This note presents a measure of similarity between connected nodes in terms of centrality based on Euclidean distances, and compares it to 'assortative mixing' [Newman, M.E.J., 2002. Assortative mixing in networks. Physical Review Letters 89, 208701], which is based on Pearson correlation coefficien
Effect of standardization on fragment-based measures of structural similarity
β Scribed by Peter A. Bath; Carol A. Morris; Peter Willett
- Publisher
- John Wiley and Sons
- Year
- 1993
- Tongue
- English
- Weight
- 501 KB
- Volume
- 7
- Category
- Article
- ISSN
- 0886-9383
No coin nor oath required. For personal study only.
β¦ Synopsis
Substructural fragment occurrence data are widely used as the basis for measures of inter-molecular structural similarity. This paper investigates the effect of standardization on the effectiveness of such measures using eight data sets for which both structural and biological activity data are available. Eight different standardization methods are studied and it is shown that there is no significant difference in the effectivenesses of the various methods; accordingly, any of them can be used for the calculation of intermolecular structural similarity.
π SIMILAR VOLUMES
This paper presents a new method for similarity measures between intuitionistic fuzzy sets (IFSs). We will present a method to calculate the distance between IFSs on the basis of the Hausdorff distance. We will then use this distance to generate a new similarity measure to calculate the degree of si
A method is presented for the derivation of knowledge-based pair potentials that corrects for the various compositions of different proteins. The resulting statistical pair potential is more specific than that derived from previous approaches as assessed by gapless threading results. Additionally, a