Calibration with confidence:A principled method for panel assessment

Frequently, a set of objects has to be evaluated by a panel of assessors, but not every object is assessed by every assessor. A problem facing such panels is how to take into account different standards amongst panel members and varying levels of confidence in their scores. Here, a mathematically-based algorithm is developed to calibrate the scores of such assessors, addressing both of these issues. The algorithm is based on the connectivity of the graph of assessors and objects evaluated, incorporating declared confidences as weights on its edges. If the graph is sufficiently well connected, relative standards can be inferred by comparing how assessors rate objects they assess in common, weighted by the levels of confidence of each assessment. By removing these biases, "true" values are inferred for all the objects. Reliability estimates for the resulting values are obtained. The algorithm is tested in two case studies, one by computer simulation and another based on realistic evaluation data. The process is compared to the simple averaging procedure in widespread use, and to Fisher's additive incomplete block analysis. It is anticipated that the algorithm will prove useful in a wide variety of situations such as evaluation of the quality of research submitted to national assessment exercises; appraisal of grant proposals submitted to funding panels; ranking of job applicants; and judgement of performances on degree courses wherein candidates can choose from lists of options.Comment: 32 pages including supplementary information; 5 figure

Estimating the evidence of selection and the reliability of inference in unigenic evolution

<p>Abstract</p> <p>Background</p> <p>Unigenic evolution is a large-scale mutagenesis experiment used to identify residues that are potentially important for protein function. Both currently-used methods for the analysis of unigenic evolution data analyze 'windows' of contiguous sites, a strategy that increases statistical power but incorrectly assumes that functionally-critical sites are contiguous. In addition, both methods require the questionable assumption of asymptotically-large sample size due to the presumption of approximate normality.</p> <p>Results</p> <p>We develop a novel approach, termed the Evidence of Selection (EoS), removing the assumption that functionally important sites are adjacent in sequence and and explicitly modelling the effects of limited sample-size. Precise statistical derivations show that the EoS score can be easily interpreted as an expected log-odds-ratio between two competing hypotheses, namely, the hypothetical presence or absence of functional selection for a given site. Using the EoS score, we then develop selection criteria by which functionally-important yet non-adjacent sites can be identified. An approximate power analysis is also developed to estimate the reliability of inference given the data. We validate and demonstrate the the practical utility of our method by analysis of the homing endonuclease <monospace>I-Bmol</monospace>, comparing our predictions with the results of existing methods.</p> <p>Conclusions</p> <p>Our method is able to assess both the evidence of selection at individual amino acid sites and estimate the reliability of those inferences. Experimental validation with <monospace>I-Bmol</monospace> proves its utility to identify functionally-important residues of poorly characterized proteins, demonstrating increased sensitivity over previous methods without loss of specificity. With the ability to guide the selection of precise experimental mutagenesis conditions, our method helps make unigenic analysis a more broadly applicable technique with which to probe protein function.</p> <p>Availability</p> <p>Software to compute, plot, and summarize EoS data is available as an open-source package called 'unigenic' for the 'R' programming language at <url>http://www.fernandes.org/txp/article/13/an-analytical-framework-for-unigenic-evolution</url>.</p

Caribbean-wide decline in carbonate production threatens coral reef growth

This a post-print, author-produced version of an article accepted for publication in Nature Communications. Copyright © 2013 Nature Publishing Group . The definitive version is available at http://www.nature.com/ncomms/journal/v4/n1/full/ncomms2409.htmlGlobal-scale deteriorations in coral reef health have caused major shifts in species composition. One projected consequence is a lowering of reef carbonate production rates, potentially impairing reef growth, compromising ecosystem functionality and ultimately leading to net reef erosion. Here, using measures of gross and net carbonate production and erosion from 19 Caribbean reefs, we show that contemporary carbonate production rates are now substantially below historical (mid- to late-Holocene) values. On average, current production rates are reduced by at least 50%, and 37% of surveyed sites were net erosional. Calculated accretion rates (mm year(-1)) for shallow fore-reef habitats are also close to an order of magnitude lower than Holocene averages. A live coral cover threshold of ~10% appears critical to maintaining positive production states. Below this ecological threshold carbonate budgets typically become net negative and threaten reef accretion. Collectively, these data suggest that recent ecological declines are now suppressing Caribbean reef growth potential

Recent developments of the Hierarchical Reference Theory of Fluids and its relation to the Renormalization Group

The Hierarchical Reference Theory (HRT) of fluids is a general framework for the description of phase transitions in microscopic models of classical and quantum statistical physics. The foundations of HRT are briefly reviewed in a self-consistent formulation which includes both the original sharp cut-off procedure and the smooth cut-off implementation, which has been recently investigated. The critical properties of HRT are summarized, together with the behavior of the theory at first order phase transitions. However, the emphasis of this presentation is on the close relationship between HRT and non perturbative renormalization group methods, as well as on recent generalizations of HRT to microscopic models of interest in soft matter and quantum many body physics.Comment: 17 pages, 5 figures. Review paper to appear in Molecular Physic

Characterization of N-acetyltransferase 1 and 2 polymorphisms and haplotype analysis for inflammatory bowel disease and sporadic colorectal carcinoma

<p>Abstract</p> <p>Background</p> <p>N-acetyltransferase 1 (NAT1) and 2 (NAT2) are polymorphic isoenzymes responsible for the metabolism of numerous drugs and carcinogens. Acetylation catalyzed by NAT1 and NAT2 are important in metabolic activation of arylamines to electrophilic intermediates that initiate carcinogenesis. Inflammatory bowel diseases (IBD) consist of Crohn's disease (CD) and ulcerative colitis (UC), both are associated with increased colorectal cancer (CRC) risk. We hypothesized that <it>NAT1 </it>and/or <it>NAT2 </it>polymorphisms contribute to the increased cancer evident in IBD.</p> <p>Methods</p> <p>A case control study was performed with 729 Caucasian participants, 123 CRC, 201 CD, 167 UC, 15 IBD dysplasia/cancer and 223 controls. <it>NAT1 </it>and <it>NAT2 </it>genotyping were performed using Taqman based techniques. Eight single nucleotide polymorphisms (SNPs) were characterized for <it>NAT1 </it>and 7 SNPs for <it>NAT2</it>. Haplotype frequencies were estimated using an Expectation-Maximization (EM) method. Disease groups were compared to a control group for the frequencies at each individual SNP separately. The same groups were compared for the frequencies of <it>NAT1 </it>and <it>NAT2 </it>haplotypes and deduced NAT2 phenotypes.</p> <p>Results</p> <p>No statistically significant differences were found for any comparison. Strong linkage disequilibrium was present among both the <it>NAT1 </it>SNPs and the <it>NAT2 </it>SNPs.</p> <p>Conclusion</p> <p>This study did not demonstrate an association between <it>NAT1 </it>and <it>NAT2 </it>polymorphisms and IBD or sporadic CRC, although power calculations indicate this study had sufficient sample size to detect differences in frequency as small as 0.05 to 0.15 depending on SNP or haplotype.</p

Structural Similarity and Classification of Protein Interaction Interfaces

Interactions between proteins play a key role in many cellular processes. Studying protein-protein interactions that share similar interaction interfaces may shed light on their evolution and could be helpful in elucidating the mechanisms behind stability and dynamics of the protein complexes. When two complexes share structurally similar subunits, the similarity of the interaction interfaces can be found through a structural superposition of the subunits. However, an accurate detection of similarity between the protein complexes containing subunits of unrelated structure remains an open problem

Adaptive and maladaptive consequences of “matching habitat choice:” lessons from a rapidly-evolving butterfly metapopulation

Relationships between biased dispersal and local adaptation are currently debated. Here, I show how prior work on wild butterflies casts a novel light on this topic. “Preference” is defined as the set of likelihoods of accepting particular resources after encountering them. So defined, butterfly oviposition preferences are heritable habitat adaptations distinct from both habitat preference and biased dispersal, but influencing both processes. When a butterfly emigrates after its oviposition preference begins to reduce realized fecundity, the resulting biased dispersal is analogous to that occurring when a fish emigrates after its morphological habitat adaptations reduce its feeding rate. I illustrate preference-biased dispersal with examples from metapopulations of Melitaea cinxia and Euphydryas editha. E. editha were feeding on a well-defended host, Pedicularis, when humans created patches in which Pedicularis was killed and a less-defended host, Collinsia, was rendered phenologically available. Patch-specific natural selection favoured oviposition on Collinsia in logged (“clearing”) patches and on Pedicularis in undisturbed open forest. Quantitative variation in post-alighting oviposition preference was heritable, and evolved to be consistently different between patch types. This difference was driven more by biased dispersal than by spatial variation of natural selection. Insects developing on Collinsia in clearings retained adaptations to Pedicularis in clutch size, geotaxis and oviposition preference, forcing them to choose between emigrating in search of forest habitats with Pedicularis or staying and failing to find their preferred host. Insects that stayed suffered reduction of realized fecundity after delayed oviposition on Collinsia. Those that emigrated suffered even greater fitness penalty from consistently low offspring survival on Pedicularis. Paradoxically, most emigrants reduced both their own fitness and that of the recipient populations by dispersing from a benign natal habitat to which they were maladapted into a more demanding habitat to which they were well-adapted. “Matching habitat choice” reduced fitness when evolutionary lag rendered traditional cues unreliable in a changing environment

Evaluating Forecasting Methods

Ideally, forecasting methods should be evaluated in the situations for which they will be used. Underlying the evaluation procedure is the need to test methods against reasonable alternatives. Evaluation consists of four steps: testing assumptions, testing data and methods, replicating outputs, and assessing outputs. Most principles for testing forecasting methods are based on commonly accepted methodological procedures, such as to prespecify criteria or to obtain a large sample of forecast errors. However, forecasters often violate such principles, even in academic studies. Some principles might be surprising, such as do not use R-square, do not use Mean Square Error, and do not use the within-sample fit of the model to select the most accurate time-series model. A checklist of 32 principles is provided to help in systematically evaluating forecasting methods

The association between retinal vascular geometry changes and diabetic retinopathy and their role in prediction of progression: an exploratory study

Background: The study describes the relationship of retinal vascular geometry (RVG) to severity of diabetic retinopathy (DR), and its predictive role for subsequent development of proliferative diabetic retinopathy (PDR). Methods. The research project comprises of two stages. Firstly, a comparative study of diabetic patients with different grades of DR. (No DR: Minimal non-proliferative DR: Severe non-proliferative DR: PDR) (10:10: 12: 19). Analysed RVG features including vascular widths and branching angles were compared between patient cohorts. A preliminary statistical model for determination of the retinopathy grade of patients, using these features, is presented. Secondly, in a longitudinal predictive study, RVG features were analysed for diabetic patients with progressive DR over 7 years. RVG at baseline was examined to determine risk for subsequent PDR development. Results: In the comparative study, increased DR severity was associated with gradual vascular dilatation (p = 0.000), and widening of the bifurcating angle (p = 0.000) with increase in smaller-child-vessel branching angle (p = 0.027). Type 2 diabetes and increased diabetes duration were associated with increased vascular width (p = <0.05 In the predictive study, at baseline, reduced small-child vascular width (OR = 0.73 (95 CI 0.58-0.92)), was predictive of future progression to PDR. Conclusions: The study findings suggest that RVG alterations can act as novel markers indicative of progression of DR severity and establishment of PDR. RVG may also have a potential predictive role in determining the risk of future retinopathy progression. © 2014 Habib et al.; licensee BioMed Central Ltd