Comprehensive review of models and methods for inferences in bio-chemical reaction networks

The key processes in biological and chemical systems are described by networks of chemical reactions. From molecular biology to biotechnology applications, computational models of reaction networks are used extensively to elucidate their non-linear dynamics. The model dynamics are crucially dependent on the parameter values which are often estimated from observations. Over the past decade, the interest in parameter and state estimation in models of (bio-) chemical reaction networks (BRNs) grew considerably. The related inference problems are also encountered in many other tasks including model calibration, discrimination, identifiability, and checking, and optimum experiment design, sensitivity analysis, and bifurcation analysis. The aim of this review paper is to examine the developments in literature to understand what BRN models are commonly used, and for what inference tasks and inference methods. The initial collection of about 700 documents concerning estimation problems in BRNs excluding books and textbooks in computational biology and chemistry were screened to select over 270 research papers and 20 graduate research theses. The paper selection was facilitated by text mining scripts to automate the search for relevant keywords and terms. The outcomes are presented in tables revealing the levels of interest in different inference tasks and methods for given models in the literature as well as the research trends are uncovered. Our findings indicate that many combinations of models, tasks and methods are still relatively unexplored, and there are many new research opportunities to explore combinations that have not been considered—perhaps for good reasons. The most common models of BRNs in literature involve differential equations, Markov processes, mass action kinetics, and state space representations whereas the most common tasks are the parameter inference and model identification. The most common methods in literature are Bayesian analysis, Monte Carlo sampling strategies, and model fitting to data using evolutionary algorithms. The new research problems which cannot be directly deduced from the text mining data are also discussed

Proliferation of Tail Risks and Policy Responses in EU Financial Markets

This study draws attention to the proliferation of tail risks in financial markets prior to and during the course of the recent global financial crisis. It examines the level of tail risks in selected equity, interbank lending and foreign exchange markets in selected EU Member States in relation to the United States. The extent of tail risks is assessed by applying general error distribution (GED) parameterization in GARCH volatility tests of the examined variables. The empirical tests prove that tail risks were pronounced across all of the examined European financial markets throughout the crisis. They were also significant prior to the crisis outbreak. The analyzed interbank lending markets exhibited more extreme volatility outbursts than the equity and foreign exchange markets. Several countercyclical monetary and macroprudential policies aimed at abating tail risks are identified and discussed. Flexible capital adequacy and contingent capital requirements for financial institutions are advocated

Prevalence of widespread pain and associations with work status: a population study

<p>Abstract</p> <p>Background</p> <p>This population study based on a representative sample from a Swedish county investigates the prevalence, duration, and determinants of widespread pain (WSP) in the population using two constructs and estimates how WSP affects work status. In addition, this study investigates the prevalence of widespread pain and its relationship to pain intensity, gender, age, income, work status, citizenship, civil status, urban residence, and health care seeking.</p> <p>Methods</p> <p>A cross-sectional survey using a postal questionnaire was sent to a representative sample (n = 9952) of the target population (284,073 people, 18–74 years) in a county (Östergötland) in the southern Sweden. The questionnaire was mailed and followed by two postal reminders when necessary.</p> <p>Results</p> <p>The participation rate was 76.7% (n = 7637); the non-participants were on the average younger, earned less money, and male. Women had higher prevalences of pain in 10 different predetermined anatomical regions. WSP was generally chronic (90–94%) and depending on definition of WSP the prevalence varied between 4.8–7.4% in the population. Women had significantly higher prevalence of WSP than men and the age effect appeared to be stronger in women than in men. WSP was a significant negative factor – together with age 50–64 years, low annual income, and non-Nordic citizen – for work status in the community and in the group with chronic pain. Chronic pain but not the spreading of pain was related to health care seeking in the population.</p> <p>Conclusion</p> <p>This study confirms earlier studies that report high prevalences of widespread pain in the population and especially among females and with increasing age. Widespread pain is associated with prominent effects on work status.</p