Name
Title | ||
|---|---|---|
Similarity Coefficients for Binary Chemoinformatics Data: Overview and Extended Comparison Using Simulated and Real Data Sets. |
Abstract | ||
|---|---|---|
This paper reports an analysis and comparison of the use of Si different similarity coefficients for computing the similarities between binary fingerprints. for both simulated and real chemical data sets.. Five pairs and a triplet of Coefficients were found to yield identical similarity values; leading to the elimination of seven. of the coefficients. The remaining 44 coefficients were then compared in two Ways by their theoretical characteristics Using simple descriptive statistic's, correlation analysis, multidimensional scaling, Hasse diagrams, and the recently described atemporal target diffusion model; and by their effectiveness for similarity based virtual screening using MDDR, WOMBAT, and MUV data. The comparisons demonstrate the general utility Of the well-known Tanimoto method but also suggest other coefficients that may be worthy of further attention. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1021/ci300261r | JOURNAL OF CHEMICAL INFORMATION AND MODELING |
Field | DocType | Volume |
Data mining,Data set,Multidimensional scaling,Pattern recognition,Combinatorial chemistry,Artificial intelligence,Cheminformatics,Correlation analysis,Mathematics,Binary number | Journal | 52 |
Issue | ISSN | Citations |
11 | 1549-9596 | 26 |
PageRank | References | Authors |
1.20 | 5 | 6 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Roberto Todeschini | 1 | 279 | 24.12 |
| Viviana Consonni | 2 | 103 | 7.58 |
| Hua Xiang | 3 | 26 | 1.20 |
| John D. Holliday | 4 | 318 | 39.20 |
| Massimo Buscema | 5 | 99 | 9.55 |
| PETER WILLETT | 6 | 3421 | 592.93 |