The suppression of q card selections: Evidence for deductive inference in Wason's Selection Task

The results of three experiments investigating the role of deductive inference in Wason's selection task are reported. In Experiment 1, participants received either a standard one-rule problem or a task containing a second rule, which specified an alternative antecedent. Both groups of participants were asked to select those cards that they considered were necessary to test whether the rule common to both problems was true or false. The results showed a significant suppression of q card selections in the two-rule condition. In addition there was weak evidence for both decreased p selection and increased not-q selection. In Experiment 2 we again manipulated number of rules and found suppression of q card selections only. Finally, in Experiment 3 we compared one- and two-rule conditions with a two-rule condition where the second rule specified two alternative antecedents in the form of a disjunction. The q card selections were suppressed in both of the two-rule conditions but there was no effect of whether the second rule contained one or two alternative antecedents. We argue that our results support the claim that people make inferences about the unseen side of the cards when engaging with the indicative selection task.

Revealing differences in gene network inference algorithms on the network level by ensemble methods

Motivation: The inference of regulatory networks from large-scale expression data holds great promise because of the potentially causal interpretation of these networks. However, due to the difficulty to establish reliable methods based on observational data there is so far only incomplete knowledge about possibilities and limitations of such inference methods in this context.

Results: In this article, we conduct a statistical analysis investigating differences and similarities of four network inference algorithms, ARACNE, CLR, MRNET and RN, with respect to local network-based measures. We employ ensemble methods allowing to assess the inferability down to the level of individual edges. Our analysis reveals the bias of these inference methods with respect to the inference of various network components and, hence, provides guidance in the interpretation of inferred regulatory networks from expression data. Further, as application we predict the total number of regulatory interactions in human B cells and hypothesize about the role of Myc and its targets regarding molecular information processing.

Structural influence of gene networks on their inference: analysis of C3NET

Background: The availability of large-scale high-throughput data possesses considerable challenges toward their functional analysis. For this reason gene network inference methods gained considerable interest. However, our current knowledge, especially about the influence of the structure of a gene network on its inference, is limited.

Bagging statistical network inference from large-scale gene expression data.

Modern biology and medicine aim at hunting molecular and cellular causes of biological functions and diseases. Gene regulatory networks (GRN) inferred from gene expression data are considered an important aid for this research by providing a map of molecular interactions. Hence, GRNs have the potential enabling and enhancing basic as well as applied research in the life sciences. In this paper, we introduce a new method called BC3NET for inferring causal gene regulatory networks from large-scale gene expression data. BC3NET is an ensemble method that is based on bagging the C3NET algorithm, which means it corresponds to a Bayesian approach with noninformative priors. In this study we demonstrate for a variety of simulated and biological gene expression data from S. cerevisiae that BC3NET is an important enhancement over other inference methods that is capable of capturing biochemical interactions from transcription regulation and protein-protein interaction sensibly. An implementation of BC3NET is freely available as an R package from the CRAN repository. © 2012 de Matos Simoes, Emmert-Streib.

The Contemporary Urban Condition: Understanding the Globalizing City as Informal, Contested, and Anchored.

In attempting to expand the vocabulary of urban description and understanding, and to offer a new composite conceptual framework for a more integrated urban planning and policy, this essay addresses the informal, contested, and anchored dimensions of the urban in turn; second, it seeks to increasingly link the three within the new global context; and finally, it attempts to draw these strands together in a proposed reconceptualization of the contemporary city within a world where the global is urbanizing and the urban is globalizing.