ESG web server is available for automated protein function prediction at http://dragon.bio.purdue.edu/ESG/.

A Variable Sampling Rate (VSR) control chart is a control chart whose sampling scheme is to vary the sampling interval and the sample size for the next sample depending on the current chart statistic. A VSR EWMA chart is an EWMA chart with the VSR sampling scheme. An economic model, which was developed for a VSRX chart, is also applied here to evaluate the efficiency of the VSR EWMA chart. The properties of the VSR EWMA chart are obtained by using a Markov chain approach. The model contains cost parameters which allow the specification of the costs associated with sampling, false alarms and operating off target as well as search and repair. This economic model can be used to quantify the cost saving that can be obtained by using a VSR chart instead of a Fixed Sampling Rate (FSR) chart and can also be used to gain insight into the way that a VSR chart should be designed to achieve optimal economic performance. It is shown that with some design parameter combinations the economically optimal VSR chart has a lower false alarm rate than the FSR chart.

No abstract

Computational protein tertiary structure prediction has made significant progress over the past years. However, most of the existing structure prediction methods are not equipped with functionality to predict accuracy of constructed models. Knowing the accuracy of a structure model is crucial for its practical use since the accuracy determines potential applications of the model. Here we have developed quality assessment methods, which predict real value of the global and local quality of protein structure models. The global quality of a model is defined as the root mean square deviation (RMSD) and the LGA score to its native structure. The local quality is defined as the distance between the corresponding Calpha positions of a model and its native structure when they are superimposed. Three regression methods are employed to combine different types of quality assessment measures of models, including alignment-level scores, residue-position level scores, atomic-detailed structure level scores and composite scores. The regression models were tested on a large benchmark data set of template-based protein structure models of various qualities. In predicting RMSD and the LGA score, a combination of two terms, length-normalized SPAD, a score that assesses alignment stability by considering suboptimal alignments, and Verify3D normalized by the square of the model length shows a significant performance, achieving 97.1 and 83.6% accuracy in identifying models with an RMSD of <2 and 6 A, respectively. For predicting the local quality of models, we find that a two-step approach, in which the global RMSD predicted in the first step is further combined with the other terms, can dramatically increase the accuracy. Finally, the developed regression equations are applied to assess the quality of structure models of whole E. coli proteome.

In addressing user experience issues, users' perceptions and emotions need to be considered important. This study examines the relationships between perceived usability/aesthetics and emotional valence/arousal/engagement through an experiment using 15 existing websites from various domains and questionnaire items developed to measure users' responses. According to the experimental results, both perceived usability and perceived aesthetics were positively correlated with emotional valence and negatively correlated with emotional engagement. No specific relationship was found between perceived usability/aesthetics and emotional arousal. Perceived aesthetics potentially had a greater impact on valence than perceived usability. Unlike valence, engagement could be more influenced by perceived usability than by perceived aesthetics. These findings can be utilized as bases for applying users' emotional responses in each dimension to the product-use situations in the chain of perceptions, emotions, and behaviors.