Estimation of conditional laws given an extreme component

Let $(X,Y)$ be a bivariate random vector. The estimation of a probability of the form $P(Y\leq y \mid X >t)$ is challenging when $t$ is large, and a fruitful approach consists in studying, if it exists, the limiting conditional distribution of the random vector $(X,Y)$, suitably normalized, given that $X$ is large. There already exists a wide literature on bivariate models for which this limiting distribution exists. In this paper, a statistical analysis of this problem is done. Estimators of the limiting distribution (which is assumed to exist) and the normalizing functions are provided, as well as an estimator of the conditional quantile function when the conditioning event is extreme. Consistency of the estimators is proved and a functional central limit theorem for the estimator of the limiting distribution is obtained. The small sample behavior of the estimator of the conditional quantile function is illustrated through simulations.Comment: 32 pages, 5 figur

The eNMR platform for structural biology

The e-NMR project is a European cooperation initiative that aims at providing the bio-NMR user community with a software platform integrating and streamlining the computational approaches necessary for the analysis of bio-NMR data. The e-NMR platform is based on a Grid computational infrastructure. A main focus of the current implementation of the e-NMR platform is on streamlining structure determination protocols. Indeed, to facilitate the use of NMR spectroscopy in the life sciences, the eNMR consortium has set out to provide protocolized services through easy-to-use web interfaces, while still retaining sufficient flexibility to handle specific requests by expert users. Various programs relevant for structural biology applications are already available through the e-NMR portal, including HADDOCK, XPLOR-NIH, CYANA and csRosetta. The implementation of these services, and in particular the distribution of calculations to the GRID infrastructure, has required the development of specific tools. However, the GRID infrastructure is maintained completely transparent to the users. With more than 150 registered users, eNMR is currently the second largest European Virtual Organization in the life sciences

The NMR restraints grid at BMRB for 5,266 protein and nucleic acid PDB entries

Several pilot experiments have indicated that improvements in older NMR structures can be expected by applying modern software and new protocols (Nabuurs et al. in Proteins 55:483–186, 2004; Nederveen et al. in Proteins 59:662–672, 2005; Saccenti and Rosato in J Biomol NMR 40:251–261, 2008). A recent large scale X-ray study also has shown that modern software can significantly improve the quality of X-ray structures that were deposited more than a few years ago (Joosten et al. in J. Appl Crystallogr 42:376–384, 2009; Sanderson in Nature 459:1038–1039, 2009). Recalculation of three-dimensional coordinates requires that the original experimental data are available and complete, and are semantically and syntactically correct, or are at least correct enough to be reconstructed. For multiple reasons, including a lack of standards, the heterogeneity of the experimental data and the many NMR experiment types, it has not been practical to parse a large proportion of the originally deposited NMR experimental data files related to protein NMR structures. This has made impractical the automatic recalculation, and thus improvement, of the three dimensional coordinates of these structures. We here describe a large-scale international collaborative effort to make all deposited experimental NMR data semantically and syntactically homogeneous, and thus useful for further research. A total of 4,014 out of 5,266 entries were ‘cleaned’ in this process. For 1,387 entries, human intervention was needed. Continuous efforts in automating the parsing of both old, and newly deposited files is steadily decreasing this fraction. The cleaned data files are available from the NMR restraints grid at http://restraintsgrid.bmrb.wisc.edu

The Multicultural Classroom as a Comparative Law Site: A United Kingdom Perspective

This chapter studies the impact of the recent multicultural approach to comparative legal studies on comparative law teaching, with a focus on British debates and literature. I will argue that the multicultural turn of (comparative) legal teaching, reflected for example in a greater diversity of teaching techniques, a greater emphasis on minority issues and law &… disciplines, responds to a multiplicity of motivations. Pedagogically, it is a response to the increasingly diverse backgrounds of students and their differing intellectual starting-points. Pragmatically, it is a means to boost students’ employability and intellectual versality in a job market that now values “cultural awareness skills”. Finally, conceptually, it is a tool designed to unravel the pluralistic nature of law. From these diverse drivers to the multicultural turn in (comparative) legal teaching, it is possible to identify similarities with other recent trends of globalisation and internationalisation of legal education. However, this article will submit that differences remain. Having analysed these differences, I will go on to argue and reveal that in them lie the core features of a multicultural approach to legal teaching and its intrinsic connections to comparative law, as the multicultural classroom itself becomes a comparative law site

Use of selected complementary and alternative medicine (CAM) treatments in veterans with cancer or chronic pain: a cross-sectional survey

BACKGROUND: Complementary and alternative medicine (CAM) is emerging as an important form of care in the United States. We sought to measure the prevalence of selected CAM use among veterans attending oncology and chronic pain clinics and to describe the characteristics of CAM use in this population. METHODS: The self-administered, mail-in survey included questions on demographics, health beliefs, medical problems and 6 common CAM treatments (herbs, dietary supplements, chiropractic care, massage therapy, acupuncture and homeopathy) use. We used the chi-square test to examine bivariate associations between our predictor variables and CAM use. RESULTS: Seventy-two patients (27.3%) reported CAM use within the past 12 months. CAM use was associated with more education (p = 0.02), higher income (p = 0.006), non-VA insurance (p = 0.003), additional care outside the VA (p = 0.01) and the belief that lifestyle contributes to illness (p = 0.015). The diagnosis of chronic pain versus cancer was not associated with differential CAM use (p = 0.15). Seventy-six percent of CAM non-users reported that they would use it if offered at the VA. CONCLUSION: Use of 6 common CAM treatments among these veterans is lower than among the general population, but still substantial. A large majority of veterans reported interest in using CAM modalities if they were offered at the VA. A national assessment of veteran interest in CAM may assist VA leaders to respond to patients' needs

Accurate and efficient gp120 V3 loop structure based models for the determination of HIV-1 co-receptor usage

<p>Abstract</p> <p>Background</p> <p>HIV-1 targets human cells expressing both the CD4 receptor, which binds the viral envelope glycoprotein gp120, as well as either the CCR5 (R5) or CXCR4 (X4) co-receptors, which interact primarily with the third hypervariable loop (V3 loop) of gp120. Determination of HIV-1 affinity for either the R5 or X4 co-receptor on host cells facilitates the inclusion of co-receptor antagonists as a part of patient treatment strategies. A dataset of 1193 distinct gp120 V3 loop peptide sequences (989 R5-utilizing, 204 X4-capable) is utilized to train predictive classifiers based on implementations of random forest, support vector machine, boosted decision tree, and neural network machine learning algorithms. An <it>in silico </it>mutagenesis procedure employing multibody statistical potentials, computational geometry, and threading of variant V3 sequences onto an experimental structure, is used to generate a feature vector representation for each variant whose components measure environmental perturbations at corresponding structural positions.</p> <p>Results</p> <p>Classifier performance is evaluated based on stratified 10-fold cross-validation, stratified dataset splits (2/3 training, 1/3 validation), and leave-one-out cross-validation. Best reported values of sensitivity (85%), specificity (100%), and precision (98%) for predicting X4-capable HIV-1 virus, overall accuracy (97%), Matthew's correlation coefficient (89%), balanced error rate (0.08), and ROC area (0.97) all reach critical thresholds, suggesting that the models outperform six other state-of-the-art methods and come closer to competing with phenotype assays.</p> <p>Conclusions</p> <p>The trained classifiers provide instantaneous and reliable predictions regarding HIV-1 co-receptor usage, requiring only translated V3 loop genotypes as input. Furthermore, the novelty of these computational mutagenesis based predictor attributes distinguishes the models as orthogonal and complementary to previous methods that utilize sequence, structure, and/or evolutionary information. The classifiers are available online at <url>http://proteins.gmu.edu/automute</url>.</p

The effect of tightly-bound water molecules on scaffold diversity in computer-aided de novo ligand design of CDK2 inhibitors

We have determined the effects that tightly bound water molecules have on the de novo design of cyclin-dependent kinase-2 (CDK2) ligands. In particular, we have analyzed the impact of a specific structural water molecule on the chemical diversity and binding mode of ligands generated through a de novo structure-based ligand generation method in the binding site of CDK2. The tightly bound water molecule modifies the size and shape of the binding site and we have found that it also imposed constraints on the observed binding modes of the generated ligands. This in turn had the indirect effect of reducing the chemical diversity of the underlying molecular scaffolds that were able to bind to the enzyme satisfactorily

Menopausal Status Modifies Breast Cancer Risk Associated with the Myeloperoxidase (MPO) G463A Polymorphism in Caucasian Women: A Meta-Analysis

BACKGROUND: Breast cancer susceptibility may be modulated partly through polymorphisms in oxidative enzymes, one of which is myeloperoxidase (MPO). Association of the low transcription activity variant allele A in the G463A polymorphism has been investigated for its association with breast cancer risk, considering the modifying effects of menopausal status and antioxidant intake levels of cases and controls. METHODOLOGY/PRINCIPAL FINDINGS: To obtain a more precise estimate of association using the odds ratio (OR), we performed a meta-analysis of 2,975 cases and 3,427 controls from three published articles of Caucasian populations living in the United States. Heterogeneity among studies was tested and sensitivity analysis was applied. The lower transcriptional activity AA genotype of MPO in the pre-menopausal population showed significantly reduced risk (OR 0.56-0.57, p = 0.03) in contrast to their post-menopausal counterparts which showed non-significant increased risk (OR 1.14; p = 0.34-0.36). High intake of antioxidants (OR 0.67-0.86, p = 0.04-0.05) and carotenoids (OR 0.68-0.86, p = 0.03-0.05) conferred significant protection in the women. Stratified by menopausal status, this effect was observed in pre-menopausal women especially those whose antioxidant intake was high (OR 0.42-0.69, p = 0.04). In post-menopausal women, effect of low intake elicited susceptibility (OR 1.19-1.67, p = 0.07-0.17) to breast cancer. CONCLUSIONS/SIGNIFICANCE: Based on a homogeneous Caucasian population, the MPO G463A polymorphism places post-menopausal women at risk for breast cancer, where this effect is modified by diet