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1.
J Res Natl Inst Stand Technol ; 105(6): 875-94, 2000.
Article in English | MEDLINE | ID: mdl-27551642

ABSTRACT

The rate of scientific discovery can be accelerated through computation and visualization. This acceleration results from the synergy of expertise, computing tools, and hardware for enabling high-performance computation, information science, and visualization that is provided by a team of computation and visualization scientists collaborating in a peer-to-peer effort with the research scientists. In the context of this discussion, high performance refers to capabilities beyond the current state of the art in desktop computing. To be effective in this arena, a team comprising a critical mass of talent, parallel computing techniques, visualization algorithms, advanced visualization hardware, and a recurring investment is required to stay beyond the desktop capabilities. This article describes, through examples, how the Scientific Applications and Visualization Group (SAVG) at NIST has utilized high performance parallel computing and visualization to accelerate condensate modeling, (2) fluid flow in porous materials and in other complex geometries, (3) flows in suspensions, (4) x-ray absorption, (5) dielectric breakdown modeling, and (6) dendritic growth in alloys.

2.
Nucleic Acids Res ; 19(3): 637-47, 1991 Feb 11.
Article in English | MEDLINE | ID: mdl-2011534

ABSTRACT

Methods are presented for organizing and integrating DNA sequence data, restriction maps, and genetic maps for the same organism but from a variety of sources (databases, publications, personal communications). Proper software tools are essential for successful organization of such diverse data into an ordered, cohesive body of information, and a suite of novel software to support this endeavor is described. Though these tools automate much of the task, a variety of strategies is needed to cope with recalcitrant cases. We describe such strategies and illustrate their application with numerous examples. These strategies have allowed us to order, analyze, and display over one megabase of E. coli DNA sequence information. The integration task often exposes inconsistencies in the available data, perhaps caused by strain polymorphisms or human oversight, necessitating the application of sound biological judgment. The examples illustrate both the level of expertise required of the database curator and the knowledge gained as apparent inconsistencies are resolved. The software and mapping methods are applicable to the study of any genome for which a high resolution restriction map is available. They were developed to support a weakly coordinated sequencing effort involving many laboratories, but would also be useful for highly orchestrated sequencing projects.


Subject(s)
Chromosome Mapping , DNA, Bacterial/genetics , Databases, Factual , Escherichia coli/genetics , Genes, Bacterial , Base Sequence , Restriction Mapping , Software
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