Projected pseudotransient continuation

2008-2009 > Academic research: refereed > Publication in refereed journalVersion of RecordPublishe

The Phyre2 web portal for protein modeling, prediction and analysis

Phyre2 is a suite of tools available on the web to predict and analyze protein structure, function and mutations. The focus of Phyre2 is to provide biologists with a simple and intuitive interface to state-of-the-art protein bioinformatics tools. Phyre2 replaces Phyre, the original version of the server for which we previously published a paper in Nature Protocols. In this updated protocol, we describe Phyre2, which uses advanced remote homology detection methods to build 3D models, predict ligand binding sites and analyze the effect of amino acid variants (e.g., nonsynonymous SNPs (nsSNPs)) for a user's protein sequence. Users are guided through results by a simple interface at a level of detail they determine. This protocol will guide users from submitting a protein sequence to interpreting the secondary and tertiary structure of their models, their domain composition and model quality. A range of additional available tools is described to find a protein structure in a genome, to submit large number of sequences at once and to automatically run weekly searches for proteins that are difficult to model. The server is available at http://www.sbg.bio.ic.ac.uk/phyre2. A typical structure prediction will be returned between 30 min and 2 h after submission

A global method for coupling transport with chemistry in heterogeneous porous media

Modeling reactive transport in porous media, using a local chemical equilibrium assumption, leads to a system of advection-diffusion PDE's coupled with algebraic equations. When solving this coupled system, the algebraic equations have to be solved at each grid point for each chemical species and at each time step. This leads to a coupled non-linear system. In this paper a global solution approach that enables to keep the software codes for transport and chemistry distinct is proposed. The method applies the Newton-Krylov framework to the formulation for reactive transport used in operator splitting. The method is formulated in terms of total mobile and total fixed concentrations and uses the chemical solver as a black box, as it only requires that on be able to solve chemical equilibrium problems (and compute derivatives), without having to know the solution method. An additional advantage of the Newton-Krylov method is that the Jacobian is only needed as an operator in a Jacobian matrix times vector product. The proposed method is tested on the MoMaS reactive transport benchmark.Comment: Computational Geosciences (2009) http://www.springerlink.com/content/933p55085742m203/?p=db14bb8c399b49979ba8389a3cae1b0f&pi=1

Fast interior point solution of quadratic programming problems arising from PDE-constrained optimization

Interior point methods provide an attractive class of approaches for solving linear, quadratic and nonlinear programming problems, due to their excellent efficiency and wide applicability. In this paper, we consider PDE-constrained optimization problems with bound constraints on the state and control variables, and their representation on the discrete level as quadratic programming problems. To tackle complex problems and achieve high accuracy in the solution, one is required to solve matrix systems of huge scale resulting from Newton iteration, and hence fast and robust methods for these systems are required. We present preconditioned iterative techniques for solving a number of these problems using Krylov subspace methods, considering in what circumstances one may predict rapid convergence of the solvers in theory, as well as the solutions observed from practical computations

Parameter identification problems in the modelling of cell motility

We present a novel parameter identification algorithm for the estimation of parameters in models of cell motility using imaging data of migrating cells. Two alternative formulations of the objective functional that measures the difference between the computed and observed data are proposed and the parameter identification problem is formulated as a minimisation problem of nonlinear least squares type. A Levenberg–Marquardt based optimisation method is applied to the solution of the minimisation problem and the details of the implementation are discussed. A number of numerical experiments are presented which illustrate the robustness of the algorithm to parameter identification in the presence of large deformations and noisy data and parameter identification in three dimensional models of cell motility. An application to experimental data is also presented in which we seek to identify parameters in a model for the monopolar growth of fission yeast cells using experimental imaging data. Our numerical tests allow us to compare the method with the two different formulations of the objective functional and we conclude that the results with both objective functionals seem to agree

Discovery of a black smoker vent field and vent fauna at the Arctic Mid-Ocean Ridge

The Arctic Mid-Ocean Ridge (AMOR) represents one of the most slow-spreading ridge systems on Earth. Previous attempts to locate hydrothermal vent fields and unravel the nature of venting, as well as the provenance of vent fauna at this northern and insular termination of the global ridge system, have been unsuccessful. Here, we report the first discovery of a black smoker vent field at the AMOR. The field is located on the crest of an axial volcanic ridge (AVR) and is associated with an unusually large hydrothermal deposit, which documents that extensive venting and long-lived hydrothermal systems exist at ultraslow-spreading ridges, despite their strongly reduced volcanic activity. The vent field hosts a distinct vent fauna that differs from the fauna to the south along the Mid-Atlantic Ridge. The novel vent fauna seems to have developed by local specialization and by migration of fauna from cold seeps and the Pacific

Testing Nelder-Mead based repulsion algorithms for multiple roots of nonlinear systems via a two-level factorial design of experiments

This paper addresses the challenging task of computing multiple roots of a system of nonlinear equations. A repulsion algorithm that invokes the Nelder-Mead (N-M) local search method and uses a penalty-type merit function based on the error function, known as 'erf', is presented. In the N-M algorithm context, different strategies are proposed to enhance the quality of the solutions and improve the overall efficiency. The main goal of this paper is to use a two-level factorial design of experiments to analyze the statistical significance of the observed differences in selected performance criteria produced when testing different strategies in the N-M based repulsion algorithm. The main goal of this paper is to use a two-level factorial design of experiments to analyze the statistical significance of the observed differences in selected performance criteria produced when testing different strategies in the N-M based repulsion algorithm.Fundação para a Ciência e Tecnologia (FCT

Antiracist Feminism and the Politics of Solidarity in Neoliberal Times

The chapter analyses the establishment and expansion of antiracist feminism in the last decade throughout the Nordic region, with new groups, media sites, and public events organised, especially in the large cities. Keskinen examines antiracist feminist and queer of colour activism in which the main or sole actors belong to groups racialised as non-white or ‘others’ in Nordic societies. A fundamental argument developed in the chapter is the central role and potential of these emerging social movements in the reconfiguring of political agendas and tackling pressing societal issues, due to its capacity to overlap and connect the borders of antiracist, feminist, and (to some extent) class-based politics. The chapter further argues for the usefulness of theorising the neoliberal turn of racial capitalism as the societal condition in which feminist activism takes place.Peer reviewe

Brain mapping in cognitive disorders: a multidisciplinary approach to learning the tools and applications of functional neuroimaging

<p>Abstract</p> <p>Background</p> <p>With rapid advances in functional imaging methods, human studies that feature functional neuroimaging techniques are increasing exponentially and have opened a vast arena of new possibilities for understanding brain function and improving the care of patients with cognitive disorders in the clinical setting. There is a growing need for medical centers to offer clinically relevant functional neuroimaging courses that emphasize the multifaceted and multidisciplinary nature of this field. In this paper, we describe the implementation of a functional neuroimaging course focusing on cognitive disorders that might serve as a model for other medical centers. We identify key components of an active learning course design that impact student learning gains in methods and issues pertaining to functional neuroimaging that deserve consideration when optimizing the medical neuroimaging curriculum.</p> <p>Methods</p> <p>Learning gains associated with the course were assessed using polychoric correlation analysis of responses to the SALG (Student Assessment of Learning Gains) instrument.</p> <p>Results</p> <p>Student gains in the functional neuroimaging of cognition as assessed by the SALG instrument were strongly associated with several aspects of the course design.</p> <p>Conclusion</p> <p>Our implementation of a multidisciplinary and active learning functional neuroimaging course produced positive learning outcomes. Inquiry-based learning activities and an online learning environment contributed positively to reported gains. This functional neuroimaging course design may serve as a useful model for other medical centers.</p