Computational method for the real-time calculation of the full-body muscle load distribution

A method is described for minimising a quadratic function subject to equality and inequality constraints. This approach is applicable to solving the full-body muscle load distribution problem and calculating joint contact loads. It has been found that this approach can provide the solution on modest computing facilities and in significantly less time than using active set and interior point quadratic programming techniques. Hence the approach is suitable for providing real-time feedback to subjects undergoing biomechanical analysis of muscle, skeletal and joint loadings.     

‘Have you got the Britísh?’: narratives of migration and settlement among Albanian-origin immigrants in London

Studies on migration and integration in Britain have noted the paucity of research on ‘new’ migrants, especially ‘illegal’ migrants and asylum seekers. This paper focuses on one understudied group – Albanian immigrants and their children – and looks at their migration and settlement, based on sixty interviews conducted in two phases either side of a 2003 mini-amnesty that gave many indefinite leave to remain. This regularization is the fulcrum around which our analytical narrative is built. Focusing on the interaction of migrants' agency with host-country structure, the paper shows that an unsettled asylum policy and delays in implementation have had deleterious effects on migrants' integration and sense of belonging, even after citizenship acquisition. As they search for a social and ethnic positioning within a multi-ethnic host society, the eventual realization of Albanians' migration project is accompanied by culture shock, intergenerational difference and ambivalence towards integration.     

Effects of PRE and POST therapy drug-pressure selected mutations on HIV-1 protease conformational sampling

Conformational sampling of pre- and post-therapy subtype B HIV-1 protease sequences derived from a pediatric subject infected via maternal transmission with HIV-1 were characterized by double electron–electron resonance spectroscopy. The conformational ensemble of the PRE construct resembles native-like inhibitor bound states. In contrast, the POST construct, which contains accumulated drug-pressure selected mutations, has a predominantly semi-open conformational ensemble, with increased populations of open-like states. The single point mutant L63P, which is contained in PRE and POST, has decreased dynamics, particularly in the flap region, and also displays a closed-like conformation of inhibitor-bound states. These findings support our hypothesis that secondary mutations accumulate in HIV-1 protease to shift conformational sampling to stabilize open-like conformations, while maintaining the predominant semi-open conformation for activity.     

Optimal trait scoring for age estimation

What are the effects that genetics has had on Anthropological research and how can we think anthropologically about Genetics? Just as genetic data have encouraged new hypotheses about human phenotypic variation, evolutionary history, population interaction, and environmental effects, so too has Anthropology offered to genetic studies a new interpretive locus in its history and perspective. This introduction examines how the fields of Anthropology and Genetics have arrived at a crucial moment at which their interaction requires careful examination and critical reflection. The papers discussed here exemplify how we may engage in such a trans-disciplinary conversation. They speak to the future of thoughtful interaction between genetic and anthropological literature and seek a new integration that embodies the holism of the human biological sciences.     

Learning generative models for protein fold families

We introduce a new approach to learning statistical models from multiple sequence alignments (MSA) of proteins. Our method, called GREMLIN (Generative REgularized ModeLs of proteINs), learns an undirected probabilistic graphical model of the amino acid composition within the MSA. The resulting model encodes both the position-specific conservation statistics and the correlated mutation statistics between sequential and long-range pairs of residues. Existing techniques for learning graphical models from MSA either make strong, and often inappropriate assumptions about the conditional independencies within the MSA (e.g., Hidden Markov Models), or else use suboptimal algorithms to learn the parameters of the model. In contrast, GREMLIN makes no a priori assumptions about the conditional independencies within the MSA. We formulate and solve a convex optimization problem, thus guaranteeing that we find a globally optimal model at convergence. The resulting model is also generative, allowing for the design of new protein sequences that have the same statistical properties as those in the MSA. We perform a detailed analysis of covariation statistics on the extensively studied WW and PDZ domains and show that our method out-performs an existing algorithm for learning undirected probabilistic graphical models from MSA. We then apply our approach to 71 additional families from the PFAM database and demonstrate that the resulting models significantly out-perform Hidden Markov Models in terms of predictive accuracy.     

Issues of cost and efficiency in the design of reliability studies

Reliability of continuous and dichotomous responses is usually assessed by means of the intraclass correlation coefficient (ICC). We derive the optimal allocation of the number of subjects k and the number of repeated measurements n that minimize the variance of the estimated ICC. Cost constraints are discussed for the case of normally distributed responses. Tables showing optimal choices of k and n are given, along with guidelines for the design of reliability studies in light of our results and those reported by others.     

Calculation of rate spectra from noisy time series data

As the resolution of experiments to measure folding kinetics continues to improve, it has become imperative to avoid bias that may come with fitting data to a predetermined mechanistic model. Toward this end, we present a rate spectrum approach to analyze timescales present in kinetic data. Computing rate spectra of noisy time series data via numerical discrete inverse Laplace transform is an ill‐conditioned inverse problem, so a regularization procedure must be used to perform the calculation. Here, we show the results of different regularization procedures applied to noisy multiexponential and stretched exponential time series, as well as data from time‐resolved folding kinetics experiments. In each case, the rate spectrum method recapitulates the relevant distribution of timescales present in the data, with different priors on the rate amplitudes naturally corresponding to common biases toward simple phenomenological models. These results suggest an attractive alternative to the “Occam's razor” philosophy of simply choosing models with the fewest number of relaxation rates. Proteins 2012. © 2011 Wiley Periodicals, Inc.