Using Correlated Parameters for Improved Ranking of Protein-Protein Docking Decoys

A successful protein-protein docking study culminates in identification of decoys at top ranks with near-native quaternary structures. However, this task remains enigmatic because no generalized scoring functions exist that effectively infer decoys according to the similarity to near-native quaternary structures. Difficulties arise because of the highly irregular nature of the protein surface and the significant variation of the nonbonding and solvation energies based on the chemical composition of the protein-protein interface. In this work, we describe a novel method combining an interface-size filter, a regression model for geometric compatibility (based on two correlated surface and packing parameters), and normalized interaction energy (calculated from correlated nonbonded and solvation energies), to effectively rank decoys from a set of 10,000 decoys. Tests on 30 unbound binary protein-protein complexes show that in 16 cases we can identify at least one decoy in top three ranks having <= 10 angstrom backbone root mean square deviation from true binding geometry. Comparisons with other state-of-art methods confirm the improved ranking power of our method without the use of any experiment-guided restraints, evolutionary information, statistical propensities, or modified interaction energy equations. Tests on 118 less-difficult bound binary protein-protein complexes with <= 35% sequence redundancy at the interface showed that in 77% cases, at least 1 in 10,000 decoys were identified with <= 5 angstrom backbone root mean square deviation from true geometry at first rank. The work will promote the use of new concepts where correlations among parameters provide more robust scoring models. It will facilitate studies involving molecular interactions, including modeling of large macromolecular assemblies and protein structure prediction. (C) 2010 Wiley Periodicals, Inc. J Comput Chem 32: 787-796, 2011.

Semi-Supervised Classification Using Sparse Gaussian Process Regression

Gaussian Processes (GPs) are promising Bayesian methods for classification and regression problems. They have also been used for semi-supervised learning tasks. In this paper, we propose a new algorithm for solving semi-supervised binary classification problem using sparse GP regression (GPR) models. It is closely related to semi-supervised learning based on support vector regression (SVR) and maximum margin clustering. The proposed algorithm is simple and easy to implement. It gives a sparse solution directly unlike the SVR based algorithm. Also, the hyperparameters are estimated easily without resorting to expensive cross-validation technique. Use of sparse GPR model helps in making the proposed algorithm scalable. Preliminary results on synthetic and real-world data sets demonstrate the efficacy of the new algorithm.

Surface tension of some binary organic solutions of alkylbenzenes and 1-alkanols

The surface tensions of binary mixtures of 1-alkanols (Cl-Cd with benzene, toluene, or xylene were measured. The results were correlated with the activity coefficients calculated through the group contribution method such as UNIFAC, with the maximum deviation from the experimental results less that 5%. The coefficients of the correlation are correlated with the chain length.

Symmetry adaptation of correlated states in the valence bond basis

Symmetry?adapted linear combinations of valence?bond (VB) diagrams are constructed for arbitrary point groups and total spin S using diagrammatic VB methods. VB diagrams are related uniquely to invariant subspaces whose size reflects the number of group elements; their nonorthogonality leads to sparser matrices and is fully incorporated into a binary integer representation. Symmetry?adapated linear combinations of VB diagrams are constructed for the 1764 singlets of a half?filled cube of eight sites, the 2.8 million ??electron singlets of anthracene, and for illustrative S?0 systems.

Distributed intrusion detection in the presence of correlated sensor readings: Signal-space and communication-complexity view-point

The problem of sensor-network-based distributed intrusion detection in the presence of clutter is considered. It is argued that sensing is best regarded as a local phenomenon in that only sensors in the immediate vicinity of an intruder are triggered. In such a setting, lack of knowledge of intruder location gives rise to correlated sensor readings. A signal-space view-point is introduced in which the noise-free sensor readings associated to intruder and clutter appear as surfaces f(s) and f(g) and the problem reduces to one of determining in distributed fashion, whether the current noisy sensor reading is best classified as intruder or clutter. Two approaches to distributed detection are pursued. In the first, a decision surface separating f(s) and f(g) is identified using Neyman-Pearson criteria. Thereafter, the individual sensor nodes interactively exchange bits to determine whether the sensor readings are on one side or the other of the decision surface. Bounds on the number of bits needed to be exchanged are derived, based on communication-complexity (CC) theory. A lower bound derived for the two-party average case CC of general functions is compared against the performance of a greedy algorithm. Extensions to the multi-party case is straightforward and is briefly discussed. The average case CC of the relevant greaterthan (CT) function is characterized within two bits. Under the second approach, each sensor node broadcasts a single bit arising from appropriate two-level quantization of its own sensor reading, keeping in mind the fusion rule to be subsequently applied at a local fusion center. The optimality of a threshold test as a quantization rule is proved under simplifying assumptions. Finally, results from a QualNet simulation of the algorithms are presented that include intruder tracking using a naive polynomial-regression algorithm. 2010 Elsevier B.V. All rights reserved.

Flux Partitioning of Species Approach in Binary Interdiffusion Process

Validation of the flux partitioning of species model has been illustrated. Various combinations of inequality expression for the fluxes of species A and B in two successively grown hypothetical intermetallic phases in the interdiffusion zone have been considered within the constraints of this concept. Furthermore, ratio of intrinsic diffusivities of the species A and B in those two phases has been correlated in four different cases. Moreover, complete and or partial validation or invalidation of this model with respect to both the species, has been proven theoretically and also discussed with the Co-Si system as an example.

Microstructural and mechanical behavior study of suction cast Nb-Si binary alloys

The solidification pathways of Nb rich Nb-Si alloys when processed under non-equilibrium conditions require understanding. Continuing with our earlier work on alloying additions in single eutectic composition 1,2], we report a detailed characterization of the microstructures of Nb-Si binary alloys with wide composition range (10-25 at% Si). The alloys are processed using chilled copper mould suction casting. This has allowed us to correlate the evolution of microstructure and phases with different possible solidification pathways. Finally these are correlated with mechanical properties through studies on deformation using mechanical testing under indentation and compressive loads. It is shown that microstructure modification can significantly influence the plasticity of these alloys.

Properties of the correlated electronic states of pyrene and hydrogenated pyrene

Approximate calculations are reported on pyrene within the PPP model Hamiltonian using a novel restricted CI scheme which employs both molecular orbital and valence bond techniques. Also reported are detailed full CI results of the PPP model on 2,7-dihydropyrene obtained using the valence bond method. Spectral studies, charge and spin density calculations in ground and excited states, and ring current calculations in the ground state of the molecules are presented. In pyrene, the calculated excitation energies are in good agreement with experiment. The closed structure pi-conjugated molecule pyrene appears to show smaller distortions from the ground state geometry compared with the open structure pi-conjugated molecule 2,7-dihydropyrene. The ground state equilibrium structure of 2,7-dihydropyrene can be viewed as two hexatriene molecules connected by a vinyl crosslink, as is evident from bond order and ring current calculations. This is consistent with the only Kekule resonant structure possible for this molecule.

Non-linear regression model for spatial variation in precipitation chemistry for South India

Chemical composition of rainwater changes from sea to inland under the influence of several major factors - topographic location of area, its distance from sea, annual rainfall. A model is developed here to quantify the variation in precipitation chemistry under the influence of inland distance and rainfall amount. Various sites in India categorized as 'urban', 'suburban' and 'rural' have been considered for model development. pH, HCO3, NO3 and Mg do not change much from coast to inland while, SO4 and Ca change is subjected to local emissions. Cl and Na originate solely from sea salinity and are the chemistry parameters in the model. Non-linear multiple regressions performed for the various categories revealed that both rainfall amount and precipitation chemistry obeyed a power law reduction with distance from sea. Cl and Na decrease rapidly for the first 100 km distance from sea, then decrease marginally for the next 100 km, and later stabilize. Regression parameters estimated for different cases were found to be consistent (R-2 similar to 0.8). Variation in one of the parameters accounted for urbanization. Model was validated using data points from the southern peninsular region of the country. Estimates are found to be within 99.9% confidence interval. Finally, this relationship between the three parameters - rainfall amount, coastline distance, and concentration (in terms of Cl and Na) was validated with experiments conducted in a small experimental watershed in the south-west India. Chemistry estimated using the model was in good correlation with observed values with a relative error of similar to 5%. Monthly variation in the chemistry is predicted from a downscaling model and then compared with the observed data. Hence, the model developed for rain chemistry is useful in estimating the concentrations at different spatio-temporal scales and is especially applicable for south-west region of India. (C) 2008 Elsevier Ltd. All rights reserved.

Different phenomenological theories and their abilities to describe the interdiffusion process in a binary system during multiphase growth

There are essentially two different phenomenological models available to describe the interdiffusion process in binary systems in the olid state. The first of these, which is used more frequently, is based on the theory of flux partitioning. The second model, developed much more recently, uses the theory of dissociation and reaction. Although the theory of flux partitioning has been widely used, we found that this theory does not account for the mobility of both species and therefore is not suitable for use in most interdiffusion systems. We have first modified this theory to take into account the mobility of both species and then further extended it to develop relations or the integrated diffusion coefficient and the ratio of diffusivities of the species. The versatility of these two different models is examined in the Co-Si system with respect to different end-member compositions. From our analysis, we found that the applicability of the theory of flux partitioning is rather limited but the theory of dissociation and reaction can be used in any binary system.

Impedance-fatigue correlated studies on SrBi2Ta2O9

Ceramic samples of SrBi2Ta2O9 (SBT) were prepared by the solid state reaction method with a view to study their electrical properties. Reasons as to why SBT shows better fatigue endurance than conventional perovskites like Pb(Zr, Ti)O-3 are looked into. Complex impedance spectroscopy (CIS) was used as a tool to do so. CIS data was acquired over the temperature range from room temperature to 500 degrees C over a wide range of frequencies. Electrical conductivity data indicates that the conductivity in SBT is essentially due to oxygen vacancies and the activation energy for conduction in the high temperature region was found to be 0.95 eV. CIS was used to separate out the bulk and the interfacial contributions to complex impedance.

Massive black-hole binary inspirals: results from the LISA parameter estimation taskforce

The LISA Parameter Estimation Taskforce was formed in September 2007 to provide the LISA Project with vetted codes, source distribution models and results related to parameter estimation. The Taskforce's goal is to be able to quickly calculate the impact of any mission design changes on LISA's science capabilities, based on reasonable estimates of the distribution of astrophysical sources in the universe. This paper describes our Taskforce's work on massive black-hole binaries (MBHBs). Given present uncertainties in the formation history of MBHBs, we adopt four different population models, based on (i) whether the initial black-hole seeds are small or large and (ii) whether accretion is efficient or inefficient at spinning up the holes. We compare four largely independent codes for calculating LISA's parameter-estimation capabilities. All codes are based on the Fisher-matrix approximation, but in the past they used somewhat different signal models, source parametrizations and noise curves. We show that once these differences are removed, the four codes give results in extremely close agreement with each other. Using a code that includes both spin precession and higher harmonics in the gravitational-wave signal, we carry out Monte Carlo simulations and determine the number of events that can be detected and accurately localized in our four population models.

Electron Mean Energy, Secondary Ionization Coefficients And (E/P)Crit In Binary-Mixtures Of Sf6-N2 And Ccl2f2-N2

Measurements of the ratio of diffusion coefficient to mobility (D/ mu ) of electrons in SF6-N2 and CCl2F2-N2 mixtures over the range 80

Ionisation and attachment in binary mixtures of SF6-N2 and CCl2F2-N2

Experimental results are presented of ionisation (a)a nd electron attachment ( v ) coefficients evaluated from the steady-state Townsend curregnrto wth curves for SFsN2 and CC12FrN2 mixtures over the range 60 S E/P 6 240 (where E is the electric field in V cm" and P is the pressure in Torr reduced to 20'C). In both the mixtures the attachment coefficients (vmu) evaluated were found to follow the relationship; where 7 is the attachment coefficient of pure electronegative gas, F is the fraction of the electronegative gas in the mixture and /3 is a constant. The ionisation coefficients (amlx) generally obeyed the relationship where w2a nd aAa re thei onisation coefficients of nitrogen and the attachinggraess pectively. However, in case of CC12FrN2 mixtures, there were maxima in the a,,,v,a,l ues for CCI2F2 concentrations varying between 10% and 30% at all values of E/P investigated. Effective ionisation coefficients (a - p)/P obtained in these binary mixtures show that the critical E/P (corresponding to (a - q)/P = 0) increases with increase in the concentration of the electronegative gas up to 40%. Further increase in the electronegative gas content does not seem to alter the critical E/P.

Numerical studies on columnar-to-equiaxed transition in directional solidification of binary alloys

A numerical study on columnar-to-equiaxed transition (CET) during directional solidification of binary alloys is presented using a macroscopic solidification model. The position of CET is predicted numerically using a critical cooling rate criterion reported in literature. The macroscopic solidification model takes into account movement of solid phase due to buoyancy, and drag effect on the moving solid phase because of fluid motion. The model is applied to simulate the solidification process for binary alloys (Sn-Pb) and to estimate solidification parameters such as position of the liquidus, velocity of the liquidus isotherm, temperature gradient ahead of the liquidus, and cooling rate at the liquidus. Solidification phenomena under two cooling configurations are studied: one without melt convection and the other involvin thermosolutal convection. The numerically predicted positions of CET compare well with those of experiments reported in literature. Melt convection results in higher cooling rate, higher liquidus isotherm velocities, and stimulation of occurrence of CET in comparison to the nonconvecting case. The movement of solid phase aids further the process of CET. With a fixed solid phase, the occurrence of CET based on the same critical cooling rate is delayed and it occurs at a greater distance from the chill.