Sentence examples for seed framework from inspiring English sources

MG-RAST server is a freely available, fully automated open source system for processing metagenome sequence data based on the SEED framework for comparative genomics (McNeil et al. 2007; Overbeek et al. 2005).

In 2010, a semi-automatic model generation system has been developed [ 76] based on the RAST annotation system upon the SEED framework (relying on FIGfam database) that automatically maps genes from full genomes into metabolic maps connected with the KEGG database.

While gene clusters as used for COGs [ 3] or within the SEED framework [ 4] provide a valuable resource for functional annotation based on the identification of homologous genes, the domain based approach is focussed on modelling and detection of functional modules which usually involve only parts of a gene.

Taylor's SEED-Scale framework defines successful scaling up in terms of community involvement, where successful community projects are developed and promoted, and transformed into learning centers for other organizations seeking to learn how to implement the innovation, so that the projects are then systematically extended throughout different regions with other groups [ 24].

A seed point propagation framework is designed and implemented.

Finally, we show how using a particular topology as a seed to our framework significantly reduces the time to compute the final topology.

Subsystems in the SEED provide the framework for further improvement of these annotations and functional predictions.

Using this as the seed, the OptCircuit framework is employed to sequentially identify additional components by following the step-wise procedure shown in Figure 6.

Furthermore, the subsystem spreadsheet is used in SEED as a framework for integration of various types of functional data organized as gene attributes (e.g. gene clustering on a chromosome, expression array data, gene essentiality, etc).

Based on a formal adversarial model, the Seed-Explore-Exploit framework is presented, for simulating the generation of data driven and reverse engineering attacks on classifiers.

We compare in this section various types of seeds using the framework constructed above and then discuss the obtained results.