Name
Abstract | ||
|---|---|---|
Computational modeling in the health sciences is still very challenging and much of the success has been despite the difficulties involved in integrating all of the technologies, software, and other tools necessary to answer complex questions. Very large-scale problems are open to questions of spatio-temporal scale, and whether physico-chemical complexity is matched by biological complexity. For example, for many reasons, many large-scale biomedical computations today still tend to use rather simplified physics/chemistry compared with the state of knowledge of the actual biology/biochemistry. The ability to invoke modern grid technologies offers the ability to create new paradigms for computing, enabling access of resources which facilitate spanning the biological scale. |
Year | DOI | Venue |
|---|---|---|
2004 | 10.1007/BF03040952 | New Generation Comput. |
Keywords | Field | DocType |
pseudopotentials.,large-scale biomedical computation,spatio-temporal scale,grid computing,actual biology,computational modeling,complex question,effective group difference pseudopotential,biological complexity,physico-chemical complexity,qm/mm methods,biological scale,large-scale problem,distributed parametric modeling,enabling access,computer model,parametric model | Grid computing,Computer science,Theoretical computer science,Software,Grid,Computation | Journal |
Volume | Issue | ISSN |
22 | 2 | 1882-7055 |
Citations | PageRank | References |
18 | 2.39 | 4 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Wibke Sudholt | 1 | 122 | 11.60 |
| Kim K. Baldridge | 2 | 154 | 14.82 |
| David Abramson | 3 | 3302 | 393.08 |
| Colin Enticott | 4 | 231 | 21.68 |
| Slavisa Garic | 5 | 114 | 12.83 |