A Bayesian Framework for Parameter Estimation in Dynamical Models with Applications to Forecasting

Mathematical models in Biology are powerful tools for the study and exploration of complex dynamics. Nevertheless, bringing theoretical results to an agreement with experimental observations involves acknowledging a great deal of uncertainty intrinsic to our theoretical representation of a real system.
Proper handling of such uncertainties, is key to the successful usage of models to predict experimental or field observations. This problem has been addressed over the years by many tools for model calibration an parameter estimation. In this article we present a general framework for uncertainty analysis and parameter estimation which is designed to handle uncertainties associated with the modeling of dynamic biological systems while remaining agnostic as to the type of model used. We apply the framework to two Influenza transmission models: one deterministic and the other stochastic. The results show that the framework can be applied without modifications to the two types of models and that it performs equally well on both. We also discuss the application of the framework to calibrate models for forecasting purposes.
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Modelling, Estimation and Visualization of Multivariate Dependence for Risk Management

Dependence modelling and estimation is a key issue in the assessment of portfolio risk. When measuring extreme risk in terms of the Value-at-Risk, the multivariate normal model with linear correlation as its natural dependence measure is by no means an ideal model. We suggest a large class of models and a new dependence function which allows us to capture the complete extreme dependence structure of a portfolio. We also present a simple nonparametric estimation procedure. To show our new method at work we apply it to a financial data set of zero coupon swap rates and estimate the extreme dependence in the data

Dependence Estimation and Visualization in Multivariate Extremes with Applications to Financial Data

We investigate extreme dependence in a multivariate setting with special emphasis on financial applications. We introduce a new dependence function which allows us to capture the complete extreme dependence structure and present a nonparametric estimation procedure. The new dependence function is compared with existing measures including the spectral measure and other devices measuring extreme dependence. We also apply our method to a financial data set of zero coupon swap rates and estimate the extreme dependence in the data

The Exosome Subunit Rrp44 Plays a Direct Role in RNA Substrate Recognition

The exosome plays key roles in RNA maturation and surveillance, but it is unclear how target RNAs are identified. We report the functional characterization of the yeast exosome component Rrp44, a member of the RNase II family. Recombinant Rrp44 and the purified TRAMP polyadenylation complex each specifically recognized tRNAiMet lacking a single m1A58 modification, even in the presence of a large excess of total tRNA. This tRNA is otherwise mature and functional in translation in vivo but is presumably subtly misfolded. Complete degradation of the hypomodified tRNA required both Rrp44 and the poly(A) polymerase activity of TRAMP. The intact exosome lacking only the catalytic activity of Rrp44 failed to degrade tRNAiMet, showing this to be a specific Rrp44 substrate. Recognition of hypomodified tRNAiMet by Rrp44 is genetically separable from its catalytic activity on other substrates, with the mutations mapping to distinct regions of the protein

Optimizing Measurement of Vascular Endothelial Growth Factor in Small Blood Samples of Premature Infants

To establish a method that allows for the reliable assessment of vascular endothelial growth factor (VEGF-A) concentrations in very small blood samples of preterm infants. Systemic VEGF measurements are important in view of the most appropriate Anti-VEGF drug to be used for the treatment of acute retinopathy of prematurity (ROP). Cord blood samples from preterm (n = 6) infants, blood samples from preterm infants with treatment requiring ROP (n = 12), and blood samples from healthy adults (n = 10) were collected. Serum, citrate plasma, and serum from recalcified citrate blood were obtained. Levels of VEGF-A and platelet factor-4 (PF-4) were quantified by ELISA or AlphaLISA immunoassay. VEGF-A levels could be detected by both assays, with the AlphaLISA generating slightly lower levels in healthy adults, but not in cord blood of preterm infants. In plasma samples, VEGF levels ranged from non detectable to 181 pg/ml. PF-4 concentrations were between 0.16-3.88 microg/ml. Values of VEGF-A and PF-4 in serum and recalcified serum were significantly higher compared to plasma through the release of these cytokines after platelet activation. In plasma samples of infants with ROP, VEGF-A could always be detected and its values ranged from 19.50 to 245.91 pg/ml and PF-4 concentrations were between 0.1 and 3.3 microg/ml. Using the AlphaLISA kit, we were able to detect VEGF in small sample volumes (5 microl plasma or serum/well) in premature infants with treatment requiring ROP and to monitor platelet activation by PF-4 detection. Minimal blood probe volumes reduce phlebotomy losses avoiding the risk of iatrogenic anemia, thus allowing close monitoring of the cytokine levels in these very fragile infants

Assessing household vulnerability to climate change: The case of farmers in the Nile Basin of Ethiopia

Vulnerability to climate extremes, Nile Basin of Ethiopia, Minimum daily income, Climate change,