New Parallel and Distributed Tools and Algorithms for Life Sciences
Computational methods are nowadays ubiquitous in the field of bioinformatics and biomedicine. Besides established fields like molecular dynamics, genomics or neuroimaging, new emerging methods rely heavily on large scale computational resources. These new methods need to manage Tbytes or Pbytes of d...
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| Veröffentlicht in: | Future generation computer systems Jg. 112; S. 1174 - 1176 |
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| Hauptverfasser: | , |
| Format: | Journal Article |
| Sprache: | Englisch |
| Veröffentlicht: |
Elsevier B.V
01.11.2020
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| Schlagworte: | |
| ISSN: | 0167-739X, 1872-7115 |
| Online-Zugang: | Volltext |
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| Zusammenfassung: | Computational methods are nowadays ubiquitous in the field of bioinformatics and biomedicine. Besides established fields like molecular dynamics, genomics or neuroimaging, new emerging methods rely heavily on large scale computational resources. These new methods need to manage Tbytes or Pbytes of data with large-scale structural and functional relationships, TFlops or PFlops of computing power for simulating highly complex models, or many-task processes and workflows for processing and analyzing data. Today, many areas in Life Sciences are facing these challenges. This special issue contains papers showing existing solutions and latest developments in Life Sciences and Computing Sciences to collaboratively explore new ideas and approaches to successfully apply distributed IT-systems in translational research, clinical intervention, and decision-making. |
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| ISSN: | 0167-739X 1872-7115 |
| DOI: | 10.1016/j.future.2020.07.058 |