Agents to the Rescue?

The advent of electronic environments is bound to have profound effects on consumer decision making. While the exact nature of these influences is only partially known it is clear that consumers could benefit from properly designed electronic agents that know individual users\u27 preferences and can act on their behalf. An examination of the various roles agents perform is presented as a framework for thinking about the design of electronic agents. In addition, a set of goals is established that include both outcome-based measures, such as improving decision quality, as well as process measures like increasing satisfaction and developing trust

Precise detection of rearrangement breakpoints in mammalian chromosomes

<p>Abstract</p> <p>Background</p> <p>Genomes undergo large structural changes that alter their organisation. The chromosomal regions affected by these rearrangements are called breakpoints, while those which have not been rearranged are called synteny blocks. We developed a method to precisely delimit rearrangement breakpoints on a genome by comparison with the genome of a related species. Contrary to current methods which search for synteny blocks and simply return what remains in the genome as breakpoints, we propose to go further and to investigate the breakpoints themselves in order to refine them.</p> <p>Results</p> <p>Given some reliable and non overlapping synteny blocks, the core of the method consists in refining the regions that are not contained in them. By aligning each breakpoint sequence against its specific orthologous sequences in the other species, we can look for weak similarities inside the breakpoint, thus extending the synteny blocks and narrowing the breakpoints. The identification of the narrowed breakpoints relies on a segmentation algorithm and is statistically assessed. Since this method requires as input synteny blocks with some properties which, though they appear natural, are not verified by current methods for detecting such blocks, we further give a formal definition and provide an algorithm to compute them.</p> <p>The whole method is applied to delimit breakpoints on the human genome when compared to the mouse and dog genomes. Among the 355 human-mouse and 240 human-dog breakpoints, 168 and 146 respectively span less than 50 Kb. We compared the resulting breakpoints with some publicly available ones and show that we achieve a better resolution. Furthermore, we suggest that breakpoints are rarely reduced to a point, and instead consist in often large regions that can be distinguished from the sequences around in terms of segmental duplications, similarity with related species, and transposable elements.</p> <p>Conclusion</p> <p>Our method leads to smaller breakpoints than already published ones and allows for a better description of their internal structure. In the majority of cases, our refined regions of breakpoint exhibit specific biological properties (no similarity, presence of segmental duplications and of transposable elements). We hope that this new result may provide some insight into the mechanism and evolutionary properties of chromosomal rearrangements.</p

A General Framework for Formal Tests of Interaction after Exhaustive Search Methods with Applications to MDR and MDR-PDT

The initial presentation of multifactor dimensionality reduction (MDR) featured cross-validation to mitigate over-fitting, computationally efficient searches of the epistatic model space, and variable construction with constructive induction to alleviate the curse of dimensionality. However, the method was unable to differentiate association signals arising from true interactions from those due to independent main effects at individual loci. This issue leads to problems in inference and interpretability for the results from MDR and the family-based compliment the MDR-pedigree disequilibrium test (PDT). A suggestion from previous work was to fit regression models post hoc to specifically evaluate the null hypothesis of no interaction for MDR or MDR-PDT models. We demonstrate with simulation that fitting a regression model on the same data as that analyzed by MDR or MDR-PDT is not a valid test of interaction. This is likely to be true for any other procedure that searches for models, and then performs an uncorrected test for interaction. We also show with simulation that when strong main effects are present and the null hypothesis of no interaction is true, that MDR and MDR-PDT reject at far greater than the nominal rate. We also provide a valid regression-based permutation test procedure that specifically tests the null hypothesis of no interaction, and does not reject the null when only main effects are present. The regression-based permutation test implemented here conducts a valid test of interaction after a search for multilocus models, and can be applied to any method that conducts a search to find a multilocus model representing an interaction

Predictors of Online Buying: Findings from the Wharton Virtual Test Market

Introduction Consumers worldwide can shop online 24 hours per day, seven days a week, 365 days a year. Some market sectors such as insurance, financial services, computer hardware and software, travel, books, music, video, flowers, and automobiles have experienced rapid growth in online sales [7]. For example, Dell Computer Corporation sells $6,000,000 of equipment online each day [3], and Amazon.Com has become the third largest bookseller in the USA, since opening its virtual doors in July 1995 [6]. With projections that the Web will generate consumer and business-to-business sales in excess of$294 billion by 2002 [2], clearly online retailing raises many questions about marketing on the Net. Yet shopping on the net is far from universal, even among those who are online, and who do use the web for other tasks. To help identify what factors influence shopping on the Internet, the Wharton Forum on Electronic Commerce [http://ecom.wharton.upenn.edu] sponsored a research projec