3,941 research outputs found
Deriving chemosensitivity from cell lines: Forensic bioinformatics and reproducible research in high-throughput biology
High-throughput biological assays such as microarrays let us ask very
detailed questions about how diseases operate, and promise to let us
personalize therapy. Data processing, however, is often not described well
enough to allow for exact reproduction of the results, leading to exercises in
"forensic bioinformatics" where aspects of raw data and reported results are
used to infer what methods must have been employed. Unfortunately, poor
documentation can shift from an inconvenience to an active danger when it
obscures not just methods but errors. In this report we examine several related
papers purporting to use microarray-based signatures of drug sensitivity
derived from cell lines to predict patient response. Patients in clinical
trials are currently being allocated to treatment arms on the basis of these
results. However, we show in five case studies that the results incorporate
several simple errors that may be putting patients at risk. One theme that
emerges is that the most common errors are simple (e.g., row or column
offsets); conversely, it is our experience that the most simple errors are
common. We then discuss steps we are taking to avoid such errors in our own
investigations.Comment: Published in at http://dx.doi.org/10.1214/09-AOAS291 the Annals of
Applied Statistics (http://www.imstat.org/aoas/) by the Institute of
Mathematical Statistics (http://www.imstat.org
High Dimensional Data Enrichment: Interpretable, Fast, and Data-Efficient
High dimensional structured data enriched model describes groups of
observations by shared and per-group individual parameters, each with its own
structure such as sparsity or group sparsity. In this paper, we consider the
general form of data enrichment where data comes in a fixed but arbitrary
number of groups G. Any convex function, e.g., norms, can characterize the
structure of both shared and individual parameters. We propose an estimator for
high dimensional data enriched model and provide conditions under which it
consistently estimates both shared and individual parameters. We also delineate
sample complexity of the estimator and present high probability non-asymptotic
bound on estimation error of all parameters. Interestingly the sample
complexity of our estimator translates to conditions on both per-group sample
sizes and the total number of samples. We propose an iterative estimation
algorithm with linear convergence rate and supplement our theoretical analysis
with synthetic and real experimental results. Particularly, we show the
predictive power of data-enriched model along with its interpretable results in
anticancer drug sensitivity analysis
Bumps, breathers, and waves in a neural network with spike frequency adaptation
In this Letter we introduce a continuum model of neural tissue that include the effects of so-called spike frequency adaptation (SFA). The basic model is an integral equation for synaptic activity that depends upon the non-local network connectivity, synaptic response, and firing rate of a single neuron. A phenomenological model of SFA is examined whereby the firing rate is taken to be a simple state-dependent threshold function. As in the case without SFA classical Mexican-Hat connectivity is shown to allow for the existence of spatially localized states (bumps). Importantly an analysis of bump stability using recent Evans function techniques shows that bumps may undergo instabilities leading to the emergence of both breathers and traveling waves. Moreover, a similar analysis for traveling pulses leads to the conditions necessary to observe a stable traveling breather. Direct numerical simulations both confirm our theoretical predictions and illustrate the rich dynamic behavior of this model, including the appearance of self-replicating bumps
Sources of variation in false discovery rate estimation include sample size, correlation, and inherent differences between groups
BACKGROUND: High-throughtput technologies enable the testing of tens of thousands of measurements simultaneously. Identification of genes that are differentially expressed or associated with clinical outcomes invokes the multiple testing problem. False Discovery Rate (FDR) control is a statistical method used to correct for multiple comparisons for independent or weakly dependent test statistics. Although FDR control is frequently applied to microarray data analysis, gene expression is usually correlated, which might lead to inaccurate estimates. In this paper, we evaluate the accuracy of FDR estimation. METHODS: Using two real data sets, we resampled subgroups of patients and recalculated statistics of interest to illustrate the imprecision of FDR estimation. Next, we generated many simulated data sets with block correlation structures and realistic noise parameters, using the Ultimate Microarray Prediction, Inference, and Reality Engine (UMPIRE) R package. We estimated FDR using a beta-uniform mixture (BUM) model, and examined the variation in FDR estimation. RESULTS: The three major sources of variation in FDR estimation are the sample size, correlations among genes, and the true proportion of differentially expressed genes (DEGs). The sample size and proportion of DEGs affect both magnitude and precision of FDR estimation, while the correlation structure mainly affects the variation of the estimated parameters. CONCLUSIONS: We have decomposed various factors that affect FDR estimation, and illustrated the direction and extent of the impact. We found that the proportion of DEGs has a significant impact on FDR; this factor might have been overlooked in previous studies and deserves more thought when controlling FDR
CYLINDER SEALS IN THE COLLECTIONS OF IZIKO MUSEUMS OF SOUTH AFRICA IN CAPE TOWN AND THE DEPARTMENT OF ANCIENT STUDIES OF STELLENBOSCH UNIVERSITY
This paper studies the cylinder seals in the collections of IzikoMuseums of South Africa in Cape Town and the Department ofAncient Studies of Stellenbosch University. The individual seals aredescribed and there is an iconographic analysis of the scenes andmotifs depicted on each seal, with comparisons to other artefacts.These seals date from the Early Dynastic period until the Persianperiod (ca. 3100-332 BC) and represent motifs such as deities,mythological beings and the ‘master of animals’, and scenes such asthe contest scene and presentation scene
Bumps and rings in a two-dimensional neural field: splitting and rotational instabilities
In this paper we consider instabilities of localised solutions in planar neural field firing rate models of Wilson-Cowan or Amari type. Importantly we show that angular perturbations can destabilise spatially localised solutions. For a scalar model with Heaviside firing rate function we calculate symmetric one-bump and ring solutions explicitly and use an Evans function approach to predict the point of instability and the shapes of the dominant growing modes. Our predictions are shown to be in excellent agreement with direct numerical simulations. Moreover, beyond the instability our simulations demonstrate the emergence of multi-bump and labyrinthine patterns.
With the addition of spike-frequency adaptation, numerical simulations of the resulting vector model show that it is possible for structures without rotational symmetry, and in particular multi-bumps, to undergo an instability to a rotating wave. We use a general argument, valid for smooth firing rate functions, to establish the conditions necessary to generate such a rotational instability. Numerical continuation of the rotating wave is used to quantify the emergent angular velocity as a bifurcation parameter is varied. Wave stability is found via the numerical evaluation of an associated eigenvalue problem
Life in Anticipation of Wind Power Development: Three Cases from Coastal Norway
Wind power development, whilst welcomed by many as a potentially green source of energy, also gives rise to considerable local resistance. Drawing on three case studies from coastal Norway (Frøya, Haramsøy, and Egersund), the present article sets out to reflect on life in anticipation of wind power development. Reflecting on the nature of life in anticipation of undesired wind power developments, with implications for how life is lived in dread of imminent adversities in general (such as climate change, pandemics, and disaster risks), these case studies focus on how communities relate to the future and how they perceive and strive to organise so as to shape outcomes. A central point raised in this article is that wind power projects could become more socially, environmentally and economically sustainable if greater attention is paid to working with communities to reduce distrust and uncertainties before, during and after such projects. Hence, relational work carried out that may shape the affective state of anticipation prior to and during wind farm construction can be understood as crucial to the sustainability of large-scale green infrastructure projects.publishedVersio
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