Sentence examples for mappings and data from inspiring English sources

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In this section we present three case studies to illustrate the merits of some data analysis and visualization options in Chipster, such as linear modelling, alternative probe mappings, and data integration.

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In this article, we present MostoDE, a tool that assists software engineers in generating SPARQL executable mappings and exchanging data amongst ontologies.

We compared the location of CUX1 binding sites that are more than 4 Kb from the nearest TSS to DNAse hypersensitivity mappings and ChromHMM data in human mammary epithelial cells from published datasets.

A total of (68) F1 progeny individuals were genotyped using the SFP-mapping microarray and data for 28 individuals from the discovery set was retrieved for the same 43,777 probes, totaling 96 individuals.

Firstly, given the following: the set of clouds P the set of services S the set of data O the map of security locations l. the set of clouds P. the set of services S. the set of data O. the map of security locations l. we can define the valid mappings of services and data onto clouds, using rule (7): V : S + O → P V = { b → p | b ∈ S + O, p ∈ P, l ( b ) ≤ l ( p ) }.

If either is violated then the workflow does not meet the security requirements, and so should be removed from the set W of valid mappings of services and data to clouds.

Having determined all valid mappings of services and data to clouds, the set of all valid workflow deployments is given by: W : ( S + O → P ) → { ( S + O → P ) } = { w ∈ | | V | |, ∀ b ∈ S + O. ∃ p ∈ P.b → p ∈ w, | w | = | S + O | }.

NIF uses the data harvested by DISCO to support other technologies including ontological mappings, horizontal integration, and data update alerts to help develop an evolvable global scientific portal architecture in support of neuroscience research.

Designing the data integration processes involves creating stage-related conceptual and logical data integration process models and designing stage-related physical data integration process models, stage-related source to target mappings and the overall data integration workflow.

The understanding of the genetic component of autoimmune etiology will become more complete as fine-mapping and sequencing data become readily available.

Therefore, edges represent the work flow/information flow when creating mappings and the resulting data are used again as input for a mapping function.

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