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Alternative online IC50 calculator (www.ic50.org) based on Python, NumPy, SciPy and Matplotlib; ELISA IC50/EC50 Online Tool (link seems broken) IC50 to pIC50 calculator; Online tool for analysis of in vitro resistance to antimalarial drugs; IC50-to-Ki converter of an inhibitor and enzyme that obey classic Michaelis-Menten kinetics
Interpretation is more complicated in mixed susceptibility populations. These are plotted as linear dimensions or squares of distances as a function of the natural logarithm of antibiotic concentration in the disks. The MIC is determined from the zero intercept of a linear regression fit through the data. [12]
Nowadays, the MIC is used in antimicrobial susceptibility testing. The MIC is reported by providing the susceptibility interpretation next to each antibiotic. The different susceptibility interpretations are: "S" (susceptible or responding to a standard dosing regimen), "I" (intermediate or requiring increased exposure), and "R" (resistant).
The breakpoint can be important in decision making [1] The figures illustrate some of the results and regression types obtainable. A segmented regression analysis is based on the presence of a set of ( y, x ) data, in which y is the dependent variable and x the independent variable .
Without hardware support (and in multitasking environments), debuggers have to implement breakpoints in software. For instruction breakpoints, this is a comparatively simple task of replacing the instruction at the location of the breakpoint by either: an instruction that calls the debugger directly (e.g. a system call, or int3 in case of x86) or
Python supports normal floating point numbers, which are created when a dot is used in a literal (e.g. 1.1), when an integer and a floating point number are used in an expression, or as a result of some mathematical operations ("true division" via the / operator, or exponentiation with a negative exponent).
The MZ test developed by Maasoumi, Zaman, and Ahmed (2010) allows for the simultaneous detection of one or more breaks in both mean and variance at a known break point. [ 4 ] [ 14 ] The sup-MZ test developed by Ahmed, Haider, and Zaman (2016) is a generalization of the MZ test which allows for the detection of breaks in mean and variance at an ...
If partitions are not known, the residual sum of squares can be used to choose optimal separation points. [5] However efficient computation and joint estimation of all model parameters (including the breakpoints) may be obtained by an iterative procedure [ 6 ] currently implemented in the package segmented [ 7 ] for the R language .