH experiment and we propose a new fatigue criterion to predict the lifetime of the SPLASH specimen. We propose and compare several numerical models with various complexity to estimate the mechanical response of the SPLASH specimen. The practical implications of this work are the reevaluation of the hypothesis used in the French code RCC, which are used to simulate thermal shock and to interpret the results in terms of fatigue. This work leads to new perspectives on the mechanical interpretation of the fatigue criterion. (author)

  7. Secondary flow vortical structures in a 180∘ elastic curved vessel with torsion under steady and pulsatile inflow conditions

    Science.gov (United States)

    Najjari, Mohammad Reza; Plesniak, Michael W.

    2018-01-01

    Secondary flow structures in a 180∘ curved pipe model of an artery are studied using particle image velocimetry. Both steady and pulsatile inflow conditions are investigated. In planar curved pipes with steady flow, multiple (two, four, six) vortices are detected. For pulsatile flow, various pairs of vortices, i.e., Dean, deformed-Dean, Lyne-type, and split-Dean, are present in the cross section of the pipe at 90∘ into the bend. The effects of nonplanar curvature (torsion) and vessel dilatation on these vortical structures are studied. Torsion distorts the symmetric secondary flows (which exist in planar curvatures) and can result in formation of more complex vortical structures. For example, the split-Dean and Lyne-type vortices with same rotation direction originating from opposite sides of the cross section tend to merge together in pulsatile flow. The vortical structures in elastic vessels with dilatation (0.61%-3.23%) are also investigated and the results are compared with rigid model results. It was found that the secondary flow structures in rigid and elastic models are similar, and hence the local compliance of the vessel does not affect the morphology of secondary flow structures.

  8. Initial Serum Ferritin Predicts Number of Therapeutic Phlebotomies to Iron Depletion in Secondary Iron Overload

    Science.gov (United States)

    Panch, Sandhya R.; Yau, Yu Ying; West, Kamille; Diggs, Karen; Sweigart, Tamsen; Leitman, Susan F.

    2014-01-01

    Background Therapeutic phlebotomy is increasingly used in patients with transfusional siderosis to mitigate organ injury associated with iron overload (IO). Laboratory response parameters and therapy duration are not well characterized in such patients. Methods We retrospectively evaluated 99 consecutive patients undergoing therapeutic phlebotomy for either transfusional IO (TIO, n=88; 76% had undergone hematopoietic transplantation) or non-transfusional indications (hyperferritinemia or erythrocytosis) (n=11). CBC, serum ferritin (SF), transferrin saturation, and transaminases were measured serially. Phlebotomy goal was an SF< 300 mcg/L. Results Mean SF prior to phlebotomy among TIO and nontransfusional subjects was 3,093 and 396 mcg/L, respectively. Transfusion burden in the TIO group was 94 ± 108 (mean ± SD) RBC units; about half completed therapy with 24 ± 23 phlebotomies (range 1–103). One-third was lost to follow-up. Overall, 15% had mild adverse effects, including headache, nausea, and dizziness, mainly during first phlebotomy. Prior transfusion burden correlated poorly with initial ferritin and total number of phlebotomies to target (NPT) in the TIO group. However, NPT was strongly correlated with initial SF (R2=0.8; p<0.0001) in both TIO and nontransfusional groups. ALT decreased significantly with serial phlebotomy in all groups (mean initial and final values, 61 and 39 U/L; p = 0.03). Conclusions Initial SF but not transfusion burden predicted number of phlebotomies to target in patients with TIO. Despite good treatment tolerance, significant losses to follow-up were noted. Providing patients with an estimated phlebotomy number and follow-up duration, and thus a finite endpoint, may improve compliance. Hepatic function improved with iron off-loading. PMID:25209879

  9. Halide salts and their structural properties in presence of secondary amine based molecule: A combined experimental and theoretical analysis

    Science.gov (United States)

    Ghosh, Pritam; Hazra, Abhijit; Ghosh, Meenakshi; Chandra Murmu, Naresh; Banerjee, Priyabrata

    2018-04-01

    Biologically relevant halide salts and its solution state structural properties are always been significant. In general, exposure of halide salts into polar solution medium results in solvation which in turn separates the cationic and anionic part of the salt. However, the conventional behaviour of salts might alter in presence of any secondary amine based compound, i.e.; moderately strong Lewis acid. In its consequence, to investigate the effect of secondary amine based compound in the salt solution, novel (E)-2-(4-bromobenzylidene)-1-(perfluorophenyl) hydrazine has been synthesized and used as secondary amine source. The secondary amine compound interestingly shows a drastic color change upon exposure to fluoride salts owing to hydrogen bonding interaction. Several experimental methods, e.g.; SCXRD, UV-Vis, FT-IR, ESI-MS and DLS together with modern DFT (i.e.; DFT-D3) have been performed to explore the structural properties of the halide salts upon exposure to secondary amine based compound. The effect of counter cation of the fluoride salt in binding with secondary amine source has also been investigated.

  10. Imaging the 3D structure of secondary osteons in human cortical bone using phase-retrieval tomography

    Energy Technology Data Exchange (ETDEWEB)

    Arhatari, B D; Peele, A G [Department of Physics, La Trobe University, Victoria 3086 (Australia); Cooper, D M L [Department of Anatomy and Cell Biology, University of Saskatchewan, Saskatoon (Canada); Thomas, C D L; Clement, J G [Melbourne Dental School, University of Melbourne, Victoria 3010 (Australia)

    2011-08-21

    By applying a phase-retrieval step before carrying out standard filtered back-projection reconstructions in tomographic imaging, we were able to resolve structures with small differences in density within a densely absorbing sample. This phase-retrieval tomography is particularly suited for the three-dimensional segmentation of secondary osteons (roughly cylindrical structures) which are superimposed upon an existing cortical bone structure through the process of turnover known as remodelling. The resulting images make possible the analysis of the secondary osteon structure and the relationship between an osteon and the surrounding tissue. Our observations have revealed many different and complex 3D structures of osteons that could not be studied using previous methods. This work was carried out using a laboratory-based x-ray source, which makes obtaining these sorts of images readily accessible.

  11. Residual structure of Streptococcus mutans biofilm following complete disinfection favors secondary bacterial adhesion and biofilm re-development.

    Directory of Open Access Journals (Sweden)

    Tatsuya Ohsumi

    Full Text Available Chemical disinfection of oral biofilms often leaves biofilm structures intact. This study aimed to examine whether the residual structure promotes secondary bacterial adhesion. Streptococcus mutans biofilms generated on resin-composite disks in a rotating disc reactor were disinfected completely with 70% isopropyl alcohol, and were again cultured in the same reactor after resupplying with the same bacterial solution. Specimens were subjected to fluorescence confocal laser scanning microscopy, viable cell counts and PCR-Invader assay in order to observe and quantify secondarily adhered cells. Fluorescence microscopic analysis, particularly after longitudinal cryosectioning, demonstrated stratified patterns of viable cells on the disinfected biofilm structure. Viable cell counts of test specimens were significantly higher than those of controls, and increased according to the amount of residual structure and culture period. Linear regression analysis exhibited a high correlation between viable and total cell counts. It was concluded that disinfected biofilm structures favored secondary bacterial adhesion.

  12. Occupational Structure in European Countries: What do Forecasts Predict?

    Directory of Open Access Journals (Sweden)

    Nina Vishnevskaya

    2017-12-01

    Full Text Available This paper analyzes the future occupational structure of the labour force in European members of the Organisation for Co-operation and Development (OECD. Occupational structure forecasts allow researchers to evaluate the quality of job openings and, consequently, overall future labour market performance. Identification of demand for certain occupations in Europe can facilitate assessment of whether processes occurring in the Russian labour market are consistent with global trends. The paper discusses the methodology of labour force forecasting and basic research approaches to the prediction of occupational structure changes. It emphasizes the dynamics of demand for representatives of certain occupations in Europe by identifying the fastest growing and declining occupations and suggests possible reasons for changing demand. The paper demonstrates that the main occupational trend over the next decade will consist in the increasing importance of professionals, as well as technicians and associate professionals. The increase in demand for health professionals and representatives of occupations providing scientific and technological innovation will be most significant. At the same time, it is expected that demand for elementary occupations will also rise. This process will evolve simultaneously with the decrease in the total number of skilled and semi-skilled blue-collar occupations due to globalization and the reduction of industrial production in developed economies. The ongoing “mechanization” of many job functions will not eliminate the need for occupations such as cleaners, labourers, domestic servants or personal workers. The need for these jobs allow employees with low levels of education to enter the labour market rather than depending on the social benefit system. Another tendency for all countries with developed economies will be reduced demand for many whitecollar occupations as modern computer technologies and the automation of many

  13. Secondary structure and phylogeny of Staphylococcus and Micrococcus 5S rRNAs.

    Science.gov (United States)

    Dekio, S; Yamasaki, R; Jidoi, J; Hori, H; Osawa, S

    1984-01-01

    Nucleotide sequences of 5S rRNAs from four bacteria, Staphylococcus aureus Smith (diffuse), Staphylococcus epidermidis ATCC 14990, Micrococcus luteus ATCC 9341 and Micrococcus luteus ATCC 4698, were determined. The secondary structural models of S. aureus and S. epidermidis sequences showed characteristics of the gram-positive bacterial 5S rRNA (116-N type [H. Hori and S. Osawa, Proc. Natl. Acad. Sci. U.S.A. 76:381-385, 1979]). Those of M. luteus ATCC 9341 and M. luteus ATCC 4698 together with that of Streptomyces griseus (A. Simoncsits, Nucleic Acids Res. 8:4111-4124, 1980) showed intermediary characteristics between the gram-positive and gram-negative (120-N type [H. Hori and S. Osawa, 1979]) 5S rRNAs. This and previous studies revealed that there exist at least three major groups of eubacteria having distinct 5S rRNA and belonging to different stems in the 5S rRNA phylogenic tree. PMID:6735981

  14. Flammability of self-extinguishing kenaf/ABS nanoclays composite for aircraft secondary structure

    Science.gov (United States)

    Karunakaran, S.; Majid, D. L.; Mohd Tawil, M. L.

    2016-10-01

    This study investigates the flammability properties of kenaf fiber reinforced acrylonitrile butadiene styrene (ABS) with nanoclays composites. Natural fiber is one of the potential materials to be used with thermoplastic as a composite due to its attractive properties such as lightweight and strong. In this paper, flammability properties of this material are evaluated through Underwriters Laboratory 94 Horizontal Burning (UL94 HB), which has been conducted for both controlled and uncontrolled conditions, smoke density and limiting oxygen index tests (LOI). These flammability tests are in compliance with the Federal Aviation Regulation (FAR) requirement. The results from UL94 HB and smoke density tests show that the presence of nanoclays with effective composition of kenaf fiber reinforced ABS has enhanced the burning characteristics of the material by hindering propagation of flame spread over the surface of the material through char formation. Consequently, this decreases the burning rate and produces low amount of smoke during burning. On contrary, through LOI test, this material requires less oxygen to burn when exposed to fire, which hinders the enhancement of burning characteristics. This is due to burning mechanism exhibited by nanoclays that catalyzes barrier formation and flame propagation rate over the surface of the biocomposite material. Overall, these experimental results suggest that this biocomposite material is capable of self-extinguishing and possesses effective fire extinction. The observed novel synergism from the result obtained is promising to be implemented in secondary structures of aircraft with significant benefits such as cost-effective, lightweight and biodegradable self-extinguishing biocomposite.

  15. Comparative Genome Structure, Secondary Metabolite, and Effector Coding Capacity across Cochliobolus Pathogens

    Energy Technology Data Exchange (ETDEWEB)

    Condon, Bradford J.; Leng, Yueqiang; Wu, Dongliang; Bushley, Kathryn E.; Ohm, Robin A.; Otillar, Robert; Martin, Joel; Schackwitz, Wendy; Grimwood, Jane; MohdZainudin, NurAinlzzati; Xue, Chunsheng; Wang, Rui; Manning, Viola A.; Dhillon, Braham; Tu, Zheng Jin; Steffenson, Brian J.; Salamov, Asaf; Sun, Hui; Lowry, Steve; LaButti, Kurt; Han, James; Copeland, Alex; Lindquist, Erika; Barry, Kerrie; Schmutz, Jeremy; Baker, Scott E.; Ciuffetti, Lynda M.; Grigoriev, Igor V.; Zhong, Shaobin; Turgeon, B. Gillian

    2013-01-24

    The genomes of five Cochliobolus heterostrophus strains, two Cochliobolus sativus strains, three additional Cochliobolus species (Cochliobolus victoriae, Cochliobolus carbonum, Cochliobolus miyabeanus), and closely related Setosphaeria turcica were sequenced at the Joint Genome Institute (JGI). The datasets were used to identify SNPs between strains and species, unique genomic regions, core secondary metabolism genes, and small secreted protein (SSP) candidate effector encoding genes with a view towards pinpointing structural elements and gene content associated with specificity of these closely related fungi to different cereal hosts. Whole-genome alignment shows that three to five of each genome differs between strains of the same species, while a quarter of each genome differs between species. On average, SNP counts among field isolates of the same C. heterostrophus species are more than 25 higher than those between inbred lines and 50 lower than SNPs between Cochliobolus species. The suites of nonribosomal peptide synthetase (NRPS), polyketide synthase (PKS), and SSP encoding genes are astoundingly diverse among species but remarkably conserved among isolates of the same species, whether inbred or field strains, except for defining examples that map to unique genomic regions. Functional analysis of several strain-unique PKSs and NRPSs reveal a strong correlation with a role in virulence.

  16. Genomic mid-range inhomogeneity correlates with an abundance of RNA secondary structures

    Directory of Open Access Journals (Sweden)

    Song Jun

    2008-06-01

    Full Text Available Abstract Background Genomes possess different levels of non-randomness, in particular, an inhomogeneity in their nucleotide composition. Inhomogeneity is manifest from the short-range where neighboring nucleotides influence the choice of base at a site, to the long-range, commonly known as isochores, where a particular base composition can span millions of nucleotides. A separate genomic issue that has yet to be thoroughly elucidated is the role that RNA secondary structure (SS plays in gene expression. Results We present novel data and approaches that show that a mid-range inhomogeneity (~30 to 1000 nt not only exists in mammalian genomes but is also significantly associated with strong RNA SS. A whole-genome bioinformatics investigation of local SS in a set of 11,315 non-redundant human pre-mRNA sequences has been carried out. Four distinct components of these molecules (5'-UTRs, exons, introns and 3'-UTRs were considered separately, since they differ in overall nucleotide composition, sequence motifs and periodicities. For each pre-mRNA component, the abundance of strong local SS ( Conclusion We demonstrate that the excess of strong local SS in pre-mRNAs is linked to the little explored phenomenon of genomic mid-range inhomogeneity (MRI. MRI is an interdependence between nucleotide choice and base composition over a distance of 20–1000 nt. Additionally, we have created a public computational resource to support further study of genomic MRI.

  17. Influence of secondary water supply systems on microbial community structure and opportunistic pathogen gene markers.

    Science.gov (United States)

    Li, Huan; Li, Shang; Tang, Wei; Yang, Yang; Zhao, Jianfu; Xia, Siqing; Zhang, Weixian; Wang, Hong

    2018-06-01

    Secondary water supply systems (SWSSs) refer to the in-building infrastructures (e.g., water storage tanks) used to supply water pressure beyond the main distribution systems. The purpose of this study was to investigate the influence of SWSSs on microbial community structure and the occurrence of opportunistic pathogens, the latter of which are an emerging public health concern. Higher numbers of bacterial 16S rRNA genes, Legionella and mycobacterial gene markers were found in public building taps served by SWSSs relative to the mains, regardless of the flushing practice (P water retention time, warm temperature and loss of disinfectant residuals promoted microbial growth and colonization of potential pathogens in SWSSs. Varied levels of microbial community shifts were found in different types of SWSSs during water transportation from the distribution main to taps, highlighting the critical role of SWSSs in shaping the drinking water microbiota. Overall, the results provided insight to factors that might aid in controlling pathogen proliferation in real-world water systems using SWSSs. Copyright © 2018 Elsevier Ltd. All rights reserved.

  18. Temperature Effects on Mechanical Properties of Woven Thermoplastic Composites for Secondary Aircraft Structure Applications

    Directory of Open Access Journals (Sweden)

    Wang Yue

    2017-01-01

    Full Text Available The effect of temperature on the mechanical behavior of 8-H satin woven glass fabric/polyethylene sulfide (GF/PPS was investigated in this paper. Static-tensile tests were both conducted on notched and unnotched specimens at typical temperatures (ambient, 95°C and 125°C based on the glass transition temperatures (Tg of the neat resin and composite, their strength and moduli were obtained and compared. The damage patterns of failed specimens of notched and unnotched were examined with the aid of high-definition camera and stereomicroscope. The results of stress-strain relationships showed that the slight nonlinearity of the curves were observed for these two specimens, which was associated with the plastic deformation of localized resin. The damage patterns of notched and unnotched specimens at different temperatures proved that damage and plastic deformation were two simultaneous mechanisms and it was prominent in the notched. It was the overstress accommodation mechanism that led to a relative high strength rentention for the notched and a reduction of the hole sensitivity. The results obtained in this paper indicated that GF/PPS can be used as secondary aircraft structures at elevated temperatures higher than its Tg.

  19. Molecular structure impacts on secondary organic aerosol formation from glycol ethers

    Science.gov (United States)

    Li, Lijie; Cocker, David R.

    2018-05-01

    Glycol ethers, a class of widely used solvents in consumer products, are often considered exempt as volatile organic compounds based on their vapor pressure or boiling points by regulatory agencies. However, recent studies found that glycol ethers volatilize at ambient conditions nearly as rapidly as the traditional high-volatility solvents indicating the potential of glycol ethers to form secondary organic aerosol (SOA). This is the first work on SOA formation from glycol ethers. The impact of molecular structure, specifically -OH, on SOA formation from glycol ethers and related ethers are investigated in the work. Ethers with and without -OH, with methyl group hindrance on -OH and with -OH at different location are studied in the presence of NOX and under "NOX free" conditions. Photooxidation experiments under different oxidation conditions confirm that the processing of ethers is a combination of carbonyl formation, cyclization and fragmentation. Bulk SOA chemical composition analysis and oxidation products identified in both gas and particle phase suggests that the presence and location of -OH in the carbon bond of ethers determine the occurrence of cyclization mechanism during ether oxidation. The cyclization is proposed as a critical SOA formation mechanism to prevent the formation of volatile compounds from fragmentation during the oxidation of ethers. Glycol ethers with -CH2-O-CH2CH2OH structure is found to readily form cyclization products, especially with the presence of NOx, which is more relevant to urban atmospheric conditions than without NOx. Glycol ethers are evaluated as dominating SOA precursors among all ethers studied. It is estimated that the contribution of glycol ethers to anthropogenic SOA is roughly 1% of the current organic aerosol from mobile sources. The contribution of glycol ethers to anthropogenic SOA is roughly 1% of the current organic aerosol from mobile sources and will play a more important role in future anthropogenic SOA

  20. Ebola virus RNA editing depends on the primary editing site sequence and an upstream secondary structure.

    Directory of Open Access Journals (Sweden)

    Masfique Mehedi

    Full Text Available Ebolavirus (EBOV, the causative agent of a severe hemorrhagic fever and a biosafety level 4 pathogen, increases its genome coding capacity by producing multiple transcripts encoding for structural and nonstructural glycoproteins from a single gene. This is achieved through RNA editing, during which non-template adenosine residues are incorporated into the EBOV mRNAs at an editing site encoding for 7 adenosine residues. However, the mechanism of EBOV RNA editing is currently not understood. In this study, we report for the first time that minigenomes containing the glycoprotein gene editing site can undergo RNA editing, thereby eliminating the requirement for a biosafety level 4 laboratory to study EBOV RNA editing. Using a newly developed dual-reporter minigenome, we have characterized the mechanism of EBOV RNA editing, and have identified cis-acting sequences that are required for editing, located between 9 nt upstream and 9 nt downstream of the editing site. Moreover, we show that a secondary structure in the upstream cis-acting sequence plays an important role in RNA editing. EBOV RNA editing is glycoprotein gene-specific, as a stretch encoding for 7 adenosine residues located in the viral polymerase gene did not serve as an editing site, most likely due to an absence of the necessary cis-acting sequences. Finally, the EBOV protein VP30 was identified as a trans-acting factor for RNA editing, constituting a novel function for this protein. Overall, our results provide novel insights into the RNA editing mechanism of EBOV, further understanding of which might result in novel intervention strategies against this viral pathogen.

  1. Ebola virus RNA editing depends on the primary editing site sequence and an upstream secondary structure.

    Science.gov (United States)

    Mehedi, Masfique; Hoenen, Thomas; Robertson, Shelly; Ricklefs, Stacy; Dolan, Michael A; Taylor, Travis; Falzarano, Darryl; Ebihara, Hideki; Porcella, Stephen F; Feldmann, Heinz

    2013-01-01

    Ebolavirus (EBOV), the causative agent of a severe hemorrhagic fever and a biosafety level 4 pathogen, increases its genome coding capacity by producing multiple transcripts encoding for structural and nonstructural glycoproteins from a single gene. This is achieved through RNA editing, during which non-template adenosine residues are incorporated into the EBOV mRNAs at an editing site encoding for 7 adenosine residues. However, the mechanism of EBOV RNA editing is currently not understood. In this study, we report for the first time that minigenomes containing the glycoprotein gene editing site can undergo RNA editing, thereby eliminating the requirement for a biosafety level 4 laboratory to study EBOV RNA editing. Using a newly developed dual-reporter minigenome, we have characterized the mechanism of EBOV RNA editing, and have identified cis-acting sequences that are required for editing, located between 9 nt upstream and 9 nt downstream of the editing site. Moreover, we show that a secondary structure in the upstream cis-acting sequence plays an important role in RNA editing. EBOV RNA editing is glycoprotein gene-specific, as a stretch encoding for 7 adenosine residues located in the viral polymerase gene did not serve as an editing site, most likely due to an absence of the necessary cis-acting sequences. Finally, the EBOV protein VP30 was identified as a trans-acting factor for RNA editing, constituting a novel function for this protein. Overall, our results provide novel insights into the RNA editing mechanism of EBOV, further understanding of which might result in novel intervention strategies against this viral pathogen.

  2. Fold classification based on secondary structure – how much is gained by including loop topology?

    Directory of Open Access Journals (Sweden)

    Przytycka Teresa

    2006-03-01

    Full Text Available Abstract Background It has been proposed that secondary structure information can be used to classify (to some extend protein folds. Since this method utilizes very limited information about the protein structure, it is not surprising that it has a higher error rate than the approaches that use full 3D fold description. On the other hand, the comparing of 3D protein structures is computing intensive. This raises the question to what extend the error rate can be decreased with each new source of information, especially if the new information can still be used with simple alignment algorithms. We consider the question whether the information about closed loops can improve the accuracy of this approach. While the answer appears to be obvious, we had to overcome two challenges. First, how to code and to compare topological information in such a way that local alignment of strings will properly identify similar structures. Second, how to properly measure the effect of new information in a large data sample. We investigate alternative ways of computing and presenting this information. Results We used the set of beta proteins with at most 30% pairwise identity to test the approach; local alignment scores were used to build a tree of clusters which was evaluated using a new log-odd cluster scoring function. In particular, we derive a closed formula for the probability of obtaining a given score by chance.Parameters of local alignment function were optimized using a genetic algorithm. Of 81 folds that had more than one representative in our data set, log-odds scores registered significantly better clustering in 27 cases and significantly worse in 6 cases, and small differences in the remaining cases. Various notions of the significant change or average change were considered and tried, and the results were all pointing in the same direction. Conclusion We found that, on average, properly presented information about the loop topology improves noticeably

  3. Secondary Circulating Prostate Cells Predict Biochemical Failure in Prostate Cancer Patients after Radical Prostatectomy and without Evidence of Disease

    Directory of Open Access Journals (Sweden)

    Nigel P. Murray

    2013-01-01

    Full Text Available Introduction. Although 90% of prostate cancer is considered to be localized, 20%–30% of patients will experience biochemical failure (BF, defined as serum PSA >0.2 ng/mL, after radical prostatectomy (RP. The presence of circulating prostate cells (CPCs in men without evidence of BF may be useful to predict patients at risk for BF. We describe the frequency of CPCs detected after RP, relation with clinicopathological parameters, and association with biochemical failure. Methods and Patients. Serial blood samples were taken during followup after RP, mononuclear cells were obtained by differential gel centrifugation, and CPCs identified using standard immunocytochemistry using anti-PSA monoclonal antibodies. Age, pathological stage (organ confined, nonorgan confined, pathological grade, margin status (positive, negative, extracapsular extension, perineural, vascular, and lymphatic infiltration (positive, negative were compared with the presence/absence of CPCs and with and without biochemical failure. Kaplan Meier methods were used to compare the unadjusted biochemical failure free survival of patients with and without CPCs. Results. 114 men participated, and secondary CPCs were detected more frequently in patients with positive margins, extracapsular extension, and vascular and lymphatic infiltration and were associated with biochemical failure independent of these clinicopathological variables, and with a shorter time to BF. Conclusions. Secondary CPCs are an independent risk factor associated with increased BF in men with a PSA <0.2 ng/mL after radical prostatectomy, but do not determine if the recurrence is due to local or systemic disease. These results warrant larger studies to confirm the findings.

  4. UNRES server for physics-based coarse-grained simulations and prediction of protein structure, dynamics and thermodynamics.

    Science.gov (United States)

    Czaplewski, Cezary; Karczynska, Agnieszka; Sieradzan, Adam K; Liwo, Adam

    2018-04-30

    A server implementation of the UNRES package (http://www.unres.pl) for coarse-grained simulations of protein structures with the physics-based UNRES model, coined a name UNRES server, is presented. In contrast to most of the protein coarse-grained models, owing to its physics-based origin, the UNRES force field can be used in simulations, including those aimed at protein-structure prediction, without ancillary information from structural databases; however, the implementation includes the possibility of using restraints. Local energy minimization, canonical molecular dynamics simulations, replica exchange and multiplexed replica exchange molecular dynamics simulations can be run with the current UNRES server; the latter are suitable for protein-structure prediction. The user-supplied input includes protein sequence and, optionally, restraints from secondary-structure prediction or small x-ray scattering data, and simulation type and parameters which are selected or typed in. Oligomeric proteins, as well as those containing D-amino-acid residues and disulfide links can be treated. The output is displayed graphically (minimized structures, trajectories, final models, analysis of trajectory/ensembles); however, all output files can be downloaded by the user. The UNRES server can be freely accessed at http://unres-server.chem.ug.edu.pl.

  5. Statistical mechanical approach to secondary processes and structural relaxation in glasses and glass formers: a leading model to describe the onset of Johari-Goldstein processes and their relationship with fully cooperative processes.

    Science.gov (United States)

    Crisanti, A; Leuzzi, L; Paoluzzi, M

    2011-09-01

    The interrelation of dynamic processes active on separated time-scales in glasses and viscous liquids is investigated using a model displaying two time-scale bifurcations both between fast and secondary relaxation and between secondary and structural relaxation. The study of the dynamics allows for predictions on the system relaxation above the temperature of dynamic arrest in the mean-field approximation, that are compared with the outcomes of the equations of motion directly derived within the Mode Coupling Theory (MCT) for under-cooled viscous liquids. By varying the external thermodynamic parameters, a wide range of phenomenology can be represented, from a very clear separation of structural and secondary peak in the susceptibility loss to excess wing structures.

  6. Making Sense of Abstract Algebra: Exploring Secondary Teachers' Understandings of Inverse Functions in Relation to Its Group Structure

    Science.gov (United States)

    Wasserman, Nicholas H.

    2017-01-01

    This article draws on semi-structured, task-based interviews to explore secondary teachers' (N = 7) understandings of inverse functions in relation to abstract algebra. In particular, a concept map task is used to understand the degree to which participants, having recently taken an abstract algebra course, situated inverse functions within its…

  7. DNA secondary structure of the released strand stimulates WRN helicase action on forked duplexes without coordinate action of WRN exonuclease

    Energy Technology Data Exchange (ETDEWEB)

    Ahn, Byungchan, E-mail: bbccahn@mail.ulsan.ac.kr [Department of Life Sciences, University of Ulsan, Ulsan (Korea, Republic of); Bohr, Vilhelm A. [Laboratory of Molecular Gerontology, Biomedical Research Center, National Institute on Aging, Baltimore, MD (United States)

    2011-08-12

    Highlights: {yields} In this study, we investigated the effect of a DNA secondary structure on the two WRN activities. {yields} We found that a DNA secondary structure of the displaced strand during unwinding stimulates WRN helicase without coordinate action of WRN exonuclease. {yields} These results imply that WRN helicase and exonuclease activities can act independently. -- Abstract: Werner syndrome (WS) is an autosomal recessive premature aging disorder characterized by aging-related phenotypes and genomic instability. WS is caused by mutations in a gene encoding a nuclear protein, Werner syndrome protein (WRN), a member of the RecQ helicase family, that interestingly possesses both helicase and exonuclease activities. Previous studies have shown that the two activities act in concert on a single substrate. We investigated the effect of a DNA secondary structure on the two WRN activities and found that a DNA secondary structure of the displaced strand during unwinding stimulates WRN helicase without coordinate action of WRN exonuclease. These results imply that WRN helicase and exonuclease activities can act independently, and we propose that the uncoordinated action may be relevant to the in vivo activity of WRN.

  8. Observed Lesson Structure during the First Year of Secondary Education: Exploration of Change and Link with Academic Engagement

    Science.gov (United States)

    Maulana, Ridwan; Opdenakker, Marie-Christine; Stroet, Kim; Bosker, Roel

    2012-01-01

    This study investigates whether lesson structure (LS) matters and which components are important for academic engagement during the first grade of secondary education. Data from videoed lessons of 10 Dutch and 12 Indonesian teachers analyzed using an observation protocol show that six LS components are found, that between class and over…

  9. Observed lesson structure during the first year of secondary education : Exploration of change and link with academic engagement

    NARCIS (Netherlands)

    Maulana, Ridwan; Opdenakker, Marie-Christine; Stroet, Kim; Bosker, Roel

    This study investigates whether lesson structure (LS) matters and which components are important for academic engagement during the first grade of secondary education. Data from videoed lessons of 10 Dutch and 12 Indonesian teachers analyzed using an observation protocol show that six LS components

  10. Novel evolutionary lineages revealed in the Chaetothyriales (Fungi) based on multigene phylogenetic analyses and comparison of ITS secondary structure

    Czech Academy of Sciences Publication Activity Database

    Réblová, Martina; Untereiner, W. A.; Réblová, K.

    2013-01-01

    Roč. 8, č. 5 (2013), e63547 E-ISSN 1932-6203 R&D Projects: GA ČR GAP506/12/0038 Institutional support: RVO:67985939 Keywords : Cyphelophora * Phialophora * secondary structure Subject RIV: EF - Botanics Impact factor: 3.534, year: 2013

  11. Variation in secondary structure of the 16S rRNA molecule in cyanobacteria with implications for phylogenetic analysis

    Czech Academy of Sciences Publication Activity Database

    Řeháková, Klára; Johansen, J. R.; Bowen, M.B.; Martin, M.P.; Sheil, C.A.

    2014-01-01

    Roč. 14, č. 2 (2014), s. 161-178 ISSN 1802-5439 Institutional support: RVO:60077344 Keywords : 16S rRNA secondary structure * cyanobacteria * phylogeny Subject RIV: EE - Microbiology, Virology Impact factor: 1.930, year: 2014

  12. Effect of Programmed Instruction on Students' Attitude towards Structure of the Atom and the Periodic Table among Kenyan Secondary Schools

    Science.gov (United States)

    Wangila, M. J.; Martin, W.; Ronald, M.

    2015-01-01

    This study examined the effect of Programmed Instruction on students' attitude towards Structure of the Atom and the Periodic Table (SAPT) among mixed (co-educational) secondary schools of Butere district, Kakamega county, Kenya. The quasi-experimental research design was adopted, using the nonrandomized Solomon four-group as a model. The sample…

  13. Admission biomarkers of trauma-induced secondary cardiac injury predict adverse cardiac events and are associated with plasma catecholamine levels.

    Science.gov (United States)

    Naganathar, Sriveena; De'Ath, Henry D; Wall, Johanna; Brohi, Karim

    2015-07-01

    Secondary cardiac injury and dysfunction may be important contributors to poor outcomes in trauma patients, but the pathophysiology and clinical impact remain unclear. Early elevations in cardiac injury markers have been associated with the development of adverse cardiac events (ACEs), prolonged intensive care unit stays, and increased mortality. Studies of preinjury β-blocker use suggest a potential protective effect in critically ill trauma patients. This study aimed to prospectively examine the association of early biomarker evidence of trauma-induced secondary cardiac injury (TISCI) and ACEs and to examine the potential contribution of circulating catecholamines to its pathophysiology. Injured patients who met the study criteria were recruited at a single major trauma center. A blood sample was collected immediately on arrival. Serum epinephrine (E), norepinephrine (NE), and cardiac biomarkers including heart-related fatty acid binding protein (H-FABP) were assayed. Data were prospectively collected on ACEs. Of 300 patients recruited, 38 (13%) developed an ACE and had increased mortality (19% vs. 9%, p = 0.01) and longer intensive care unit stays (13 days, p < 0.001). H-FABP was elevated on admission in 56% of the patients, predicted the development of ACE, and was associated with higher mortality (14% vs. 5%, p = 0.01). Admission E and NE levels were strongly associated with elevations in H-FABP and ACEs (E, 274.0 pg/mL vs. 622.5 pg/mL, p < 0.001; NE, 1,063.2 pg/mL vs. 2,032.6 pg/mL, p < 0.001). Catecholamine effect on the development of TISCI or ACEs was not statistically independent of injury severity or depth of shock. Admission levels of H-FABP predict the development of ACEs and may be useful for prognosis and stratification of trauma patients. The development of TISCI and ACEs was associated with high admission levels of catecholamines, but their role in pathogenesis remains unclear. Clinical trials of adrenergic blockade may have the potential to

  14. Ab Initio Predictions of Structures and Densities of Energetic Solids

    National Research Council Canada - National Science Library

    Rice, Betsy M; Sorescu, Dan C

    2004-01-01

    We have applied a powerful simulation methodology known as ab initio crystal prediction to assess the ability of a generalized model of CHNO intermolecular interactions to predict accurately crystal...

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

    DEFF Research Database (Denmark)

    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...

  16. Primary and secondary structural analyses of glutathione S-transferase pi from human placenta.

    Science.gov (United States)

    Ahmad, H; Wilson, D E; Fritz, R R; Singh, S V; Medh, R D; Nagle, G T; Awasthi, Y C; Kurosky, A

    1990-05-01

    The primary structure of glutathione S-transferase (GST) pi from a single human placenta was determined. The structure was established by chemical characterization of tryptic and cyanogen bromide peptides as well as automated sequence analysis of the intact enzyme. The structural analysis indicated that the protein is comprised of 209 amino acid residues and gave no evidence of post-translational modifications. The amino acid sequence differed from that of the deduced amino acid sequence determined by nucleotide sequence analysis of a cDNA clone (Kano, T., Sakai, M., and Muramatsu, M., 1987, Cancer Res. 47, 5626-5630) at position 104 which contained both valine and isoleucine whereas the deduced sequence from nucleotide sequence analysis identified only isoleucine at this position. These results demonstrated that in the one individual placenta studied at least two GST pi genes are coexpressed, probably as a result of allelomorphism. Computer assisted consensus sequence evaluation identified a hydrophobic region in GST pi (residues 155-181) that was predicted to be either a buried transmembrane helical region or a signal sequence region. The significance of this hydrophobic region was interpreted in relation to the mode of action of the enzyme especially in regard to the potential involvement of a histidine in the active site mechanism. A comparison of the chemical similarity of five known human GST complete enzyme structures, one of pi, one of mu, two of alpha, and one microsomal, gave evidence that all five enzymes have evolved by a divergent evolutionary process after gene duplication, with the microsomal enzyme representing the most divergent form.

  17. Phylogenetic reconstruction using secondary structures of Internal Transcribed Spacer 2 (ITS2, rDNA: finding the molecular and morphological gap in Caribbean gorgonian corals

    Directory of Open Access Journals (Sweden)

    Sánchez Juan A

    2007-06-01

    Full Text Available Abstract Background Most phylogenetic studies using current methods have focused on primary DNA sequence information. However, RNA secondary structures are particularly useful in systematics because they include characteristics, not found in the primary sequence, that give "morphological" information. Despite the number of recent molecular studies on octocorals, there is no consensus opinion about a region that carries enough phylogenetic resolution to solve intrageneric or close species relationships. Moreover, intrageneric morphological information by itself does not always produce accurate phylogenies; intra-species comparisons can reveal greater differences than intra-generic ones. The search for new phylogenetic approaches, such as by RNA secondary structure analysis, is therefore a priority in octocoral research. Results Initially, twelve predicted RNA secondary structures were reconstructed to provide the basic information for phylogenetic analyses; they accorded with the 6 helicoidal ring model, also present in other groups of corals and eukaryotes. We obtained three similar topologies for nine species of the Caribbean gorgonian genus Eunicea (candelabrum corals with two sister taxa as outgroups (genera Plexaura and Pseudoplexaura on the basis of molecular morphometrics of ITS2 RNA secondary structures only, traditional primary sequence analyses and maximum likelihood, and a Bayesian analysis of the combined data. The latter approach allowed us to include both primary sequence and RNA molecular morphometrics; each data partition was allowed to have a different evolution rate. In addition, each helix was partitioned as if it had evolved at a distinct rate. Plexaura flexuosa was found to group within Eunicea; this was best supported by both the molecular morphometrics and combined analyses. We suggest Eunicea flexuosa (Lamouroux, 1821 comb. nov., and we present a new species description including Scanning Electron Microscopy (SEM images of

  18. Predictive modeling of pedestal structure in KSTAR using EPED model

    Energy Technology Data Exchange (ETDEWEB)

    Han, Hyunsun; Kim, J. Y. [National Fusion Research Institute, Daejeon 305-806 (Korea, Republic of); Kwon, Ohjin [Department of Physics, Daegu University, Gyeongbuk 712-714 (Korea, Republic of)

    2013-10-15

    A predictive calculation is given for the structure of edge pedestal in the H-mode plasma of the KSTAR (Korea Superconducting Tokamak Advanced Research) device using the EPED model. Particularly, the dependence of pedestal width and height on various plasma parameters is studied in detail. The two codes, ELITE and HELENA, are utilized for the stability analysis of the peeling-ballooning and kinetic ballooning modes, respectively. Summarizing the main results, the pedestal slope and height have a strong dependence on plasma current, rapidly increasing with it, while the pedestal width is almost independent of it. The plasma density or collisionality gives initially a mild stabilization, increasing the pedestal slope and height, but above some threshold value its effect turns to a destabilization, reducing the pedestal width and height. Among several plasma shape parameters, the triangularity gives the most dominant effect, rapidly increasing the pedestal width and height, while the effect of elongation and squareness appears to be relatively weak. Implication of these edge results, particularly in relation to the global plasma performance, is discussed.

  19. Relationship between mRNA secondary structure and sequence variability in Chloroplast genes: possible life history implications.

    Science.gov (United States)

    Krishnan, Neeraja M; Seligmann, Hervé; Rao, Basuthkar J

    2008-01-28

    Synonymous sites are freer to vary because of redundancy in genetic code. Messenger RNA secondary structure restricts this freedom, as revealed by previous findings in mitochondrial genes that mutations at third codon position nucleotides in helices are more selected against than those in loops. This motivated us to explore the constraints imposed by mRNA secondary structure on evolutionary variability at all codon positions in general, in chloroplast systems. We found that the evolutionary variability and intrinsic secondary structure stability of these sequences share an inverse relationship. Simulations of most likely single nucleotide evolution in Psilotum nudum and Nephroselmis olivacea mRNAs, indicate that helix-forming propensities of mutated mRNAs are greater than those of the natural mRNAs for short sequences and vice-versa for long sequences. Moreover, helix-forming propensity estimated by the percentage of total mRNA in helices increases gradually with mRNA length, saturating beyond 1000 nucleotides. Protection levels of functionally important sites vary across plants and proteins: r-strategists minimize mutation costs in large genes; K-strategists do the opposite. Mrna length presumably predisposes shorter mRNAs to evolve under different constraints than longer mRNAs. The positive correlation between secondary structure protection and functional importance of sites suggests that some sites might be conserved due to packing-protection constraints at the nucleic acid level in addition to protein level constraints. Consequently, nucleic acid secondary structure a priori biases mutations. The converse (exposure of conserved sites) apparently occurs in a smaller number of cases, indicating a different evolutionary adaptive strategy in these plants. The differences between the protection levels of functionally important sites for r- and K-strategists reflect their respective molecular adaptive strategies. These converge with increasing domestication levels of

  20. First Principles Prediction of Structure, Structure Selectivity, and Thermodynamic Stability under Realistic Conditions

    Energy Technology Data Exchange (ETDEWEB)

    Ceder, Gerbrand [Massachusetts Inst. of Technology (MIT), Cambridge, MA (United States). Dept. of Materials and Engineering

    2018-01-28

    Novel materials are often the enabler for new energy technologies. In ab-initio computational materials science, method are developed to predict the behavior of materials starting from the laws of physics, so that properties can be predicted before compounds have to be synthesized and tested. As such, a virtual materials laboratory can be constructed, saving time and money. The objectives of this program were to develop first-principles theory to predict the structure and thermodynamic stability of materials. Since its inception the program focused on the development of the cluster expansion to deal with the increased complexity of complex oxides. This research led to the incorporation of vibrational degrees of freedom in ab-initio thermodynamics, developed methods for multi-component cluster expansions, included the explicit configurational degrees of freedom of localized electrons, developed the formalism for stability in aqueous environments, and culminated in the first ever approach to produce exact ground state predictions of the cluster expansion. Many of these methods have been disseminated to the larger theory community through the Materials Project, pymatgen software, or individual codes. We summarize three of the main accomplishments.

  1. More Than Only Skin Deep: Appearance Self-Concept Predicts Most of Secondary School Students' Self-Esteem.

    Science.gov (United States)

    Baudson, Tanja G; Weber, Kira E; Freund, Philipp A

    2016-01-01

    One important goal of education is to develop students' self-esteem which, in turn, hinges on their self-concept in the academic, physical, and social domains. Prior studies have shown that physical self-concept accounts for most of the variation in self-esteem, with academic and social self-concepts playing a much lesser role. As pressure toward perfection seems to be increasing in education, appearance, and social relationships (three aspects that relate to crucial developmental tasks of adolescence), the goal of the present field study was to examine whether former findings still hold true in the light of the changing societal context. A sample of 2,950 students from a broad range of German secondary schools (47% girls, age 10-19 years) responded to a recently validated German-language questionnaire assessing multiple self-concept facets (Weber and Freund, 2016). We examined which self-concept aspects predict self-esteem best and whether the pattern is comparable across genders and achievement levels using latent regression analyses. Results show that self-concept of appearance is still by far the strongest predictor (total sample: B = 0.77, SE = 0.02, p educational schools. Other aspects play a much lesser role. The discussion explores why appearance is so neglected, compared to the more academic subjects, and what school can do to account for its vast importance for students' self-esteem.

  2. More Than Only Skin Deep: Appearance Self-Concept Predicts Most of Secondary School Students’ Self-Esteem

    Science.gov (United States)

    Baudson, Tanja G.; Weber, Kira E.; Freund, Philipp A.

    2016-01-01

    One important goal of education is to develop students’ self-esteem which, in turn, hinges on their self-concept in the academic, physical, and social domains. Prior studies have shown that physical self-concept accounts for most of the variation in self-esteem, with academic and social self-concepts playing a much lesser role. As pressure toward perfection seems to be increasing in education, appearance, and social relationships (three aspects that relate to crucial developmental tasks of adolescence), the goal of the present field study was to examine whether former findings still hold true in the light of the changing societal context. A sample of 2,950 students from a broad range of German secondary schools (47% girls, age 10–19 years) responded to a recently validated German-language questionnaire assessing multiple self-concept facets (Weber and Freund, 2016). We examined which self-concept aspects predict self-esteem best and whether the pattern is comparable across genders and achievement levels using latent regression analyses. Results show that self-concept of appearance is still by far the strongest predictor (total sample: B = 0.77, SE = 0.02, p educational schools. Other aspects play a much lesser role. The discussion explores why appearance is so neglected, compared to the more academic subjects, and what school can do to account for its vast importance for students’ self-esteem. PMID:27803681

  3. More Than Only Skin Deep: Appearance Self-Concept Predicts Most of Secondary School Students' Self-Esteem

    Directory of Open Access Journals (Sweden)

    Tanja Gabriele Baudson

    2016-10-01

    Full Text Available One important goal of education is to develop students' self-esteem which, in turn, hinges on their self-concept in the academic, physical, and social domains. Prior studies have shown that physical self-concept accounts for most of the variation in self-esteem, with academic and social self-concepts playing a much lesser role. As pressure towards perfection seems to be increasing in education, appearance, and social relationships (three aspects that relate to crucial developmental tasks of adolescence, the goal of the present field study was to examine whether former findings still hold true in the light of the changing societal context. A sample of 2,950 students from a broad range of German secondary schools (47% girls, age 10–19 years responded to a recently validated German-language questionnaire assessing multiple self-concept facets (Weber & Freund, 2016. We examined which self-concept aspects predict self-esteem best and whether the pattern is comparable across genders and achievement levels using latent regression analyses. Results show that self-concept of appearance is still by far the strongest predictor (total sample: B = 0.77, SE = 0.02, p < .01 and that this is especially the case for girls and students from special educational schools. Other aspects play a much lesser role. The discussion explores why appearance is so neglected, compared to the more academic subjects, and what school can do to account for its vast importance for students' self-esteem.

  4. Purification and the Secondary Structure of Fucoidanase from Fusarium sp. LD8

    Directory of Open Access Journals (Sweden)

    Wu Qianqian

    2011-01-01

    Full Text Available The fucoidanase from Fusarium sp. (LD8 was obtained by solid-state fermentation. The fermented solid medium was extracted by citric acid buffer, and the extracts were precipitated by acetone and purified by Sephadex G-100 successively. The results showed that the specific fucoidanase activity of purified enzyme was 22.7-fold than that of the crude enzyme. The recovery of the enzyme was 23.9%. The purified enzyme gave a single band on SDS-PAGE gel, and the molecular weight of fucoidanase was about 64 kDa. The isoelectric point of the enzyme was 4.5. The enzyme properties were also studied. The results showed that the optimum temperature and pH were 60°C and 6.0, respectively; the temperature of half inactivation was 50°C, and the most stable pH for the enzyme was 6.0. KM, and the Vmax  of the enzyme was 8.9 mg·L−1 and 2.02 mg·min−1·mL−1 by using fucoidan from Fucus vesiculosus as substrate. The compositions of the secondary structure of fucoidanase were estimated by FTIR, the second derivative spectra, and the curve-fitting analysis of the amide I bands in their spectra. The results showed that β-sheet was the dominant component (58.6% and α-helix was the least (12%; the content of β-turn and random coil were 15.39% and 14.5%, respectively.

  5. FT-IR spectroscopic studies of protein secondary structures for breast cancer diagnosis

    International Nuclear Information System (INIS)

    Karamancheva, I; Simonova, D.; Milev, A.

    2013-01-01

    Full text: Roughly 14 million new cancer cases and 8 million cancer deaths have occurred worldwide in 2012. At least 30 % of all cancer cases and 40 % of the cancer deaths should be avoided by improving the early detection. Fourier transform infrared (FT-IR) spectroscopy has shown many advantages as a tool for the detection of cancer over the traditional methods such as histopathological analysis, X-ray transmission, ultrasonic and computer tomography techniques. With the aim to establish the FT-IR spectroscopy as an alternative method for the diagnosis of human cancers, we have made several studies to examine in details the spectroscopic properties of normal and carcinomatous tissues. Human breast tissues were obtained immediately after surgical breast resection with the informed patient's consent. In our studies we made extensive use of Fourier self-deconvolution, second-order derivatization, difference spectra, curve-fitting procedures and quantitative determinations according to Beer's law. Cancer is a multi-step process. Characteristic differences in both the frequencies and the intensity ratios of several bands have been revealed. Considerable differences have been found in the spectral patterns. The most important and informative region in the mid-IR for determination of protein secondary structure is the amide I and amide II region. The bands between 1730 and 1600 cm -1 are highly sensitive to conformational changes. Considerable changes were observed in the A1735/A1652 absorbance ratio, which provides a measure for the content of a- helix and P-sheet domains. Our investigations have shown that the major biomarker peaks are in the amide I and amide II regions. In the so calle