BioNumerics
Trend Data Types Module
For an overview see
BioNumerics
The Trend Data Types module analyzes
series of readings of a changing factor, which define a trend.
Examples are the kinetic analysis of metabolic and enzymatic activity,
real-time PCR, or time-course experiments using microarrays. Although
multiple readings per experiment are mostly done in function of time,
they can also depend on another factor, for example in function of
different concentrations.
Twelve different curve fit models, including Logistic growth, Gompertz,
Gaussian, Hyperbolic, Power, Exponential, etc. from which specific
parameters can be derived and used for analysis and comparison. User
can add custom parameters such as statistic parameters, slopes, and
values at fixed X.
Comparison and clustering can be done on a selected parameter or a
combination of multiple parameters. Comprehensive curve plotting
tools.
For further details please download
the BioNumerics/GelCompar pdf brochure.
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