A fold-recognition approach to loop modeling

A novel approach is proposed for modeling loop regions in proteins. In this approach, a prerequisite sequence-structure alignment is examined for regions where the target sequence is not covered by the structural template. These regions, extended with a number of residues from adjacent stem regions, are submitted to fold recognition. The alignments produced by fold recognition are integrated into the initial alignment to create an alignment between the target sequence and several structures, where gaps in the main structural template are covered by local structural templates. This one-to-many (1:N) alignment is used to create a protein model by existing protein-modeling techniques. Several alternative approaches were evaluated using a set of ten proteins. One approach was selected and evaluated using another set of 31 proteins. The most promising result was for gap regions not located at the C-terminus or N-terminus of a protein, where the method produced an average RMSD 12% lower than the loop modeling provided with the program MODELLER. This improvement is shown to be statistically significant. Figure The method derived from the training set applied to CASP target T0191     

A triple-isotope approach to predict the breeding origins of European bats

Despite a commitment by the European Union to protect its migratory bat populations, conservation efforts are hindered by a poor understanding of bat migratory strategies and connectivity between breeding and wintering grounds. Traditional methods like mark-recapture are ineffective to study broad-scale bat migratory patterns. Stable hydrogen isotopes (δD) have been proven useful in establishing spatial migratory connectivity of animal populations. Before applying this tool, the method was calibrated using bat samples of known origin. Here we established the potential of δD as a robust geographical tracer of breeding origins of European bats by measuring δD in hair of five sedentary bat species from 45 locations throughout Europe. The δD of bat hair strongly correlated with well-established spatial isotopic patterns in mean annual precipitation in Europe, and therefore was highly correlated with latitude. We calculated a linear mixed-effects model, with species as random effect, linking δD of bat hair to precipitation δD of the areas of hair growth. This model can be used to predict breeding origins of European migrating bats. We used δ(13)C and δ(15)N to discriminate among potential origins of bats, and found that these isotopes can be used as variables to further refine origin predictions. A triple-isotope approach could thereby pinpoint populations or subpopulations that have distinct origins. Our results further corroborated stable isotope analysis as a powerful method to delineate animal migrations in Europe.     

Noseleaf dynamics during pulse emission in horseshoe bats

Horseshoe bats emit their biosonar pulses nasally and diffract the outgoing ultrasonic waves by conspicuous structures that surrounded the nostrils. Here, we report quantitative experimental data on the motion of a prominent component of these structures, the anterior leaf, using synchronized laser Doppler vibrometry and acoustic recordings in the greater horseshoe bat (Rhinolophus ferrumequinum). The vibrometry data has demonstrated non-random motion patterns in the anterior leaf. In these patterns, the outer rim of the walls of the anterior leaf twitches forward and inwards to decrease the aperture of the noseleaf and increase the curvature of its surfaces. Noseleaf displacements were correlated with the emitted ultrasonic pulses. After their onset, the inward displacements increased monotonically towards their maximum value which was always reached within the duration of the biosonar pulse, typically towards its end. In other words, the anterior leaf's surfaces were moving inwards during most of the pulse. Non-random motions were not present in all recorded pulse trains, but could apparently be switched on or off. Such switches happened between sequences of consecutive pulses but were never observed between individual pulses within a sequence. The amplitudes of the emitted biosonar pulse and accompanying noseleaf movement were not correlated in the analyzed data set. The measured velocities of the noseleaf surface were too small to induce Doppler shifts of a magnitude with a likely significance. However, the displacement amplitudes were significant in comparison with the overall size of the anterior leaf and the sound wavelengths. These results indicate the possibility that horseshoe bats use dynamic sensing principles on the emission side of their biosonar system. Given the already available evidence that such mechanisms exist for biosonar reception, it may be hypothesized that time-variant mechanisms play a pervasive role in the biosonar sensing of horseshoe bats.     

A multilevel approach to cancer growth modeling

Cancer growth models may be divided into macroscopic models, which describe the tumor as a single entity, and microscopic ones, which consider the tumor as a complex system whose behavior emerges from the local dynamics of its basic components, the neoplastic cells. Mesoscopic models (e.g. as based on the Local Interaction Simulation Approach [Delsanto, P.P., Mignogna, R., Scalerandi, M., Schechter, R., 1998. In: Delsanto, P.P. Saenz, A.W. (Eds.), New Perspectives on Problems in Classical and Quantum Physics, vol. 2. Gordon & Breach, New Delhi, p. 5174]), which explicitly consider the behavior of cell clusters and their interactions, may be used instead of the microscopic ones, in order to study the properties of cancer biology that strongly depend on the interactions of small groups of cells at intermediate spatial and temporal scales. All these approaches have been developed independently, which limits their usefulness, since they all include relevant features and information that should be cross-correlated for a deeper understanding of the mechanisms involved. In this contribution we consider multicellular tumor spheroids as biological reference systems and propose an intermediate model to bridge the gap between a macroscopic formulation of tumor growth and a mesoscopic one. Thus we are able to establish, as an important result of our formalism, a direct correspondence between parameters characterizing processes occurring at different scales. In particular, we analyze their dependence on an important limiting factor to tumor growth, i.e. the extra-cellular matrix pressure. Since the macro and meso-models stem from totally different roots (energy conservation and clinical observations vs. cell groups dynamics), their consistency may be used to validate both approaches. It may also be interesting to note that the proposed formalism fits well into a recently proposed conjecture of growth laws universality.     

A simplified approach to quasi-linear viscoelastic modeling

The fitting of quasi-linear viscoelastic (QLV) constitutive models to material data often involves somewhat cumbersome numerical convolution. A new approach to treating quasi-linearity in 1-D is described and applied to characterize the behavior of reconstituted collagen. This approach is based on a new principle for including nonlinearity and requires considerably less computation than other comparable models for both model calibration and response prediction, especially for smoothly applied stretching. Additionally, the approach allows relaxation to adapt with the strain history. The modeling approach is demonstrated through tests on pure reconstituted collagen. Sequences of "ramp-and-hold" stretching tests were applied to rectangular collagen specimens. The relaxation force data from the "hold" was used to calibrate a new "adaptive QLV model" and several models from literature, and the force data from the "ramp" was used to check the accuracy of model predictions. Additionally, the ability of the models to predict the force response on a reloading of the specimen was assessed. The "adaptive QLV model" based on this new approach predicts collagen behavior comparably to or better than existing models, with much less computation.     

Thermodynamic approach to explain cell adhesion to air-medium interfaces

Cell damage has been observed in suspension cell cultures with air sparging, especially in the absence of any protective additives. This damage is associated with cells adhering to bubbles, and it has been shown that if this adhesion is prevented, cell damage is prevented. This article presents a thermodynamic approach for predicting cell adhesion at the air-medium interface. With this relationship it can be shown that cell-gas adhesion can be prevented by lowering the surface tension of the liquid growth medium through the addition of surface-active protective additives. The thermodynamic relationship describes the change in free energy as a function of the interfacial tensions between the (i) gas and liquid phases, (ii) gas and cell phases, and (iii) liquid and cell phases. Experimental data, along with theoretical and empirical equations, are used to quantify the changes in free energy that predict the process of cell-gas adhesion. The thermodynamic model is nonspecific in nature and, consequently, results are equally valid for all types of cells. (c) 1995 John Wiley & Sons, Inc.     

A practical sampling design for acoustic surveys of bats

Acoustic surveys are widely used for describing bat occurrence and activity patterns and are increasingly important for addressing concerns for habitat management, wind energy, and disease on bat populations. Designing these surveys presents unique challenges, particularly when a probabilistic sample is required for drawing inference to unsampled areas. Sampling frame errors and other logistical constraints often require survey sites to be dropped from the sample and new sites added. Maintaining spatial balance and representativeness of the sample when these changes are made can be problematic. Spatially balanced sampling designs recently developed to support aquatic surveys along rivers provide solutions to a number of practical challenges faced by bat researchers and allow for sample site additions and deletions, support unequal-probability selection of sites, and provide an approximately unbiased local neighborhood-weighted variance estimator that is efficient for spatially structured populations such as is typical for bats. We implemented a spatially balanced design to survey canyon bat (Parastrellus hesperus) activity along a stream network. The spatially balanced design accommodated typical logistical challenges and yielded a 25% smaller estimated standard error for the mean activity level than the usual simple random sampling estimator. Spatially balanced designs have broad application to bat research and monitoring programs and will improve studies relying on model-based inference (e.g., occupancy models) by providing flexibility and protection against violations of the independence assumption, even if design-based estimators are not used. Our approach is scalable and can be used for pre- and post-construction surveys along wind turbine arrays and for regional monitoring programs. © 2011 The Wildlife Society.     

A survival analysis approach to modeling human fecundity

Understanding conception probabilities is important not only for helping couples to achieve pregnancy but also in identifying acute or chronic reproductive toxicants that affect the highly timed and interrelated processes underlying hormonal profiles, ovulation, libido, and conception during menstrual cycles. Currently, 2 statistical approaches are available for estimating conception probabilities depending upon the research question and extent of data collection during the menstrual cycle: a survival approach when interested in modeling time-to-pregnancy (TTP) in relation to women or couples' purported exposure(s), or a hierarchical Bayesian approach when one is interested in modeling day-specific conception probabilities during the estimated fertile window. We propose a biologically valid discrete survival model that unifies the above 2 approaches while relaxing some assumptions that may not be consistent with human reproduction or behavior. This approach combines both the survival and the hierarchical models allowing investigators to obtain the distribution of TTP and day-specific probabilities during the fertile window in a single model. Our model allows for the consideration of covariate effects at both the cycle and the daily level while accounting for daily variation in conception. We conduct extensive simulations and utilize the New York State Angler Prospective Pregnancy Cohort Study to illustrate our approach. We also provide the code to implement the model in R software in the supplemental section of the supplementary material available at Biostatistics online.     

A self-consistent knowledge-based approach to protein design

A simple and very efficient protein design strategy is proposed by developing some recently introduced theoretical tools which have been successfully applied to exactly solvable protein models. The design approach is implemented by using three amino acid classes and it is based on the minimization of an appropriate energy function. For a given native state the results of the design procedure are compared, through a statistical analysis, with the properties of an ensemble of sequences folding in the same conformation. If the success rate is computed on those sites designed with high confidence, it can be as high as 80%. The method is also able to identify key sites for the folding process: results for 2ci2 and barnase are in very good agreement with experimental results.     

A thermodynamic approach to PCR primer design

We developed a primer design method, Pythia, in which state of the art DNA binding affinity computations are directly integrated into the primer design process. We use chemical reaction equilibrium analysis to integrate multiple binding energy calculations into a conservative measure of polymerase chain reaction (PCR) efficiency, and a precomputed index on genomic sequences to evaluate primer specificity. We show that Pythia can design primers with success rates comparable with those of current methods, but yields much higher coverage in difficult genomic regions. For example, in RepeatMasked sequences in the human genome, Pythia achieved a median coverage of 89% as compared with a median coverage of 51% for Primer3. For parameter settings yielding sensitivities of 81%, our method has a recall of 97%, compared with the Primer3 recall of 48%. Because our primer design approach is based on the chemistry of DNA interactions, it has fewer and more physically meaningful parameters than current methods, and is therefore easier to adjust to specific experimental requirements. Our software is freely available at http://pythia.sourceforge.net.     

A Bayesian approach to modeling associations between pulsatile hormones

Summary .  Many hormones are secreted in pulses. The pulsatile relationship between hormones regulates many biological processes. To understand endocrine system regulation, time series of hormone concentrations are collected. The goal is to characterize pulsatile patterns and associations between hormones. Currently each hormone on each subject is fitted univariately. This leads to estimates of the number of pulses and estimates of the amount of hormone secreted; however, when the signal-to-noise ratio is small, pulse detection and parameter estimation remains difficult with existing approaches. In this article, we present a bivariate deconvolution model of pulsatile hormone data focusing on incorporating pulsatile associations. Through simulation, we exhibit that using the underlying pulsatile association between two hormones improves the estimation of the number of pulses and the other parameters defining each hormone. We develop the one-to-one, driver–response case and show how birth–death Markov chain Monte Carlo can be used for estimation. We exhibit these features through a simulation study and apply the method to luteinizing and follicle stimulating hormones.     

A niche-based modeling approach to phytoplankton community assembly rules

Six niche-based models proposed by Tokeshi, based on different assumptions of resource allocation by species, were fitted on phytoplankton relative abundance distributions, and potential environmental and biotic factors supporting the applicability of the fitted models were discussed. Overall 16 assemblages corresponding to different sampling times, various environmental conditions, and resource regimes within a year were fitted to the models. Phytoplankton biovolume was used as a measure of abundance, and a randomization test was applied to compare the model fit to the field data. The majority of the phytoplankton assemblages (11 of 16) were successfully described by the Random Fraction model, which is based on the theoretical assumption that resource is apportioned by the species in a random way. Only a few assemblages (three of 16), characterized by extremes in resource availability or disturbance, were not fitted by any of the models. The Random Fraction model in particular was rejected due to a steep slope during the first ranks, while the rest of the distribution remained relatively even, providing further evidence of resilience in phytoplankton communities. Although larger cells seem to have the potential to develop higher biomass, it seems that other factors, including the surface-to-volume ratio, counterbalance this advantage, resulting in a random-like behaviour in resource acquisition by phytoplankton, irrespective of cell size or species identity.     

A divide and conquer approach to fast loop modeling

We describe a fast ab initio method for modeling local segments in protein structures. The algorithm is based on a divide and conquer approach and uses a database of precalculated look-up tables, which represent a large set of possible conformations for loop segments of variable length. The target loop is recursively decomposed until the resulting conformations are small enough to be compiled analytically. The algorithm, which is not restricted to any specific loop length, generates a ranked set of loop conformations in 20-180 s on a desktop PC. The prediction quality is evaluated in terms of global RMSD. Depending on loop length the top prediction varies between 1.06 A RMSD for three-residue loops and 3.72 A RMSD for eight-residue loops. Due to its speed the method may also be useful to generate alternative starting conformations for complex simulations.     

A new approach to modeling daily probabilities of conception

Standard conception probabilities models assume that different acts of intercourse make independent contributions to the probability of conception in viable cycles. We propose an alternative, approximate model based on the assumption that the act of intercourse closest to the time of maximum fertility is the one most likely to have caused conception. We describe an adaptive algorithm [the most fertile intercourse day (MFID) algorithm] that estimates the most fertile intercourse day in each cycle. The approach is easily extended to include covariates and random between-couple differences in fecundability that affect the probability of conception in a given cycle. Reanalyses of two data sets reported in the literature are presented. Estimates of the probability of conception during the most fertile period of the cycle and of the effects of covariates are similar to estimates found using standard models.     

Context-dependent effects of noise on echolocation pulse characteristics in free-tailed bats

Background noise evokes a similar suite of adaptations in the acoustic structure of communication calls across a diverse range of vertebrates. Echolocating bats may have evolved specialized vocal strategies for echolocating in noise, but also seem to exhibit generic vertebrate responses such as the ubiquitous Lombard response. We wondered how bats balance generic and echolocation-specific vocal responses to noise. To address this question, we first characterized the vocal responses of flying free-tailed bats (Tadarida brasiliensis) to broadband noises varying in amplitude. Secondly, we measured the bats’ responses to band-limited noises that varied in the extent of overlap with their echolocation pulse bandwidth. We hypothesized that the bats’ generic responses to noise would be graded proportionally with noise amplitude, total bandwidth and frequency content, and consequently that more selective responses to band-limited noise such as the jamming avoidance response could be explained by a linear decomposition of the response to broadband noise. Instead, the results showed that both the nature and the magnitude of the vocal responses varied with the acoustic structure of the outgoing pulse as well as non-linearly with noise parameters. We conclude that free-tailed bats utilize separate generic and specialized vocal responses to noise in a context-dependent fashion.     

A general multivariate approach to linear modeling in human genetics.

The general linear structural equation model is applied to problems in human genetics where there may be more than one measured phenotype per individual. A modeling convention, termed conditional associations, is developed to extend the general linear model so that it can handle the unique problems in human genetic models that arise from the pairing up of individuals or families under assortment between mates and the assortative placement of adoptees. Formulas are presented to generate expected covariance matrices for assortment or assortative placement on many variables simultaneously. It is demonstrated that all linear models in human genetics can be reduced in form to two fundamental equations. An algorithm is presented that will allow the application of these two equations to linear modeling in human genetics.