378 research outputs found
CATHEDRAL: A Fast and Effective Algorithm to Predict Folds and Domain Boundaries from Multidomain Protein Structures
We present CATHEDRAL, an iterative protocol for determining the location of previously observed protein folds in novel multidomain protein structures. CATHEDRAL builds on the features of a fast secondary-structure–based method (using graph theory) to locate known folds within a multidomain context and a residue-based, double-dynamic programming algorithm, which is used to align members of the target fold groups against the query protein structure to identify the closest relative and assign domain boundaries. To increase the fidelity of the assignments, a support vector machine is used to provide an optimal scoring scheme. Once a domain is verified, it is excised, and the search protocol is repeated in an iterative fashion until all recognisable domains have been identified. We have performed an initial benchmark of CATHEDRAL against other publicly available structure comparison methods using a consensus dataset of domains derived from the CATH and SCOP domain classifications. CATHEDRAL shows superior performance in fold recognition and alignment accuracy when compared with many equivalent methods. If a novel multidomain structure contains a known fold, CATHEDRAL will locate it in 90% of cases, with <1% false positives. For nearly 80% of assigned domains in a manually validated test set, the boundaries were correctly delineated within a tolerance of ten residues. For the remaining cases, previously classified domains were very remotely related to the query chain so that embellishments to the core of the fold caused significant differences in domain sizes and manual refinement of the boundaries was necessary. To put this performance in context, a well-established sequence method based on hidden Markov models was only able to detect 65% of domains, with 33% of the subsequent boundaries assigned within ten residues. Since, on average, 50% of newly determined protein structures contain more than one domain unit, and typically 90% or more of these domains are already classified in CATH, CATHEDRAL will considerably facilitate the automation of protein structure classification
The CATH Domain Structure Database and related resources Gene3D and DHS provide comprehensive domain family information for genome analysis
The CATH database of protein domain structures (http://www.biochem.ucl.ac.uk/bsm/cath/) currently contains 43 229 domains classified into 1467 superfamilies and 5107 sequence families. Each structural family is expanded with sequence relatives from GenBank and completed genomes, using a variety of efficient sequence search protocols and reliable thresholds. This extended CATH protein family database contains 616 470 domain sequences classified into 23 876 sequence families. This results in the significant expansion of the CATHHMMmodel library to include models built from the CATH sequence relatives, giving a10%increase in coveragefor detecting remote homologues. An improved Dictionary of Homologous superfamilies (DHS) (http://www.biochem.ucl.ac.uk/bsm/dhs/) containing specific sequence, structural and functional information for each superfamily in CATH considerably assists manual validation of homologues. Information on sequence relatives in CATH superfamilies, GenBank and completed genomes is presented in the CATH associated DHS and Gene3D resources. Domain partnership information can be obtained from Gene3D (http://www.biochem.ucl.ac.uk/bsm/cath/Gene3D/). A new CATH server has been implemented (http://www.biochem.ucl.ac.uk/cgi-bin/cath/CathServer.pl) providing automatic classification of newly determined sequences and structures using a suite of rapid sequence and structure comparison methods. The statistical significance of matches is assessed and links are provided to the putative superfamily or fold group to which the query sequence or structure is assigned
Including Women? (Dis)junctures Between Voice,
Abstract Integrated development plans (IDPs) are municipal strategic plans designed
to bring about developmental local government. They have been criticised for
providing insufficient space for democratic participation. This paper explores the
extent to which a marginalised group—women—has been incorporated into the IDP
process, in response to three questions. First, how have IDP participatory processes
incorporated women’s voice, and are the new participatory spaces realising their
transformative potential? Secondly, how have women’s interests and a gender
perspective been mainstreamed in the IDP, and has it promoted transformation? And
finally, at the interface between officials and women themselves, how are IDP projects
implemented and does agency promote or impede the goals of gender equality? A
study of three KwaZulu-Natal municipalities reveals some achievements, but unequal
gender relations have not been transformed. These case studies demonstrate some of
the complexities and difficulties in the practice of democratic governance
Local threshold field for dendritic instability in superconducting MgB2 films
Using magneto-optical imaging the phenomenon of dendritic flux penetration in
superconducting films was studied. Flux dendrites were abruptly formed in a 300
nm thick film of MgB2 by applying a perpendicular magnetic field. Detailed
measurements of flux density distributions show that there exists a local
threshold field controlling the nucleation and termination of the dendritic
growth. At 4 K the local threshold field is close to 12 mT in this sample,
where the critical current density is 10^7 A/cm^2. The dendritic instability in
thin films is believed to be of thermo-magnetic origin, but the existence of a
local threshold field, and its small value are features that distinctly
contrast the thermo-magnetic instability (flux jumps) in bulk superconductors.Comment: 6 pages, 6 figures, submitted to Phys. Rev.
Fact and fiction in housing research: utilizing the creative imagination
As much of our conceptual framework is informed by the experience of the imagination, there is much to be learnt from a study of various creative forms. Narrative fiction can be one such form, allowing us to gain a useful insight into complex features of social life. The purpose of this article is to investigate the treatment of housing issues in contemporary literature in order to gain insights into attitudes, experiences and interpretations from the perspective of a broad cultural milieu. Discussions of professionalism, housing tenure and homelessness have tended to be conducted within a narrow framework and adopted orthodox modes of evaluation. Consequently, the neglect of housing within a wider cultural context has reinforced the isolation of housing issues. The article argues that although discussions of housing and housing policy have been seriously limited within the contemporary novel, there are a number of key insights that can be gained from a discussion of issues within a fictional setting
The twilight of the Liberal Social Contract? On the Reception of Rawlsian Political Liberalism
This chapter discusses the Rawlsian project of public reason, or public justification-based 'political' liberalism, and its reception. After a brief philosophical rather than philological reconstruction of the project, the chapter revolves around a distinction between idealist and realist responses to it. Focusing on political liberalism’s critical reception illuminates an overarching question: was Rawls’s revival of a contractualist approach to liberal legitimacy a fruitful move for liberalism and/or the social contract tradition? The last section contains a largely negative answer to that question. Nonetheless the chapter's conclusion shows that the research programme of political liberalism provided and continues to provide illuminating insights into the limitations of liberal contractualism, especially under conditions of persistent and radical diversity. The programme is, however, less receptive to challenges to do with the relative decline of the power of modern states
Comprehensive review:Computational modelling of Schizophrenia
Computational modelling has been used to address: (1) the variety of symptoms observed in schizophrenia using abstract models of behavior (e.g. Bayesian models - top-down descriptive models of psychopathology); (2) the causes of these symptoms using biologically realistic models involving abnormal neuromodulation and/or receptor imbalance (e.g. connectionist and neural networks - bottom-up realistic models of neural processes). These different levels of analysis have been used to answer different questions (i.e. understanding behavioral vs. neurobiological anomalies) about the nature of the disorder. As such, these computational studies have mostly supported diverging hypotheses of schizophrenia's pathophysiology, resulting in a literature that is not always expanding coherently. Some of these hypotheses are however ripe for revision using novel empirical evidence.Here we present a review that first synthesizes the literature of computational modelling for schizophrenia and psychotic symptoms into categories supporting the dopamine, glutamate, GABA, dysconnection and Bayesian inference hypotheses respectively. Secondly, we compare model predictions against the accumulated empirical evidence and finally we identify specific hypotheses that have been left relatively under-investigated
Representing and comparing protein structures as paths in three-dimensional space
BACKGROUND: Most existing formulations of protein structure comparison are based on detailed atomic level descriptions of protein structures and bypass potential insights that arise from a higher-level abstraction. RESULTS: We propose a structure comparison approach based on a simplified representation of proteins that describes its three-dimensional path by local curvature along the generalized backbone of the polypeptide. We have implemented a dynamic programming procedure that aligns curvatures of proteins by optimizing a defined sum turning angle deviation measure. CONCLUSION: Although our procedure does not directly optimize global structural similarity as measured by RMSD, our benchmarking results indicate that it can surprisingly well recover the structural similarity defined by structure classification databases and traditional structure alignment programs. In addition, our program can recognize similarities between structures with extensive conformation changes that are beyond the ability of traditional structure alignment programs. We demonstrate the applications of procedure to several contexts of structure comparison. An implementation of our procedure, CURVE, is available as a public webserver
DAG-informed regression modelling, agent-based modelling, and microsimulation modelling: A critical comparison of methods for causal inference
The current paradigm for causal inference in epidemiology relies primarily on the evaluation of counterfactual contrasts via statistical regression models informed by graphical causal models (often in the form of directed acyclic graphs, or DAGs) and their underlying mathematical theory. However, there have been growing calls for supplementary methods, and one such method that has been proposed is agent-based modelling due to its potential for simulating counterfactuals. However, within the epidemiological literature there currently exists a general lack of clarity regarding what exactly agent-based modelling is (and is not) and, importantly, how it differs from microsimulation modelling – perhaps its closest methodological comparator. We clarify this distinction by briefly reviewing the history of each method, which provides context for their similarities and differences, and casts light on the types of research questions that they have evolved (and thus are well-suited) to answering; we do the same for DAG-informed regression methods. The distinct historical evolutions of DAG-informed regression modelling, microsimulation modelling, and agent-based modelling have given rise to distinct features of the methods themselves, and provide a foundation for critical comparison. Not only are the three methods well-suited to addressing different types of causal questions, but in doing so they place differing levels of emphasis on fixed and random effects, and also tend to operate on different timescales and in different timeframes
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