University of Bath

About: University of Bath is a education organization based out in Bath, Bath and North East Somerset, United Kingdom. It is known for research contribution in the topics: Population & Context (language use). The organization has 15830 authors who have published 39608 publications receiving 1358769 citations. The organization is also known as: Bath University.

The Genetic Code Is One in a Million

Abstract: Statistical and biochemical studies of the genetic code have found evidence of nonrandom patterns in the distribution of codon assignments. It has, for example, been shown that the code minimizes the effects of point mutation or mistranslation: erroneous codons are either synonymous or code for an amino acid with chemical properties very similar to those of the one that would have been present had the error not occurred. This work has suggested that the second base of codons is less efficient in this respect, by about three orders of magnitude, than the first and third bases. These results are based on the assumption that all forms of error at all bases are equally likely. We extend this work to investigate (1) the effect of weighting transition errors differently from transversion errors and (2) the effect of weighting each base differently, depending on reported mistranslation biases. We find that if the bias affects all codon positions equally, as might be expected were the code adapted to a mutational environment with transition/transversion bias, then any reasonable transition/transversion bias increases the relative efficiency of the second base by an order of magnitude. In addition, if we employ weightings to allow for biases in translation, then only 1 in every million random alternative codes generated is more efficient than the natural code. We thus conclude not only that the natural genetic code is extremely efficient at minimizing the effects of errors, but also that its structure reflects biases in these errors, as might be expected were the code the product of selection.

Squaring lean supply with supply chain management

Abstract: Lean supply ‐ the system of purchasing and supply chain management required to underpin lean production ‐ has been characterized as “beyond partnership”. Re‐examines this idea, comparing the techniques which constitute lean supply with those contained in supply chain management, partnership sourcing, and strategic purchasing. The observations and conclusions are based on research principally in the automotive and electronics industries in the UK, Italy, Scandinavia, the USA and Japan.

An initial classification of supply networks

Abstract: The articulation of supply networks, as an extension of supply chains, seeks to accommodate and explain the commercial complexity associated with the creation and delivery of goods and services from the source of raw materials to their destination in end‐customer markets. In place of the simplistic, linear and unidirectional model sometimes presented for supply chains, the supply network concept describes lateral links, reverse loops, two‐way exchanges and so on, encompassing the upstream and downstream activity, with a focal firm as the point of reference. A review of classifications of supply networks reveals that none of the existing approaches appears adequate for managers facing the practical problems of creating and operating them on a day‐to‐day basis. This research identifies differing emphases that may be required for managing within supply networks, according to the nature of the products for which they are created. Taking an established categorisation of supply chains as its starting point, the research first develops the conceptual basis, using strategy literature, and then tests the resultant initial model in 16 case studies. Finally, a new categorisation for supply networks is presented, using the type of product as a differentiator.

Adaptive evolution of bacterial metabolic networks by horizontal gene transfer.

Abstract: Numerous studies have considered the emergence of metabolic pathways, but the modes of recent evolution of metabolic networks are poorly understood. Here, we integrate comparative genomics with flux balance analysis to examine (i) the contribution of different genetic mechanisms to network growth in bacteria, (ii) the selective forces driving network evolution and (iii) the integration of new nodes into the network. Most changes to the metabolic network of Escherichia coli in the past 100 million years are due to horizontal gene transfer, with little contribution from gene duplicates. Networks grow by acquiring genes involved in the transport and catalysis of external nutrients, driven by adaptations to changing environments. Accordingly, horizontally transferred genes are integrated at the periphery of the network, whereas central parts remain evolutionarily stable. Genes encoding physiologically coupled reactions are often transferred together, frequently in operons. Thus, bacterial metabolic networks evolve by direct uptake of peripheral reactions in response to changed environments.