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The second fitness function is nonlinear ω = α +βz +(γ/2)z 2, which represents stabilizing or disruptive selection. [1] [5] The quadratic regression (γ) is the selection gradient, ω is the fitness of a trait value z, and α is the y-intercept of the fitness function. Here, individuals with intermediate trait values may have the highest ...
A non-vertical line can be defined by its slope m, and its y-intercept y 0 (the y coordinate of its intersection with the y-axis). In this case, its linear equation can be written = +. If, moreover, the line is not horizontal, it can be defined by its slope and its x-intercept x 0. In this case, its equation can be written
In enzyme kinetics, a secondary plot uses the intercept or slope from several Lineweaver–Burk plots to find additional kinetic constants. [1] [2]For example, when a set of v by [S] curves from an enzyme with a ping–pong mechanism (varying substrate A, fixed substrate B) are plotted in a Lineweaver–Burk plot, a set of parallel lines will be produced.
An example of a Lineweaver–Burk plot of 1/v against 1/a In biochemistry , the Lineweaver–Burk plot (or double reciprocal plot ) is a graphical representation of the Michaelis–Menten equation of enzyme kinetics , described by Hans Lineweaver and Dean Burk in 1934.
The plot is occasionally attributed to Augustinsson [5] and referred to the Woolf–Augustinsson–Hofstee plot [6] [7] [8] or simply the Augustinsson plot. [9] However, although Haldane, Woolf or Eadie were not explicitly cited when Augustinsson introduced the versus / equation, both the work of Haldane [10] and of Eadie [3] are cited at other places of his work and are listed in his ...
Graph = with the -axis as the horizontal axis and the -axis as the vertical axis.The -intercept of () is indicated by the red dot at (=, =).. In analytic geometry, using the common convention that the horizontal axis represents a variable and the vertical axis represents a variable , a -intercept or vertical intercept is a point where the graph of a function or relation intersects the -axis of ...
The adjoint state method is a numerical method for efficiently computing the gradient of a function or operator in a numerical optimization problem. [1] It has applications in geophysics, seismic imaging, photonics and more recently in neural networks. [2] The adjoint state space is chosen to simplify the physical interpretation of equation ...
It has also been called Sen's slope estimator, [1] [2] slope selection, [3] [4] the single median method, [5] the Kendall robust line-fit method, [6] and the Kendall–Theil robust line. [7] It is named after Henri Theil and Pranab K. Sen , who published papers on this method in 1950 and 1968 respectively, [ 8 ] and after Maurice Kendall ...