Microarray data is usually applied for the comparison of gene expression profiles under different conditions. But we have to make sure what we are comparing is really comparable. So, to bring the data under common frame normalization is done. In technical terms, normalization of microarray data removes both random and systematic biases.
[Source: Guide To Analysis of DNA Microarray Data]
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No, it can be array, structure or union as well.
Sometimes.
An array is used to store data having the same data type.
Normalization is a process of reducing redundancies of data in a database. If you don't normalize you will have to repeat data entry.
It makes it easier to analyze the data sets from separate experiments if you normalize. The curves themselves should approximate each other regardless of the initial parameters. If you normalize first the % recovery (immobile/mobile estimates) can be taken right form the curve without post analysis. Tau should be approximately the same regardless of normalization.
All elements of any given array must satisfy the same data type requirement, meaning they should be of the same data type for the array to be well-defined and properly utilized.
That rather depends on the underlying type. For any given type T, an array of type T is user-defined if T is user-defined, otherwise it is built-in. For example: #include<string> // required to use std::string std::string s[42]; // user-defined array int i[42]; // built-in array Here, s is a user-defined array because std::string is a user-defined type, whereas i is a built-in array because int is a built-in type.
An array.
an array is a collection of the same data type.
An array is a collection of related data elements of same type.Structure can have elements of different types.An array is a derived data type.A structure is a programmer-defined data type.A struct can contain multiple data types, whereas an array can not.
An un-normalized database contains a random population of data that has not been organized into small stable data files