A novel superfamily containing the β-grasp fold involved in binding diverse soluble ligands

BACKGROUND: Domains containing the β-grasp fold are utilized in a great diversity of physiological functions but their role, if any, in soluble or small molecule ligand recognition is poorly studied. RESULTS: Using sensitive sequence and structure similarity searches we identify a novel superfamily containing the β-grasp fold. They are found in a diverse set of proteins that include the animal vitamin B12 uptake proteins transcobalamin and intrinsic factor, the bacterial polysaccharide export proteins, the competence DNA receptor ComEA, the cob(I)alamin generating enzyme PduS and the Nqo1 subunit of the respiratory electron transport chain. We present evidence that members of this superfamily are likely to bind a range of soluble ligands, including B12. There are two major clades within this superfamily, namely the transcobalamin-like clade and the Nqo1-like clade. The former clade is typified by an insert of a β-hairpin after the helix of the β-grasp fold, whereas the latter clade is characterized by an insert between strands 4 and 5 of the core fold. CONCLUSION: Members of both clades within this superfamily are predicted to interact with ligands in a similar spatial location, with their specific inserts playing a role in the process. Both clades are widely represented in bacteria suggesting that this superfamily was derived early in bacterial evolution. The animal lineage appears to have acquired the transcobalamin-like proteins from low GC Gram-positive bacteria, and this might be correlated with the emergence of the ability to utilize B12 produced by gut bacteria. REVIEWERS: This article was reviewed by Andrei Osterman, Igor Zhulin, and Arcady Mushegian

From text summarisation to style-specific summarisation for broadcast news

In this paper we report on a series of experiments investigating the path from text summarisation to style-specific summarisation of spoken news stories. We show that the portability of traditional text summarisation features to broadcast news is dependent on the diffusiveness of the information in the broadcast news story. An analysis of two categories of news stories (containing only read speech or including some spontaneous speech) demonstrates the importance of the style and the quality of the transcript, when extracting the summary-worthy information content. Further experiments indicate the advantages of doing style-specific summarisation of broadcast news

Towards Machine Wald

The past century has seen a steady increase in the need of estimating and predicting complex systems and making (possibly critical) decisions with limited information. Although computers have made possible the numerical evaluation of sophisticated statistical models, these models are still designed \emph{by humans} because there is currently no known recipe or algorithm for dividing the design of a statistical model into a sequence of arithmetic operations. Indeed enabling computers to \emph{think} as \emph{humans} have the ability to do when faced with uncertainty is challenging in several major ways: (1) Finding optimal statistical models remains to be formulated as a well posed problem when information on the system of interest is incomplete and comes in the form of a complex combination of sample data, partial knowledge of constitutive relations and a limited description of the distribution of input random variables. (2) The space of admissible scenarios along with the space of relevant information, assumptions, and/or beliefs, tend to be infinite dimensional, whereas calculus on a computer is necessarily discrete and finite. With this purpose, this paper explores the foundations of a rigorous framework for the scientific computation of optimal statistical estimators/models and reviews their connections with Decision Theory, Machine Learning, Bayesian Inference, Stochastic Optimization, Robust Optimization, Optimal Uncertainty Quantification and Information Based Complexity.Comment: 37 page