138 resultados para Computational topology


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In this article, we propose a denoising algorithm to denoise a time series y(i) = x(i) + e(i), where {x(i)} is a time series obtained from a time- T map of a uniformly hyperbolic or Anosov flow, and {e(i)} a uniformly bounded sequence of independent and identically distributed (i.i.d.) random variables. Making use of observations up to time n, we create an estimate of x(i) for i<n. We show under typical limiting behaviours of the orbit and the recurrence properties of x(i), the estimation error converges to zero as n tends to infinity with probability 1.

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Two new copper(II) complexes, [Cu-2(L-1)(2)](ClO4)(2) (1) and [Cu(L-2)(ClO4)] (2), of the highly unsymmetrical tetradentate (N3O) Schiff base ligands HL1 and HL2 (where HL1 = N-(2-hydroxyacetophenone)-bis-3-aminopropylamine and HL2 = N-(salicyldehydine)-bis-3-aminopropylamine) have been synthesised using a template method. Their single crystal X-ray structures show that in complex 1 two independent copper(II) centers are doubly bridged through sphenoxo-O atoms (O1A and O1B) of the two ligands and each copper atom is five-coordinated with a distorted square pyramidal geometry. The asymmetric unit of complex 2 consists of two crystallographically independe N-(salicylidene) bis(aminopropyl)amine-copper(II) molecules, A and B, with similar square pyramidal geometries. Cryomagnetic susceptibility measurements (5-300 K) on complex 1 reveal a distinct antiferromagnetic interaction with J=-23.6 cm(-1), which is substantiated by a DFT calculation (J=-27.6 cm(-1)) using the B3LYP functional. Complex 1, immobilized over highly ordered hexagonal mesoporous silica, shows moderate catalytic activity for the epoxidation of cyclohexene and styrene in the presence of TBHP as an oxidant.

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Importance of the field: The shift in focus from ligand based design approaches to target based discovery over the last two to three decades has been a major milestone in drug discovery research. Currently, it is witnessing another major paradigm shift by leaning towards the holistic systems based approaches rather the reductionist single molecule based methods. The effect of this new trend is likely to be felt strongly in terms of new strategies for therapeutic intervention, new targets individually and in combinations, and design of specific and safer drugs. Computational modeling and simulation form important constituents of new-age biology because they are essential to comprehend the large-scale data generated by high-throughput experiments and to generate hypotheses, which are typically iterated with experimental validation. Areas covered in this review: This review focuses on the repertoire of systems-level computational approaches currently available for target identification. The review starts with a discussion on levels of abstraction of biological systems and describes different modeling methodologies that are available for this purpose. The review then focuses on how such modeling and simulations can be applied for drug target discovery. Finally, it discusses methods for studying other important issues such as understanding targetability, identifying target combinations and predicting drug resistance, and considering them during the target identification stage itself. What the reader will gain: The reader will get an account of the various approaches for target discovery and the need for systems approaches, followed by an overview of the different modeling and simulation approaches that have been developed. An idea of the promise and limitations of the various approaches and perspectives for future development will also be obtained. Take home message: Systems thinking has now come of age enabling a `bird's eye view' of the biological systems under study, at the same time allowing us to `zoom in', where necessary, for a detailed description of individual components. A number of different methods available for computational modeling and simulation of biological systems can be used effectively for drug target discovery.

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Aromatic aldehydes and aryl isocyanates do not react at room temperature. However, we have shown for the first time that in the presence of catalytic amounts of group(IV) n-butoxide, they undergo metathesis at room temperature to produce imines with the extrusion of carbon dioxide. The mechanism of action has been investigated by a study of stoichiometric reactions. The insertion of aryl isocyanates into the metal n-butoxide occurs very rapidly. Reaction of the insertion product with the aldehyde is responsible for the metathesis. Among the n-butoxides of group(IV) metals, Ti((OBu)-Bu-n)(4) (8aTi) was found to be more efficient than Zr((OBu)-Bu-n)(4) (8aZr) and Hf((OBu)-Bu-n)(4) (8aHf) in carrying out metathesis. The surprisingly large difference in the metathetic activity of these alkoxides has been probed computationally using model complexes Ti(OMe)(4) (8bTi), Zr(OMe)(4) (8bZr) and Hf(OMe)(4) (8bHf) at the B3LYP/LANL2DZ level of theory. These studies indicate that the insertion product formed by Zr and Hf are extremely stable compared to that formed by Ti. This makes subsequent reaction of Zr and Hf complexes unfavorable.

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Here, we present the synthesis, photochemical, and DNA binding properties of three photoisomerizable azobenzene−distamycin conjugates in which two distamycin units were linked via electron-rich alkoxy or electron-withdrawing carboxamido moieties with the azobenzene core. Like parent distamycin A, these molecules also demonstrated AT-specific DNA binding. Duplex DNA binding abilities of these conjugates were found to depend upon the nature and length of the spacer, the location of protonatable residues, and the isomeric state of the conjugate. The changes in the duplex DNA binding efficiency of the individual conjugates in the dark and with their respective photoirradiated forms were examined by circular dichroism, thermal denaturation of DNA, and Hoechst displacement assay with poly[d(A-T).d(T-A)] DNA in 150 mM NaCl buffer. Computational structural analyses of the uncomplexed ligands using ab initio HF and MP2 theory and molecular docking studies involving the conjugates with duplex d[(GC(AT)10CG)]2 DNA were performed to rationalize the nature of binding of these conjugates.

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The existing vaccines against influenza are based on the generation of neutralizing antibody primarily directed against surface proteins-hernagglutinin and neuraminidase. In this work, we have computationally defined conserved T cell epitopes of proteins of influenza virus H5N1 to help in the design of a vaccine with haplotype specificity for a target population. The peptides from the proteome of H5NI irus which are predicted to bind to different HLAs, do not show similarity with peptides of human proteorne and are also identified to be generated by proteolytic cleavage. These peptides could be made use of in the design of either a DNA vaccine or a subunit vaccine against V influenza. (c) 2007 Elsevier Ltd. All rights reserved.

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Investigations on the electrical switching behavior and thermal studies using Alternating Differential Scanning Calorimetry have been undertaken on bulk, melt-quenched Ge22Te78-,Is (3 <= x <= 10) chalcohalide glasses. All the glasses studied have been found to exhibit memory-type electrical switching. The threshold voltages of Ge22Te78-I-x(x) glasses have been found to increase with the addition of iodine and the composition dependence of threshold voltages of Ge22Te78-xIx glasses exhibits a cusp at 5 at.% of iodine. Also, the variation with composition of the glass transition temperature (Tg) of Ge22Te78-I-x(x) glasses, exhibits a broad hump around this composition. Based on the present results, the composition x = 5 has been identified as the inverse rigidity percolation threshold at which Ge22Te78-I-x(x) glassy system exhibits a change from a stressed rigid amorphous solid to a flexible polymeric glass. Further, a sharp minimum is seen in the composition dependence of non-reversing enthalpy (Delta H-nr) of Ge22Te78-I-x(x) glasses at x = 5, which is suggestive of a thermally reversing window at this composition. (C) 2007 Elsevier Ltd. All rights reserved.

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Surface models of biomolecules have become crucially important for the study and understanding of interaction between biomolecules and their environment. We argue for the need for a detailed understanding of biomolecular surfaces by describing several applications in computational and structural biology. We review methods used to model, represent, characterize, and visualize biomolecular surfaces focusing on the role that geometry and topology play in identifying features on the surface. These methods enable the development of efficient computational and visualization tools for studying the function of biomolecules.

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For hybrid electric vehicles the batteries and the drive dc-link may be at different voltages. The batteries are at low voltage to obtain higher volumetric efficiencies and the dc-link is at higher voltage to have higher efficiency on the motor side. Therefore a power interface between the batteries and the drive's dc-link is essential. This power interface should handle power flow from battery to motor, motor to battery, external genset to battery and grid to battery. This paper proposes a multi power port topology which is capable of handling multiple power sources and still maintains simplicity and features like obtaining any gain, wide load variations, lower output current ripple and capability of parallel battery energy due to the modular structure. The development and testing of a bi-directional fly-back DC-DC converter for hybrid electric vehicle is described in this paper. Simple hysteresis voltage control is used for DC link voltage regulation. The experimental results are presented to show the working of the proposed converter.

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Conventional three-dimensional isoparametric elements are susceptible to problems of locking when used to model plate/shell geometries or when the meshes are distorted etc. Hybrid elements that are based on a two-field variational formulation are immune to most of these problems, and hence can be used to efficiently model both "chunky" three-dimensional and plate/shell type structures. Thus, only one type of element can be used to model "all" types of structures, and also allows us to use a standard dual algorithm for carrying out the topology optimization of the structure. We also address the issue of manufacturability of the designs.

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The notion of optimization is inherent in protein design. A long linear chain of twenty types of amino acid residues are known to fold to a 3-D conformation that minimizes the combined inter-residue energy interactions. There are two distinct protein design problems, viz. predicting the folded structure from a given sequence of amino acid monomers (folding problem) and determining a sequence for a given folded structure (inverse folding problem). These two problems have much similarity to engineering structural analysis and structural optimization problems respectively. In the folding problem, a protein chain with a given sequence folds to a conformation, called a native state, which has a unique global minimum energy value when compared to all other unfolded conformations. This involves a search in the conformation space. This is somewhat akin to the principle of minimum potential energy that determines the deformed static equilibrium configuration of an elastic structure of given topology, shape, and size that is subjected to certain boundary conditions. In the inverse-folding problem, one has to design a sequence with some objectives (having a specific feature of the folded structure, docking with another protein, etc.) and constraints (sequence being fixed in some portion, a particular composition of amino acid types, etc.) while obtaining a sequence that would fold to the desired conformation satisfying the criteria of folding. This requires a search in the sequence space. This is similar to structural optimization in the design-variable space wherein a certain feature of structural response is optimized subject to some constraints while satisfying the governing static or dynamic equilibrium equations. Based on this similarity, in this work we apply the topology optimization methods to protein design, discuss modeling issues and present some initial results.

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The author presents adaptive control techniques for controlling the flow of real-time jobs from the peripheral processors (PPs) to the central processor (CP) of a distributed system with a star topology. He considers two classes of flow control mechanisms: (1) proportional control, where a certain proportion of the load offered to each PP is sent to the CP, and (2) threshold control, where there is a maximum rate at which each PP can send jobs to the CP. The problem is to obtain good algorithms for dynamically adjusting the control level at each PP in order to prevent overload of the CP, when the load offered by the PPs is unknown and varying. The author formulates the problem approximately as a standard system control problem in which the system has unknown parameters that are subject to change. Using well-known techniques (e.g., naive-feedback-controller and stochastic approximation techniques), he derives adaptive controls for the system control problem. He demonstrates the efficacy of these controls in the original problem by using the control algorithms in simulations of a queuing model of the CP and the load controls.

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The static response of thin, wrinkled membranes is studied using both a tension field approximation based on plane stress conditions and a 3D nonlinear elasticityformulation, discretized through 8-noded Cosserat point elements. While the tension field approach only obtains the wrinkled/slack regions and at best a measure of the extent of wrinkliness, the 3D elasticity solution provides, in principle, the deformed shape of a wrinkled/slack membrane. However, since membranes barely resist compression, the discretized and linearized system equations via both the approaches are ill-conditioned and solutions could thus be sensitive to discretizations errors as well as other sources of noises/imperfections. We propose a regularized, pseudo-dynamical recursion scheme that provides a sequence of updates, which are almost insensitive to theregularizing term as well as the time step size used for integrating the pseudo-dynamical form. This is borne out through several numerical examples wherein the relative performance of the proposed recursion scheme vis-a-vis a regularized Newton strategy is compared. The pseudo-time marching strategy, when implemented using 3D Cosserat point elements, also provides a computationally cheaper, numerically accurate and simpler alternative to that using geometrically exact shell theories for computing large deformations of membranes in the presence of wrinkles. (C) 2010 Elsevier Ltd. All rights reserved.

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The three-phase equilibrium between alloy, spinel solid solution and alpha -Al sub 2 O sub 3 in the Fe--Co--Al--O system at 1873k was fully characterized as a function of alloy composition using both experimental and computational methods. The equilibrium oxygen content of the liquid alloy was measured by suction sampling and inert gas fusion analysis. The O potential corresponding to the three-phase equilibrium was determined by emf measurements on a solid state galvanic cell incorporating (Y sub 2 O sub 3 )ThO sub 2 as the solid electrolyte and Cr + Cr sub 2 O sub 3 as the reference electrode. The equilibrium composition of the spinel phase formed at the interface between the alloy and alumina crucible was measured by electron probe microanalysis (EPMA). The experimental results were compared with the values computed using a thermodynamic model. The model used values for standard Gibbs energies of formation of pure end-member spinels and Gibbs energies of solution of gaseous O in liquid Fe and cobalt available in the literature. The activity--composition relationship in the spinel solid solution was computed using a cation distribution model. The variation of the activity coefficient of O with alloy composition in the Fe--Co--O system was estimated using both the quasichemical model of Jacob and Alcock and Wagner's model along with the correlations of Chiang and Chang and Kuo and Chang. The computed results of spinel composition and O potential are in excellent agreement with the experimental data. Graphs. 29 ref.--AA

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Background:Bacterial non-coding small RNAs (sRNAs) have attracted considerable attention due to their ubiquitous nature and contribution to numerous cellular processes including survival, adaptation and pathogenesis. Existing computational approaches for identifying bacterial sRNAs demonstrate varying levels of success and there remains considerable room for improvement. Methodology/Principal Findings: Here we have proposed a transcriptional signal-based computational method to identify intergenic sRNA transcriptional units (TUs) in completely sequenced bacterial genomes. Our sRNAscanner tool uses position weight matrices derived from experimentally defined E. coli K-12 MG1655 sRNA promoter and rho-independent terminator signals to identify intergenic sRNA TUs through sliding window based genome scans. Analysis of genomes representative of twelve species suggested that sRNAscanner demonstrated equivalent sensitivity to sRNAPredict2, the best performing bioinformatics tool available presently. However, each algorithm yielded substantial numbers of known and uncharacterized hits that were unique to one or the other tool only. sRNAscanner identified 118 novel putative intergenic sRNA genes in Salmonella enterica Typhimurium LT2, none of which were flagged by sRNAPredict2. Candidate sRNA locations were compared with available deep sequencing libraries derived from Hfq-co-immunoprecipitated RNA purified from a second Typhimurium strain (Sittka et al. (2008) PLoS Genetics 4: e1000163). Sixteen potential novel sRNAs computationally predicted and detected in deep sequencing libraries were selected for experimental validation by Northern analysis using total RNA isolated from bacteria grown under eleven different growth conditions. RNA bands of expected sizes were detected in Northern blots for six of the examined candidates. Furthermore, the 5'-ends of these six Northern-supported sRNA candidates were successfully mapped using 5'-RACE analysis. Conclusions/Significance: We have developed, computationally examined and experimentally validated the sRNAscanner algorithm. Data derived from this study has successfully identified six novel S. Typhimurium sRNA genes. In addition, the computational specificity analysis we have undertaken suggests that similar to 40% of sRNAscanner hits with high cumulative sum of scores represent genuine, undiscovered sRNA genes. Collectively, these data strongly support the utility of sRNAscanner and offer a glimpse of its potential to reveal large numbers of sRNA genes that have to date defied identification. sRNAscanner is available from: http://bicmku.in:8081/sRNAscanner or http://cluster.physics.iisc.ernet.in/sRNAscanner/.