The Poisson Index: a new probabilistic model for protein ligand binding site similarity.

MOTIVATION: The large-scale comparison of protein-ligand binding sites is problematic, in that measures of structural similarity are difficult to quantify and are not easily understood in terms of statistical similarity that can ultimately be related to structure and function. We present a binding site matching score the Poisson Index (PI) based upon a well-defined statistical model. PI requires only the number of matching atoms between two sites and the size of the two sites-the same information used by the Tanimoto Index (TI), a comparable and widely used measure for molecular similarity. We apply PI and TI to a previously automatically extracted set of binding sites to determine the robustness and usefulness of both scores. RESULTS: We found that PI outperforms TI; moreover, site similarity is poorly defined for TI at values around the 99.5% confidence level for which PI is well defined. A difference map at this confidence level shows that PI gives much more meaningful information than TI. We show individual examples where TI fails to distinguish either a false or a true site paring in contrast to PI, which performs much better. TI cannot handle large or small sites very well, or the comparison of large and small sites, in contrast to PI that is shown to be much more robust. Despite the difficulty of determining a biological 'ground truth' for binding site similarity we conclude that PI is a suitable measure of binding site similarity and could form the basis for a binding site classification scheme comparable to existing protein domain classification schema.

Bayesian fused classification of medical images.

In many applications in computer vision and signal processing, it is necessary to assimilate data from multiple sources. This is a particularly important issue in medical imaging, where information on a patient may be available from a number of different modalities. As a result, there has been much recent research interest in this area. The authors suggest an additional Bayesian method which generates a segmented classification concurrently with improving reconstructions of a set of registered images. A synthetic example is used to demonstrate the subjectives and benefits of this proposed approach. Two medical applications, one fusing computed tomography (CT) and single photon emission computed tomography (SPECT) brain scans, and the other magnetic resonance (MR) images at two different resolutions, are considered.

On the Penrose hypothesis on fingerprint patterns.

Penrose hypothesized that fingerprint patterns such as loops, whorls, etc. are formed by ridges corresponding to the lines of curvature of the skin of the embryo at the time when the ridges were being formed. Under this hypothesis, Smith (1979) has shown analytically how some patterns emerge. In this paper it is shown that (i) Smith's differential equation has an exact solution and (ii) the extension given here supplies the remaining important patterns.

Statistics of response slopes.

Daubenspeck and Ogden in a recent paper recommended the use of directional statistics in the analysis of response slopes, and their advice has been followed by other workers. Their method is not valid, since it does not follow directly from their model. An efficient estimator of the slope (i.e., an estimator with minimum variance) is well known and is given here with a confidence interval for the true slope. They were also concerned with the two-sample problem to compare the slopes from two different samples. The method for this is more complicated but is summarized here. The likelihood ratio test and point and interval estimates are given. We discuss Daubenspeck and Ogden's example and the reason why, despite its invalidity, their method gave good results using their own data. Their data are also used to illustrate the methods described in this paper, and examples are given to highlight the practical differences between the two methods. Step-by-step procedures are included in the appendixes to enable readers to use these methods.