(Inspiration drawn from Vilela et al 2010) Microtubules are tubular structures in the cytoplasm of cells that can elongate and form more complex structures but can undergo catastrophic collapse as they get longer within the cell. Suppose the rate of catastrophe (per minute) was thought to be an exponential model of relative length of the microtubules (fraction of cell half-length) based on the following data: Fraction of Cell Half-Length 0.21 0.28 0.34 0.42 0.47 0.52 0.55 0.59 0.62 0.71 0.79 0.81 0.85 0.92 0.98 Catastrophe Rate 0.1053 0.1344 0.1486 0.1703 0.1900 0.2110 0.2182 0.2331 0.2557 0.2990 0.3476 0.3587 0.3832 0.4371 0.4819
(Inspiration drawn from Vilela et al 2010) Microtubules are tubular structures in the cytoplasm of cells that can elongate and form more complex structures but can undergo catastrophic collapse as they get longer within the cell. Suppose the rate of catastrophe (per minute) was thought to be an exponential model of relative length of the microtubules (fraction of cell half-length) based on the following data: Fraction of Cell Half-Length 0.21 0.28 0.34 0.42 0.47 0.52 0.55 0.59 0.62 0.71 0.79 0.81 0.85 0.92 0.98 Catastrophe Rate 0.1053 0.1344 0.1486 0.1703 0.1900 0.2110 0.2182 0.2331 0.2557 0.2990 0.3476 0.3587 0.3832 0.4371 0.4819
Advanced Engineering Mathematics
10th Edition
ISBN:9780470458365
Author:Erwin Kreyszig
Publisher:Erwin Kreyszig
Chapter2: Second-order Linear Odes
Section: Chapter Questions
Problem 1RQ
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Question
5.
(Inspiration drawn from Vilela et al 2010) Microtubules are tubular structures in the cytoplasm of cells that can elongate and form more complex structures but can undergo catastrophic collapse as they get longer within the cell. Suppose the rate of catastrophe (per minute) was thought to be an exponential model of relative length of the microtubules (fraction of cell half-length) based on the following data:
Fraction of Cell Half-Length |
0.21 | 0.28 | 0.34 | 0.42 | 0.47 | 0.52 | 0.55 | 0.59 | 0.62 | 0.71 | 0.79 | 0.81 | 0.85 | 0.92 | 0.98 |
Catastrophe Rate | 0.1053 | 0.1344 | 0.1486 | 0.1703 | 0.1900 | 0.2110 | 0.2182 | 0.2331 | 0.2557 | 0.2990 | 0.3476 | 0.3587 | 0.3832 | 0.4371 | 0.4819 |
Expert Solution
Step 1
The least-square regression technique uses a straight line (linear equation) to fit the dataset into the equation.
Using the properties of the logarithmic functions, it can be written that:
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