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Search Results: 1 - 10 of 156787 matches for " Eric F. Lock "
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Bayesian Consensus Clustering
Eric F. Lock,David B. Dunson
Computer Science , 2013, DOI: 10.1093/bioinformatics/btt425
Abstract: The task of clustering a set of objects based on multiple sources of data arises in several modern applications. We propose an integrative statistical model that permits a separate clustering of the objects for each data source. These separate clusterings adhere loosely to an overall consensus clustering, and hence they are not independent. We describe a computationally scalable Bayesian framework for simultaneous estimation of both the consensus clustering and the source-specific clusterings. We demonstrate that this flexible approach is more robust than joint clustering of all data sources, and is more powerful than clustering each data source separately. This work is motivated by the integrated analysis of heterogeneous biomedical data, and we present an application to subtype identification of breast cancer tumor samples using publicly available data from The Cancer Genome Atlas. Software is available at http://people.duke.edu/~el113/software.html.
Shared kernel Bayesian screening
Eric F. Lock,David B. Dunson
Statistics , 2013,
Abstract: This article concerns testing for differences between groups in many related variables. For example, the focus may be on identifying genomic sites with differential methylation between tumor subtypes. Standard practice in such applications is independent screening using adjustments for multiple testing to maintain false discovery rates. We propose a Bayesian nonparametric testing methodology, which improves performance by borrowing information adaptively across the different variables through the incorporation of shared kernels and a common probability of group differences. The inclusion of shared kernels in a finite mixture, with Dirichlet priors on the different weight vectors, leads to a simple and scalable methodology that can be routinely implemented in high dimensions. We provide some theoretical results, including closed asymptotic forms for the posterior probability of equivalence in two groups and consistency even under model misspecification. The method is shown to compare favorably to frequentist and Bayesian competitors, and is applied to methylation array data from a breast cancer study.
Efficiency clustering for low-density microarrays and its application to QPCR
Eric F Lock, Ryan Ziemiecki, JS Marron, Dirk P Dittmer
BMC Bioinformatics , 2010, DOI: 10.1186/1471-2105-11-386
Abstract: Our results indicate that QPCR primer-pairs differ significantly both in reliability and efficiency. They can only be used in an array format if the raw data (so called CT values for real-time QPCR) are transformed to take these differences into account. We developed a novel method to obtain efficiency-adjusted CT values. We introduce transformed confidence intervals as a novel measure to identify unreliable primers. We introduce a robust clustering algorithm to combine efficiencies of groups of probes, and our results indicate that using n < 10 cluster-based mean efficiencies is comparable to using individually determined efficiency adjustments for each primer pair (N = 96-1024).Careful estimation of primer efficiency is necessary to avoid significant measurement inaccuracies. Transformed confidence intervals are a novel method to assess and interprete the reliability of an efficiency estimate in a high throughput format. Efficiency clustering as developed here serves as a compromise between the imprecision in assuming uniform efficiency, and the computational complexity and danger of over-fitting when using individually determined efficiencies.Array and microarray based methods are the mainstay of molecular biology. Recently, lower-density or targeted arrays have been introduced. These comprise on the order of 10-1000 targets and represent an intermediate between 1 target assays, e.g. the viral load assay for HIV, and genomewide microarrays, comprising 10,000 -1,000,000 targets, e.g. Affymetrix? arrays. Analytically they can be treated as either a collection of individual assays or as microarrays.We are interested in discovering novel statistical approaches to the analysis of these intermediate density arrays. On the one hand high density microarray-based analysis methods do not capture all the information that is available. This results in lower than possible linear range and lower discriminating power. On the other hand, applying analysis methods developed for a
Joint and individual variation explained (JIVE) for integrated analysis of multiple data types
Eric F. Lock,Katherine A. Hoadley,J. S. Marron,Andrew B. Nobel
Statistics , 2011, DOI: 10.1214/12-AOAS597
Abstract: Research in several fields now requires the analysis of data sets in which multiple high-dimensional types of data are available for a common set of objects. In particular, The Cancer Genome Atlas (TCGA) includes data from several diverse genomic technologies on the same cancerous tumor samples. In this paper we introduce Joint and Individual Variation Explained (JIVE), a general decomposition of variation for the integrated analysis of such data sets. The decomposition consists of three terms: a low-rank approximation capturing joint variation across data types, low-rank approximations for structured variation individual to each data type, and residual noise. JIVE quantifies the amount of joint variation between data types, reduces the dimensionality of the data and provides new directions for the visual exploration of joint and individual structures. The proposed method represents an extension of Principal Component Analysis and has clear advantages over popular two-block methods such as Canonical Correlation Analysis and Partial Least Squares. A JIVE analysis of gene expression and miRNA data on Glioblastoma Multiforme tumor samples reveals gene-miRNA associations and provides better characterization of tumor types. Data and software are available at https://genome.unc.edu/jive/
Maximizing the contribution of the public health workforce: the English experience
Sim,F; Lock,K; McKee,M;
Bulletin of the World Health Organization , 2007, DOI: 10.1590/S0042-96862007001200014
Abstract: in the united kingdom, until the 1990s, specialist practice of public health was dominated by the medical profession. during the past decade, the contributions to specialist public health practice of people from diverse disciplines have become recognized, respected and valued. in parallel to this paradigm shift in culture in the specialist workforce, recognition is growing of the importance to health improvement of the routine activities of people in other jobs, whose daily work can have a significant impact on population health. these people include public health practitioners, such as environmental health officials, but also others in a very wide range of occupations, from local government chief executive officers to catering assistants, who, although their actions can have a substantial influence on public health, would not traditionally have been viewed as part of the public health workforce. transforming opportunities for training and professional development to meet the diverse needs of these different groups within the public health workforce for them to recognize and fulfil their potential for health improvement is an important challenge, if we are to achieve continuing improvements in public health. presenting england's attempts to address the challenges of recruiting and training the range of people needed to deliver effective intersectoral public health may offer insights for those facing similar challenges in other countries.
Chipping away at 'stemness'
April D Pyle, Peter J Donovan, Leslie F Lock
Genome Biology , 2004, DOI: 10.1186/gb-2004-5-8-235
Abstract: Embryonic stem (ES) cells are truly remarkable because of their ability both to renew themselves and to give rise to all the cells in the body. The ability to generate a wide range of differentiated cell types defines them as pluripotent. Human ES cells could be an incredible resource for the treatment of human disease. Differentiated cells derived from them could potentially be used to treat a wide variety of human conditions, including (but not limited to) heart disease, diabetes, stroke, Alzheimer's disease and Parkinson's disease. Several major hurdles remain to be overcome if such cells are to be used clinically, however. Stated simply, we know very little about their basic physiology or their true potential. What factors are required for their survival and proliferation? What factors can maintain them in a pluripotent state? What growth conditions affect their differentiation?One way to address these questions is to analyze gene expression in ES cells. The goal is straightforward: if we can identify the full panoply of genes expressed in human ES cells and compare this with data from other stem-cell and non-stem-cell populations, it might be possible to define what makes ES cells unique. Such genes might be the ones that maintain ES cells in a self-renewing, pluripotent state. Knowledge of the genes expressed in ES cells could also have some very practical uses. For example, knowing that human ES cells express certain growth factor receptors could help in devising strategies to improve the growth of the cells in culture. Analyzing gene expression in human ES cells could provide critical insights into the cell-surface receptors involved in growth control, cell-substrate adhesion and cell-cell adhesion in these and other cell types, and into intracellular signaling pathways involved in their basic physiology.Several recent papers [1-5] have now reported global gene-expression analyses of a variety of human ES-cell lines (summarized in Table 1 and Figure 1). The
Applying Quantification of Qualitative Verbal Data to Asynchronous Written Discourse  [PDF]
Jamie Costley, Seung Lock Han
Creative Education (CE) , 2013, DOI: 10.4236/ce.2013.412A1001
Abstract: As more and more universities start to implement online components, the need to build online learning communities grows. An important and widely used type of online community is the internet forum. Internet forums operate asynchronously and each member can create threads and reply to others threads. Examination of each member’s writings can give valuable insight into the online community and the learning that is taking place within. This paper systematizes a method for researchers to investigate discussions on online forums. More specifically this paper lays out an 8-step process that a researcher may follow when investigating discussions on online forums.
A mente molecularizada e a busca da demência incipiente
Lock, Margareth;
Physis: Revista de Saúde Coletiva , 2005, DOI: 10.1590/S0103-73312005000200003
Abstract: the author presents a critique of the prevailing genetic determinism in part of the genetic research, based on a revision of its main historical landmarks, resorting to the works of authors such as kay and lewontin, among others. building on this delimitation, she examines the discussions on the possibility of an early diagnosis of alzheimer's disease (ad), including attempts to identify possible risk markers for it, including the discussion of the very diagnostic and taxonomic difficulties of da, in particular of the termed late onset form. the author emphasizes the extent that current causal theories (relevant to the idea of early diagnosis) downplay or even omit the role of social factors in the onset of ad. she then outlines the diverse and conflicting findings on possible genetic risk markers for ad, which, even with meager results, still lead to the production of tests for their detection. finally, the author examines in detail the reveal project, of the national institutes of health (nih), currently under way, which aims to identify the apoe gen in the general american population. the article concludes with a description of the subjective repercussions in the subjects that participated in that test.
Electromagnetic Scattering of Plane Wave from a Finite Array of Partially-Shielded Dielectric Cylinders
Kaiser Lock
Lecture Notes in Engineering and Computer Science , 2009,
The Universities: A New Legal Grammar
Grahame Lock
Amsterdam Law Forum , 2010,
Abstract: In recent years the national and internal administration of universities has undergone fundamental change. This change parallels developments in other sectors of public life. It is matter not just of the rise of managerialism and of a takeover of control by the New Public Managers, proxies of other non-academic interests, at the cost of professional autonomy. What we are confronted with is in fact another expression of the substitution of governance for government, and in this connexion of the rise of what is called ‘soft law’. All this is bad news not only for academia but for democracy.
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