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In the field of molecular biology, gene expression profiling is the measurement of the activity (the expression) of thousands of genes at once, to create a global picture of cellular function. These profiles can, for example, distinguish between cells that are actively dividing, or show how the cells react to a particular treatment.
The Multi-Omics Profiling Expression Database (MOPED) was an expanding multi-omics resource that supports rapid browsing of transcriptomics and proteomics information from publicly available studies on model organisms and humans. [2]
Tools for querying and downloading gene expression profiles are provided. Human Protein Atlas (HPA [10]): a public database with expression profiles of human protein coding genes both on mRNA and protein level in tissues, cells, subcellular compartments, and cancer tumors. Legume Information System (LIS): genomic database for the legume family [11]
Profiling results can be used to guide the design and optimization of an individual algorithm; the Krauss matching wildcards algorithm is an example. [5] Profilers are built into some application performance management systems that aggregate profiling data to provide insight into transaction workloads in distributed applications.
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Serial Analysis of Gene Expression (SAGE) is a transcriptomic technique used by molecular biologists to produce a snapshot of the messenger RNA population in a sample of interest in the form of small tags that correspond to fragments of those transcripts.
In information science, profiling refers to the process of construction and application of user profiles generated by computerized data analysis. This is the use of algorithms or other mathematical techniques that allow the discovery of patterns or correlations in large quantities of data, aggregated in databases .