Learning biophysically-motivated parameters for alpha helix prediction

<p>Abstract</p> <p>Background</p> <p>Our goal is to develop a state-of-the-art protein secondary structure predictor, with an intuitive and biophysically-motivated energy model. We treat structure prediction as an optimization problem, using parameterizable cost functions representing biological "pseudo-energies". Machine learning methods are applied to estimate the values of the parameters to correctly predict known protein structures.</p> <p>Results</p> <p>Focusing on the prediction of alpha helices in proteins, we show that a model with 302 parameters can achieve a Q_{<it>α </it>}value of 77.6% and an SOV_{<it>α </it>}value of 73.4%. Such performance numbers are among the best for techniques that do not rely on external databases (such as multiple sequence alignments). Further, it is easier to extract biological significance from a model with so few parameters.</p> <p>Conclusion</p> <p>The method presented shows promise for the prediction of protein secondary structure. Biophysically-motivated elementary free-energies can be learned using SVM techniques to construct an energy cost function whose predictive performance rivals state-of-the-art. This method is general and can be extended beyond the all-alpha case described here.</p

Learning biophysically-motivated parameters for alpha helix prediction

Background: Our goal is to develop a state-of-the-art protein secondary structure predictor, with an intuitive and biophysically-motivated energy model. We treat structure prediction as an optimization problem, using parameterizable cost functions representing biological “pseudo-energies. ” Machine learning methods are applied to estimate the values of the parameters to correctly predict known protein structures. Results: Focusing on the prediction of alpha helices in proteins, we show that a model with 302 parameters can achieve a Qα value of 77.6 % and an SOVα value of 73.4%. Such performance numbers are among the best for techniques that do not rely on external databases (such as multiple sequence alignments). Further, it is easier to extract biological significance from a model with so few parameters. Conclusions: The method presented shows promise for the prediction of protein secondary structure. Biophysically-motivated elementary free-energies can be learned using SVM techniques to construct an energy cost function whose predictive performance rivals state-of-the-art. This method is general and can be extended beyond the all-alpha case described here. 1 Backgroun

Models and analysis of vocal emissions for biomedical applications

This book of Proceedings collects the papers presented at the 3rd International Workshop on Models and Analysis of Vocal Emissions for Biomedical Applications, MAVEBA 2003, held 10-12 December 2003, Firenze, Italy. The workshop is organised every two years, and aims to stimulate contacts between specialists active in research and industrial developments, in the area of voice analysis for biomedical applications. The scope of the Workshop includes all aspects of voice modelling and analysis, ranging from fundamental research to all kinds of biomedical applications and related established and advanced technologies

MS FT-2-2 7 Orthogonal polynomials and quadrature: Theory, computation, and applications

Quadrature rules find many applications in science and engineering. Their analysis is a classical area of applied mathematics and continues to attract considerable attention. This seminar brings together speakers with expertise in a large variety of quadrature rules. It is the aim of the seminar to provide an overview of recent developments in the analysis of quadrature rules. The computation of error estimates and novel applications also are described

Generalized averaged Gaussian quadrature and applications

A simple numerical method for constructing the optimal generalized averaged Gaussian quadrature formulas will be presented. These formulas exist in many cases in which real positive GaussKronrod formulas do not exist, and can be used as an adequate alternative in order to estimate the error of a Gaussian rule. We also investigate the conditions under which the optimal averaged Gaussian quadrature formulas and their truncated variants are internal

SIMULATING SEISMIC WAVE PROPAGATION IN TWO-DIMENSIONAL MEDIA USING DISCONTINUOUS SPECTRAL ELEMENT METHODS

We introduce a discontinuous spectral element method for simulating seismic wave in 2- dimensional elastic media. The methods combine the flexibility of a discontinuous finite element method with the accuracy of a spectral method. The elastodynamic equations are discretized using high-degree of Lagrange interpolants and integration over an element is accomplished based upon the Gauss-Lobatto-Legendre integration rule. This combination of discretization and integration results in a diagonal mass matrix and the use of discontinuous finite element method makes the calculation can be done locally in each element. Thus, the algorithm is simplified drastically. We validated the results of one-dimensional problem by comparing them with finite-difference time-domain method and exact solution. The comparisons show excellent agreement

Antioxidant and DPPH-Scavenging Activities of Compounds and Ethanolic Extract of the Leaf and Twigs of Caesalpinia bonduc L. Roxb.

Antioxidant effects of ethanolic extract of Caesalpinia bonduc and its isolated bioactive compounds were evaluated in vitro. The compounds included two new cassanediterpenes, 1α,7α-diacetoxy-5α,6β-dihydroxyl-cass-14(15)-epoxy-16,12-olide (1)and 12α-ethoxyl-1α,14β-diacetoxy-2α,5α-dihydroxyl cass-13(15)-en-16,12-olide(2); and others, bonducellin (3), 7,4’-dihydroxy-3,11-dehydrohomoisoflavanone (4), daucosterol (5), luteolin (6), quercetin-3-methyl ether (7) and kaempferol-3-O-α-L-rhamnopyranosyl-(1Ç2)-β-D-xylopyranoside (8). The antioxidant properties of the extract and compounds were assessed by the measurement of the total phenolic content, ascorbic acid content, total antioxidant capacity and 1-1-diphenyl-2-picryl hydrazyl (DPPH) and hydrogen peroxide radicals scavenging activities.Compounds 3, 6, 7 and ethanolic extract had DPPH scavenging activities with IC50 values of 186, 75, 17 and 102 μg/ml respectively when compared to vitamin C with 15 μg/ml. On the other hand, no significant results were obtained for hydrogen peroxide radical. In addition, compound 7 has the highest phenolic content of 0.81±0.01 mg/ml of gallic acid equivalent while compound 8 showed the highest total antioxidant capacity with 254.31±3.54 and 199.82±2.78 μg/ml gallic and ascorbic acid equivalent respectively. Compound 4 and ethanolic extract showed a high ascorbic acid content of 2.26±0.01 and 6.78±0.03 mg/ml respectively.The results obtained showed the antioxidant activity of the ethanolic extract of C. bonduc and deduced that this activity was mediated by its isolated bioactive compounds