Protein contact prediction using patterns of correlation

We describe a new method for using neural networks to predict residue contact pairs in a protein. The main inputs to the neural network are a set of 25 measures of correlated mutation between all pairs of residues in two windows of size 5 centered on the residues of interest. While the individual pair-wise correlations are a relatively weak predictor of contact, by training the network on windows of correlation the accuracy of prediction is significantly improved. The neural network is trained on a set of 100 proteins and then tested on a disjoint set of 1033 proteins of known structure. An average predictive accuracy of 21.7% is obtained taking the best L/2 predictions for each protein, where L is the sequence length. Taking the best L/10 predictions gives an average accuracy of 30.7%. The predictor is also tested on a set of 59 proteins from the CASP5 experiment. The accuracy is found to be relatively consistent across different sequence lengths, but to vary widely according to the secondary structure. Predictive accuracy is also found to improve by using multiple sequence alignments containing many sequences to calculate the correlations. (C) 2004 Wiley-Liss, Inc.

Recurring contact opportunities within groups of devices

The capability to anticipate a contact with another device can greatly improve the performance and user satisfaction not only of mobile social network applications but of any other relying on some form of data harvesting or hoarding. One of the most promising approaches for contact prediction is to extrapolate from past experiences. This paper investigates the recurring contact patterns observed between groups of devices using an 8-year dataset of wireless access logs produced by more than 70000 devices. This effort permitted to model the probabilities of occurrence of a contact at a predefined date between groups of devices using a power law distribution that varies according to neighbourhood size and recurrence period. In the general case, the model can be used by applications that need to disseminate large datasets by groups of devices. As an example, the paper presents and evaluates an algorithm that provides daily contact predictions, based on the history of past pairwise contacts and their duration. Copyright © 2015 ICST.

Better prediction of protein contact number using a support vector regression analysis of amino acid sequence

Background: Protein tertiary structure can be partly characterized via each amino acid's contact number measuring how residues are spatially arranged. The contact number of a residue in a folded protein is a measure of its exposure to the local environment, and is defined as the number of C-beta atoms in other residues within a sphere around the C-beta atom of the residue of interest. Contact number is partly conserved between protein folds and thus is useful for protein fold and structure prediction. In turn, each residue's contact number can be partially predicted from primary amino acid sequence, assisting tertiary fold analysis from sequence data. In this study, we provide a more accurate contact number prediction method from protein primary sequence. Results: We predict contact number from protein sequence using a novel support vector regression algorithm. Using protein local sequences with multiple sequence alignments (PSI-BLAST profiles), we demonstrate a correlation coefficient between predicted and observed contact numbers of 0.70, which outperforms previously achieved accuracies. Including additional information about sequence weight and amino acid composition further improves prediction accuracies significantly with the correlation coefficient reaching 0.73. If residues are classified as being either contacted or non-contacted, the prediction accuracies are all greater than 77%, regardless of the choice of classification thresholds. Conclusion: The successful application of support vector regression to the prediction of protein contact number reported here, together with previous applications of this approach to the prediction of protein accessible surface area and B-factor profile, suggests that a support vector regression approach may be very useful for determining the structure-function relation between primary sequence and higher order consecutive protein structural and functional properties.

Using customer lifetime value to improve the prediction of bank deposit subscription in telemarketing campaigns

Customer lifetime value (LTV) enables using client characteristics, such as recency, frequency and monetary (RFM) value, to describe the value of a client through time in terms of profitability. We present the concept of LTV applied to telemarketing for improving the return-on-investment, using a recent (from 2008 to 2013) and real case study of bank campaigns to sell long- term deposits. The goal was to benefit from past contacts history to extract additional knowledge. A total of twelve LTV input variables were tested, un- der a forward selection method and using a realistic rolling windows scheme, highlighting the validity of five new LTV features. The results achieved by our LTV data-driven approach using neural networks allowed an improvement up to 4 pp in the Lift cumulative curve for targeting the deposit subscribers when compared with a baseline model (with no history data). Explanatory knowledge was also extracted from the proposed model, revealing two highly relevant LTV features, the last result of the previous campaign to sell the same product and the frequency of past client successes. The obtained results are particularly valuable for contact center companies, which can improve pre- dictive performance without even having to ask for more information to the companies they serve.

Contact force models for multibody dynamics

"Series: Solid mechanics and its applications, vol. 226"

Habitat selection in zones of parapatric contact between the Common shrew Sorex araneus and Millet's shrew S. coronatus

(1) The common shrew Sorex araneus and Millet's shrew S. coronatus are sibling species.They are morphologically and genetically very similar but do not hybridize. Their parapatric distribution throughout south-western Europe, with a few narrow zones of distributional overlap, suggests that they are in competitive parapatry. (2) Two of these contact zones were studied; there was evidence of coexistence over periods of 2 years as well as habitat segregation. In both zones, the species segregated on litter thickness and humidity variables. (3) A simple analysis of spatial distribution showed that habitats visible in the field corresponded to the habitats selected by the species. Habitat selection was found throughout the annual life-cycle of the shrews. (4) In one contact zone, a removal experiment was performed to test whether habitat segregation is induced by interspecific interactions. The experiment showed that the species select habitats differentially when both are present and abandon habitat selection when their competitor is removed. (5) These results confirm the role of resource partitioning in promoting narrow rangesof distributional overlap between such parapatric species and qualitatively support the prediction of habitat selection theory that, in a two-species system, coexistence may be achieved by differential habitat selection to avoid competition. The results also support the view that the common shrew and Millet's shrew are in competitive parapatry.

Habitat selection in zones of parapatric contact between the common shrew Sorex araneaus and Millet's shrew S. coronatus

(1) The common shrew Sorex araneus and Millet's shrew S. coronatusare sibling species.They are morphologically and genetically very similar but do not hybridize.Their parapatric distribution throughout south-western Europe, with a few narrow zones of distributional overlap, suggests that they are in competitive parapatry. (2) Two of these contact zones were studied; there was evidence of coexistence over periods of 2 years as well as habitat segregation. In both zones, the species segregated on litter thickness and humidity variables. (3) A simple analysis of spatial distribution showed that habitats visible in the field corresponded to the habitats selected by the species. Habitat selection was found throughout the annual life-cycle of the shrews. (4) In one contact zone, a removal experiment was performed to test whether habitat segregation is induced by interspecific interactions. The experiment showed that the species select habitats differentially when both are present and abandon habitat selection when their competitor removed. (5)These results confirm the role of resource partitioning in promoting narrow ranges of distributional overlap between such parapatric species and qualitatively support the prediction of habitat selection theory that, in a two-species system, coexistence may be achieved by differential habitat selection to avoid competition. The results also support the view that the common shrew and Millet's shrew are in competitive parapatry.

Hierarchical Prediction Machines and Big Data Analytics

An emerging consensus in cognitive science views the biological brain as a hierarchically-organized predictive processing system. This is a system in which higher-order regions are continuously attempting to predict the activity of lower-order regions at a variety of (increasingly abstract) spatial and temporal scales. The brain is thus revealed as a hierarchical prediction machine that is constantly engaged in the effort to predict the flow of information originating from the sensory surfaces. Such a view seems to afford a great deal of explanatory leverage when it comes to a broad swathe of seemingly disparate psychological phenomena (e.g., learning, memory, perception, action, emotion, planning, reason, imagination, and conscious experience). In the most positive case, the predictive processing story seems to provide our first glimpse at what a unified (computationally-tractable and neurobiological plausible) account of human psychology might look like. This obviously marks out one reason why such models should be the focus of current empirical and theoretical attention. Another reason, however, is rooted in the potential of such models to advance the current state-of-the-art in machine intelligence and machine learning. Interestingly, the vision of the brain as a hierarchical prediction machine is one that establishes contact with work that goes under the heading of 'deep learning'. Deep learning systems thus often attempt to make use of predictive processing schemes and (increasingly abstract) generative models as a means of supporting the analysis of large data sets. But are such computational systems sufficient (by themselves) to provide a route to general human-level analytic capabilities? I will argue that they are not and that closer attention to a broader range of forces and factors (many of which are not confined to the neural realm) may be required to understand what it is that gives human cognition its distinctive (and largely unique) flavour. The vision that emerges is one of 'homomimetic deep learning systems', systems that situate a hierarchically-organized predictive processing core within a larger nexus of developmental, behavioural, symbolic, technological and social influences. Relative to that vision, I suggest that we should see the Web as a form of 'cognitive ecology', one that is as much involved with the transformation of machine intelligence as it is with the progressive reshaping of our own cognitive capabilities.

Four-fermion contact interactions at one-loop and the new atomic parity violation results.

We investigate the possibility that four-fermion contact interactions give rise to the observed deviation from the Standard Model prediction for the weak charge of cesium, through one-loop contributions. We show that the presence of loops involving the third generation quarks can explain such deviation.

Can four-fermion contact interactions at one-loop explain the new atomic parity violation results?

We investigate the possibility that four-fermion contact interactions give rise to the observed deviation from the standard model prediction for the weak charge of cesium, through one-loop contributions. We show that the presence of loops involving the third generation quarks can explain such a deviation.

Search for contact interactions using the inclusive jet pT spectrum in pp collisions at √s=7 TeV

Results are reported of a search for a deviation in the jet production cross section from the prediction of perturbative quantum chromodynamics at next-to-leading order. The search is conducted using a 7 TeV proton-proton data sample corresponding to an integrated luminosity of 5.0 fb-1, collected with the Compact Muon Solenoid detector at the Large Hadron Collider. A deviation could arise from interactions characterized by a mass scale Λ too high to be probed directly at the LHC. Such phenomena can be modeled as contact interactions. No evidence of a deviation is found. Using the CL s criterion, lower limits are set on Λ of 9.9 TeV and 14.3 TeV at 95% confidence level for models with destructive and constructive interference, respectively. Limits obtained with a Bayesian method are also reported. © 2013 CERN.

Prediction of spatial orientation and morphology of calcaneonavicular coalitions

BACKGROUND: Calcaneonavicular coalitions (CNC) have been reported to be associated with anatomical aberrations of either the calcaneus and/or navicular bones. These morphological abnormalities may complicate accurate surgical resection. Three-dimensional analysis of spatial orientation and morphological characteristics may help in preoperative planning of resection. MATERIALS AND METHODS: Sixteen feet with a diagnosis of CNC were evaluated by means of 3-D CT modeling. Three angles were defined that were expressed in relation to one reproducible landmark (lateral border of the calcaneus): the dorsoplantar inclination, anteroposterior inclination, and socket angle. The depth and width of the coalitions were measured and calculated to obtain the estimated contact surface. Three-dimensional reconstructions of the calcanei served to evaluate the presence, distortion or absence of the anterior calcaneal facet and presence of a navicular beak. The interrater correlations were assessed in order to obtain values for the accuracy of the measurement methods. Sixteen normal feet were used as controls for comparison of the socket angle; anatomy of the anterior calcaneal facet and navicular beak as well. RESULTS: The dorsoplantar inclination angle averaged 50 degrees (+/-17), the anteroposterior inclination angle 64 degrees (+/-15), and the pathologic socket angle 98 degrees (+/-11). The average contact area was 156 mm(2). Ninety-four percent of all patients in the CNC group revealed a plantar navicular beak. In 50% of those patients the anterior calcaneal facet was replaced by the navicular portion and in 44% the facet was totally missing. In contrast, the socket angle in the control group averaged 77 degrees (+/-18), which was found to be statistically different than the CNC group (p = 0.0004). Only 25% of the patients in the control group had a plantar navicular beak. High, statistically significant interrater correlations were found for all measured angles. CONCLUSION: Computer-aided CT analysis and reconstructions help to determine the spatial orientations of CNC in space and provide useful information in order to anticipate morphological abnormalities of the calcaneus and navicular.

Prediction of bendig load capacity of timber beams by finite element method simulation of knots and grain deviation

A finite element model was used to simulate timberbeams with defects and predict their maximum load in bending. Taking into account the elastoplastic constitutive law of timber, the prediction of fracture load gives information about the mechanisms of timber failure, particularly with regard to the influence of knots, and their local graindeviation, on the fracture. A finite element model was constructed using the ANSYS element Plane42 in a plane stress 2D-analysis, which equates thickness to the width of the section to create a mesh which is as uniform as possible. Three sub-models reproduced the bending test according to UNE EN 408: i) timber with holes caused by knots; ii) timber with adherent knots which have structural continuity with the rest of the beam material; iii) timber with knots but with only partial contact between knot and beam which was artificially simulated by means of contact springs between the two materials. The model was validated using ten 45 × 145 × 3000 mm beams of Pinus sylvestris L. which presented knots and graindeviation. The fracture stress data obtained was compared with the results of numerical simulations, resulting in an adjustment error less of than 9.7%

Constructing and evaluating alternative prediction models for identifying clinically relevant cases in an STD clinic

Thesis (Master's)--University of Washington, 2016-06