Rapid protein domain assignment from amino acid sequence using predicted secondary structure

The elucidation of the domain content of a given protein sequence in the absence of determined structure or significant sequence homology to known domains is an important problem in structural biology. Here we address how successfully the delineation of continuous domains can be accomplished in the absence of sequence homology using simple baseline methods, an existing prediction algorithm (Domain Guess by Size), and a newly developed method (DomSSEA). The study was undertaken with a view to measuring the usefulness of these prediction methods in terms of their application to fully automatic domain assignment. Thus, the sensitivity of each domain assignment method was measured by calculating the number of correctly assigned top scoring predictions. We have implemented a new continuous domain identification method using the alignment of predicted secondary structures of target sequences against observed secondary structures of chains with known domain boundaries as assigned by Class Architecture Topology Homology (CATH). Taking top predictions only, the success rate of the method in correctly assigning domain number to the representative chain set is 73.3%. The top prediction for domain number and location of domain boundaries was correct for 24% of the multidomain set (±20 residues). These results have been put into context in relation to the results obtained from the other prediction methods assessed

Robust pole assignment in systems subject to structured perturbations

The problem of robust pole assignment by feedback in a linear, multivariable, time-invariant system which is subject to structured perturbations is investigated. A measure of robustness, or sensitivity, of the poles to a given class of perturbations is derived, and a reliable and efficient computational algorithm is presented for constructing a feedback which assigns the prescribed poles and optimizes the robustness measure.

Creating a world class business through a merger of two equals: an interview with Paul Walsh, Chief Executive Officer of Diageo Plc

Purpose – The purpose of this paper is to explore, from a practical point-of-view, a number of key strategic issues that critically influence organisations' competitiveness. Design/methodology/approach – The paper is based on a semi-structured interview with Mr Paul Walsh, CEO of Diageo. Diageo is a highly successful company and Mr Walsh has played a central role in making Diageo the number one branded drink company in the world. Findings – The paper discusses the key attributes of successful merger, lessons from a complex cross boarder acquisition, rationale for strategic alliance with competitors, distinctive resources, and the role of corporate social responsibility. Research limitations/implications – It is not too often that management scholars have the opportunity to discuss with the CEOs of large multinationals the rational of key strategic decisions. In this paper these issues are explored from the perspective of a CEO of a large and successful company. The lessons, while not generalisable, offer unique insights to students of management and management researchers. Originality/value – The paper offers a bridge between theory and practice. It demonstrates that from Diageo's perspective the distinctive capabilities are intangible. It also offers insight into how to successfully execute strategic decision. In terms of originality it offers a view from the top, which is often missing from strategy research.

Perfective marking in L2 Mandarin: agreement with inherent lexical aspect or the derived Sentential Aspectual class?

This study evaluates the differing claims of the Aspect Hypothesis (Anderson & Shirai 1996) and the Sentential Aspect Hypothesis (Sharma & Deo 2009) for perfective marking by L1 English learners of Mandarin. The AH predicts a narrow focus on inherent lexical aspect (the verb and predicate) in determining the use of the perfective marker le, whilst the SAH suggests that – subject to L1 influence – perfective marking agrees with the final derived aspectual class of the sentence. To test these claims data were collected using a controlled le-insertion task, combined with oral corpus data. The results show that learners’ perfective marking patterns with the sentential aspectual class and not inherent lexical aspect (where these differ), and that overall the sentential aspectual class better predicts learners’ assignment of perfective marking than lexical aspect.