The effects of recombination rate on the distribution and abundance of transposable elements

Transposable elements (TEs) often accumulate in regions of the genome with suppressed recombination. But it is unclear whether this pattern reflects a reduction in the efficacy of selection against deleterious insertions or a relaxation of ectopic recombination. Discriminating between these two hypotheses has been difficult, because no formal model has investigated the effects of recombination under the deleterious insertion model. Here we take a simulation-based approach to analyze this scenario and determine the conditions under which element accumulation is expected in low recombination regions. We show that TEs become fixed as a result of Hill–Robertson effects in the form of Muller's ratchet, but only in regions of extremely low recombination when excision is effectively absent and synergism between elements is weak. These results have important implications for differentiating between the leading models of how selection acts on TEs and should help to interpret emerging population genetic and genomic data

Analysis of elastically tailored viscoelastic damping member

For more than two decades, viscoelastic materials have been commonly used as a passive damping source in a variety of structures because of their high material loss factors. In most of the applications, viscoelastic materials are used either in series with or parallel to the structural load path. The latter is also known as the constrained-layer damping treatment. The advantage of the constrained-layer damping treatment is that it can be incorporated without loss in structural integrity, namely, stiffness and strength. However, the disadvantages are that: (1) it is not the most effective use of the viscoelastic material when compared with the series-type application, and (2) weight penalty from the stiff constraining layer requirement can be excessive. To overcome the disadvantages of the constrained-layer damping treatment, a new approach for using viscoelastic material in axial-type structural components, e.g., truss members, was studied in this investigation

Federated Ensemble Regression Using Classification

Ensemble learning has been shown to significantly improve predictive accuracy in a variety of machine learning problems. For a given predictive task, the goal of ensemble learning is to improve predictive accuracy by combining the predictive power of multiple models. In this paper, we present an ensemble learning algorithm for regression problems which leverages the distribution of the samples in a learning set to achieve improved performance. We apply the proposed algorithm to a problem in precision medicine where the goal is to predict drug perturbation effects on genes in cancer cell lines. The proposed approach significantly outperforms the base case

Arguably big biology: Sociology, spatiality and the knockout mouse project

© 2013 copyright Palgrave MacmillanThis is a post-peer-review, pre-copyedit version of an article published in BioSocieties. The definitive publisher-authenticated version BioSocieties, 2013, Vol. 8, pp. 417-431 is available online at: http://www.palgrave-journals.com/biosoc/journal/v8/n4/full/biosoc201325a.htmlFollowing the completion of the Human Genome Project (HGP), a critical challenge has been how to make biological sense of the amassed sequence data and translate this into clinical applications. A range of large biological research projects, as well as more distributed experimental collaborations, are seeking to realise this through translational research initiatives and postgenomic approaches. Drawing on interviews with key participants, this article explores the biological assumptions, sociological challenges and spatial imaginaries at play in arguments around one of these developments, which is using genetically altered mice to understand gene function. The knockout mouse project (KOMP) is a large-scale initiative in functional genomics, seeking to produce a ‘knockout mouse’ for each gene in the mouse’s genome, which can then be used to answer questions about gene function in mammals. KOMP is frequently framed as one successor to the HGP, emblematic of the ambitions of internationally coordinated biological research. However, the development of new technologies for generating and managing genetically altered mice, alongside the challenge of asking biologically meaningful questions of vast numbers of animals, is creating new frictions in this extension and intensification of biological research practices. This article introduces two separate approaches to the future of international research using mutant mice as stakeholders to negotiate the biological, sociological and spatial challenges of collaboration. The first centres on the directed research practices and sociological assumptions of KOMP, as individual researchers are reorganised around shared animals, databases and infrastructures. The second highlights an alternative vision of the future of biomedical research, using distributed management to enhance the sensitivities and efficiencies of existing experimental practices over space. These exemplify two different tactics in the organisation of an ‘arguably’ big biology. They also critically embody different sociological and spatial imaginaries for the collaborative practices of international translational research

Caught you: threats to confidentiality due to the public release of large-scale genetic data sets

<p>Abstract</p> <p>Background</p> <p>Large-scale genetic data sets are frequently shared with other research groups and even released on the Internet to allow for secondary analysis. Study participants are usually not informed about such data sharing because data sets are assumed to be anonymous after stripping off personal identifiers.</p> <p>Discussion</p> <p>The assumption of anonymity of genetic data sets, however, is tenuous because genetic data are intrinsically self-identifying. Two types of re-identification are possible: the "Netflix" type and the "profiling" type. The "Netflix" type needs another small genetic data set, usually with less than 100 SNPs but including a personal identifier. This second data set might originate from another clinical examination, a study of leftover samples or forensic testing. When merged to the primary, unidentified set it will re-identify all samples of that individual.</p> <p>Even with no second data set at hand, a "profiling" strategy can be developed to extract as much information as possible from a sample collection. Starting with the identification of ethnic subgroups along with predictions of body characteristics and diseases, the asthma kids case as a real-life example is used to illustrate that approach.</p> <p>Summary</p> <p>Depending on the degree of supplemental information, there is a good chance that at least a few individuals can be identified from an anonymized data set. Any re-identification, however, may potentially harm study participants because it will release individual genetic disease risks to the public.</p

Methods and processes for development of a CONSORT extension for reporting pilot randomized controlled trials.

BACKGROUND: Feasibility and pilot studies are essential components of planning or preparing for a larger randomized controlled trial (RCT). They are intended to provide useful information about the feasibility of the main RCT-with the goal of reducing uncertainty and thereby increasing the chance of successfully conducting the main RCT. However, research has shown that there are serious inadequacies in the reporting of pilot and feasibility studies. Reasons for this include a lack of explicit publication policies for pilot and feasibility studies in many journals, unclear definitions of what constitutes a pilot or feasibility RCT/study, and a lack of clarity in the objectives and methodological focus. All these suggest that there is an urgent need for new guidelines for reporting pilot and feasibility studies. OBJECTIVES: The aim of this paper is to describe the methods and processes in our development of an extension to the Consolidated Standards of Reporting Trials (CONSORT) Statement for reporting pilot and feasibility RCTs, that are executed in preparation for a future, more definitive RCT. METHODS/DESIGN: There were five overlapping parts to the project: (i) the project launch-which involved establishing a working group and conducting a review of the literature; (ii) stakeholder engagement-which entailed consultation with the CONSORT group, journal editors and publishers, the clinical trials community, and funders; (iii) a Delphi process-used to assess the agreement of experts on initial definitions and to generate a reporting checklist for pilot RCTs, based on the 2010 CONSORT statement extension applicable to reporting pilot studies; (iv) a consensus meeting-to discuss, add, remove, or modify checklist items, with input from experts in the field; and (v) write-up and implementation-which included a guideline document which gives an explanation and elaboration (E&E) and which will provide advice for each item, together with examples of good reporting practice. This final part also included a plan for dissemination and publication of the guideline. CONCLUSIONS: We anticipate that implementation of our guideline will improve the reporting completeness, transparency, and quality of pilot RCTs, and hence benefit several constituencies, including authors of journal manuscripts, funding agencies, educators, researchers, and end-users