| Autor: |
Antonio de la Vega de León, Jürgen Bajorath |
| Jazyk: |
angličtina |
| Rok vydání: |
2016 |
| Předmět: |
|
| Zdroj: |
F1000Research, Vol 5 (2016) |
| Druh dokumentu: |
article |
| ISSN: |
2046-1402 |
| DOI: |
10.12688/f1000research.10021.1 |
| Popis: |
Networks, in which nodes represent compounds and edges pairwise similarity relationships, are used as coordinate-free representations of chemical space. So-called chemical space networks (CSNs) provide intuitive access to structural relationships within compound data sets and can be annotated with activity information. However, in such similarity-based networks, distances between compounds are typically determined for layout purposes and clarity and have no chemical meaning. By contrast, inter-compound distances as a measure of dissimilarity can be directly obtained from coordinate-based representations of chemical space. Herein, we introduce a CSN variant that incorporates compound distance relationships and thus further increases the information content of compound networks. The design was facilitated by adapting the Kamada-Kawai algorithm. Kamada-Kawai networks are the first CSNs that are based on numerical similarity measures, but do not depend on chosen similarity threshold values. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
|
