Genome Exploitation: Data Mining the Genome (Stadler by J. Perry Gustafson, Randy Shoemaker, John W. Snape

By J. Perry Gustafson, Randy Shoemaker, John W. Snape

Genome Exploitation: information Mining the Genome is built from the twenty third Stadler Genetic Symposium. This quantity discusses and illustrates how scientists are going to symbolize and utilize the big volume of data being collected in regards to the plant and animal genomes. Genome Exploitation: facts Mining the Genome is a state of the art photo on mining the Genome databases. this is often one of many few instances that researchers in either vegetation and animals might be operating jointly to create a seminal info source.

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Additional info for Genome Exploitation: Data Mining the Genome (Stadler Genetics Symposia Series)

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It uploads raw sequence data and processes it through a series of analysis operations, each operation building upon the results of the previous stage. 5) and Oracle (v 9i ). The web interface provides the ability to pursue powerful complex declarative queries using Boolean operators on the part of our collaborators. The XGI Web Interface provides researchers with the ability to submit complex queries that permit precise delineation with Boolean logic operators in conjunction with scope delimiters (STRICT, LOOSE) enabling virtual Northerns and in silico subtractions as well mine the results of the analyses based on keyword searches of features and GO annotations.

From a financial perspective TAIR is not our most successful project; we have subsidized as much as 1/4 of the direct labor costs for the project. Also, because TAIR is a development project, there have not been many peer-reviewed manuscripts generated in the course of the project. None-the-less, with respect to use and impact on the biological community TAIR is the most successful integrated software system that we have developed. Growth in both content and use are measurements of this success.

Component based approaches do not produce systems capable of complex declarative queries because they do not provide inter-database consistency. However, they do allow heterogeneous resources to exchange data without homogenizing the data and applications (Szyperski, 1998). , 1999). , 2001b), a common feature includes the ability to adopt new and changing data types and applications from diverse sources. This is particularly useful in rapidly changing scientific disciplines where novel technologies and methods cannot be predicted (Gessler, 2002).

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