Name
Abstract | ||
|---|---|---|
The drug discovery enterprise provides strong drivers for data integration. While attention in this arena has tended to focus on integration of primary data from omics and other large platform technologies contributing to drug discovery and development, the scientific literature remains a major source of information valuable to pharmaceutical enterprises, and therefore tools for mining such data and integrating it with other sources are of vital interest and economic impact. This review provides a brief overview of approaches to literature mining as they relate to drug discovery, and offers an illustrative case study of a lightweight approach we have implemented within an industrial context. |
Year | DOI | Venue |
|---|---|---|
2008 | 10.1093/bib/bbn035 | BRIEFINGS IN BIOINFORMATICS |
Keywords | Field | DocType |
drug discovery | Data integration,Data science,Data mining,Scientific literature,Drug discovery,Economic impact analysis,Biology,Biomedical text mining,Bioinformatics | Journal |
Volume | Issue | ISSN |
9 | 6 | 1467-5463 |
Citations | PageRank | References |
24 | 1.53 | 56 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Pankaj Agarwal | 1 | 138 | 17.19 |
| David B. Searls | 2 | 314 | 171.53 |