Lab 1, Part A: 1-D Motion of an Amoeba.


This is the first week of a two-week lab studying cell motion. This week we will learn how to use Excel to analyze the 1-D motion of an amoeba from stop-motion images. Next week we will be analyzing videos of cell motion — wound closure, neutrophil motion, and bacteria motion — to determine whether or not a patient should be prescribed antibiotics. Clearly, the relative speeds of the wound closure, the neutrophils, and bacteria will affect this decision. Thus it becomes important that we learn how to quantify the motion of cells.

Materials and process

Grab this PDF containing a record of the movement of a Dictyostelium discoideum. The  motion is depicted as a sequence of outlines of the amoeba cell at 3.0-minute intervals. From the outlines, your task is to record and analyze the motion of the amoeba — specifically, the position, speed, acceleration.

Rather than do all of the math by hand, use a program (Excel or another spreadsheet, or a complete analysis program like MATLAB or python if you have access / experience with one) to do your calculations more quickly and efficiently. Today you will practice and master the skills necessary to transform a set of measurements into meaningful values (with proper units) and present them in comprehensible form. After today, you will all be expected to be experts at these skills, so take turns and help each other learn.

We, the cast and crew of IPLS, are officially agnostic as to what computational tools you should use. The main possibilities are

  • Excel (or a knockoff) is fast, easy and probably already familiar to you, but its analysis and graphing capabilities are pretty dismal. Excel is available to GA Tech students, and Google Sheets (free to everyone) has the same capabilities (and limitations).
  • Matlab is a powerful calculation / graphing program. If you’ve never used it it’s probably not worth learning it from scratch except that its graphing capabilities are fantastic and easy to use. Available to GA Tech students.
  • Python is similar to Matlab: very powerful and capable of elegant graphics, but probably not worth learning from scratch just to make graphs in this course. Free distributions are available.
  • Mathematica is designed for symbolic math. It’s pretty good for solving equations and plotting functions; harder to use to enter and plot sets of data points. Probably not worth learning just for its graphing capabilities. Available to GA Tech students.

Consult the main lab page for links to technical guides to Excel and graphing.

Lab writeup

Use this blank Word document as a template for your writeup. It’s really just a glorified cover page with some hints about what you might include.

At the end of the lab today, one member of your group will submit to WebAssign a document (word or PDF format) containing something like

  1. A description of how you calculated velocity and acceleration from your position data.
  2. A data table with your values of {t, x, v, a}
  3. A plot of x(t), v(t) and a(t)
  4. A very short paragraph reflecting on the numbers you measured / calculated

Your writeup will be reviewed by the TA for completeness / accuracy / conventional structure. Good attention to detail now will save you time later! Remember, your TA is here to help you with equipment and data processing, but the physics is up to you and your group!

Questions and directives
  1. Is the Dicty moving “fast” or “slow”? Define what you mean by “fast” and “slow” for something that’s 10000x smaller than you are, and be quantitative.
  2. Use standard units for your calculations: m, m/s, etc.
  1. You will have one fewer velocity data points than position data points, and one fewer acceleration data points than velocity data points. You will need to think about what times to associate with your (smaller number of) v and a points.

Originally developed by K. Moore, J. Giannini, B. Geller & W. Losert (Univ. of Maryland, College Park)