Significant Similarities In Terms Research Articles

A unified statistical framework for sequence comparison and structure comparison.

We present an approach for assessing the significance of sequence and structure comparisons by using nearly identical statistical formalisms for both sequence and structure. Doing so involves an all-vs.-all comparison of protein domains [taken here from the Structural Classification of Proteins (scop) database] and then fitting a simple distribution function to the observed scores. By using this distribution, we can attach a statistical significance to each comparison score in the form of a P value, the probability that a better score would occur by chance. As expected, we find that the scores for sequence matching follow an extreme-value distribution. The agreement, moreover, between the P values that we derive from this distribution and those reported by standard programs (e.g., BLAST and FASTA validates our approach. Structure comparison scores also follow an extreme-value distribution when the statistics are expressed in terms of a structural alignment score (essentially the sum of reciprocated distances between aligned atoms minus gap penalties). We find that the traditional metric of structural similarity, the rms deviation in atom positions after fitting aligned atoms, follows a different distribution of scores and does not perform as well as the structural alignment score. Comparison of the sequence and structure statistics for pairs of proteins known to be related distantly shows that structural comparison is able to detect approximately twice as many distant relationships as sequence comparison at the same error rate. The comparison also indicates that there are very few pairs with significant similarity in terms of sequence but not structure whereas many pairs have significant similarity in terms of structure but not sequence.

Tracks of change in hospitals: a study of quasi‐market transformation

Examines the process of change in hospitals that has emerged following the introduction of the health quasi‐market in 1991. Blends empirical evidence with Greenwood and Hinings’ archetype and tracks of change concepts to analyse the process which is labelled quasi‐market transformation (QMT). Argues that, before 1991, hospitals tended to operate within structures and systems underpinned by an interpretive scheme. Represents these similarities of configuration as the directly‐managed (DM) hospital archetype. When change initiatives challenged this configuration, the outcomes were negotiated and resulted in “adjustmental” change. In contrast, shows the introduction of the quasi‐market to have involved the first transformation of the DM archetype’s interpretive scheme, systems and structures. Analyses four years of transition to reveal that QMT has been interpreted differently within hospitals. However, presents data to suggest that many hospitals now display significant similarities in terms of configuration. Represents these similarities within the emerging Trust hospital archetype.