Inferring causal molecular networks: empirical assessment through a community-based effort

It remains unclear whether causal, rather than merely correlational, relationships in molecular networks can be inferred in complex biological settings. Here we describe the HPN-DREAM network inference challenge, which focused on learning causal influences in signaling networks. We used phosphoprotein data from cancer cell lines as well as in silico data from a nonlinear dynamical model. Using the phosphoprotein data, we scored more than 2,000 networks submitted by challenge participants. The networks spanned 32 biological contexts and were scored in terms of causal validity with respect to unseen interventional data. A number of approaches were effective, and incorporating known biology was generally advantageous. Additional sub-challenges considered time-course prediction and visualization. Our results suggest that learning causal relationships may be feasible in complex settings such as disease states. Furthermore, our scoring approach provides a practical way to empirically assess inferred molecular networks in a causal sense

EU air pollution policy : to what extent is the EU a particularly efficient body for air pollution policy development? : a case study of the development of the EU vehicle directives

EU Air Pollution Policy - To what extent is the EU a particularly efficient Body for Air Pollution Policy Development? A case study of the Development of the EU Vehicle Directives. Summary The theme of this thesis is the development in one area of the EU air pollution policy, namely the EU vehicle directives. I have first looked at the development of the vehicle directives from 1985 until 1997 in order to see whether there has taken place an increase in strength regarding the directives. This period has been divided into two phases, with the first phase going from 1985 until 1992 and the second phase from 1992 until 1997. The directives were again grouped into categories for fuel standards, emission limits and light and heavy vehicles. The dependent variable in the analysis is the development of strength of the EU vehicle directives. In order to measure degree of "strength", I have used two main indicators; scope and ambitiousness. Scope refers to how many pollutants which have been included in a directive, while ambitousness says something about the percentage reduction of a pollutant from one directive to another. In order to support the findings from these two indicators, I have looked at the opinions of interest groups and bodies inside the EU etc. My next task was to discuss possible change in the independent variables, which could shed light on the dependent variable. For this purpose, I have used two perspectives, which each contained the independent variables. The first perspective was called the character of the problem and related preferences and constitutes the first independent variable. Here, it is assumed that the member states affectedness by problem and by measures to deal with the problem to a large extent explain the outcome of that problem. The next perspective was called the problem-solving capacity of the EU-system and it claims that the outcome of a problem depends on how decisions are made, ie. that institutional characteristics determine the outcome of a problem. The perspective contains the following independent variables: decision-making procedures, decision-making processes, intra-organisational procedures and finally, institutional accessibility. My main assumption was that a combination of these two perspectives contributed the most in sheding light on the possible increase in strength of the EU vehicle directives. The empirical findings indicate that there has taken place an increase in strength of the EU vehicle directives from phase I to phase II, especially regarding the directives adopted on emission limits for light vehicles. More pollutants were added in new directives (scope) and the already existing pollutants had got their limits tightened. Regarding the explanatory perspectives and their ability to shed light on the change in strength of the EU vehicle directives, my analysis indicates that a combination of the two perspectives, with a weight on the first one (the character of the problem and related preferences) is the most likely to shed light on the dependent variable. As regards the hypothesis put forward, some of them were strengthened while others were not. Regarding the first explanatory perspective and the independent variable of which it consists, empirical findings indicated that more countries today than earlier had gone over to the group being highly affected by air pollution and for some, also highly affected by measures to deal with this problem. On the background of the analysis, the variable contributes in sheding light on the development of strength regarding the EU vehicle directives. The next explanatory perspective concerned different procedures and institutions inside the EU and consisted of four independent variable; the transition from unanimity to QMV (decision-making procedures), introduction of the co-operation procedure and the co-decision procedure (decision-making processes), development of relationships within and between the Council, the Commission and the Parliament (intra-organisational procedures) and finally the development of environmental NGOs in relation to industrial groups. On the basis of the empirical findings, I found that the hypotheses on the decision-making processes, on the Council and on the Commission were given support. The hypotheses on decision-making procedures and institutional accessibility were not strengthened to a very large degree. Regarding the hypothesis on the Parliament it was strengthened to some degree, but this is mostly due to the introduction of the co-operation and the co-decision procedure which give the body enhanced influence

Normalization of circulating microRNA expression data obtained by quantitative real-time RT-PCR

The high-throughput analysis of microRNAs (miRNAs) circulating within the blood of healthy and diseased individuals is an active area of biomarker research. Whereas quantitative real-time reverse transcription polymerase chain reaction (qPCR)-based methods are widely used, it is yet unresolved how the data should be normalized. Here, we show that a combination of different algorithms results in the identification of candidate reference miRNAs that can be exploited as normalizers, in both discovery and validation phases. Using the methodology considered here, we identify normalizers that are able to reduce nonbiological variation in the data and we present several case studies, to illustrate the relevance in the context of physiological or pathological scenarios. In conclusion, the discovery of stable reference miRNAs from high-throughput studies allows appropriate normalization of focused qPCR assays