<p>[Some</a> people have been asking about BME 140](<a href=“http://talk.collegeconfidential.com/washington-university-st-louis/680161-washu-workload-3.html]Some”>http://talk.collegeconfidential.com/washington-university-st-louis/680161-washu-workload-3.html), and I didn’t want to hijack that thread, so I started this one instead.</p>
<p>There are 5 modules covered in BME 140. The specifics here are taken from the homework assignments, so I didn’t include anything that was only in the lectures. If you want a copy of files I have from this class, PM me; I don’t want to post them here, as I don’t think the administrators would like that.</p>
<li><p>Bioelectricity
<strong><em>* Action Potential (in cell membranes)
</em></strong><strong><em>* Nernst Equation/Nernst Potential
</em></strong><strong><em>* Goldman Equation (generalized form of Nernst equation; has a very long derivation and involves differential equations)
</em></strong><strong><em>* Donnan Equilibrium
</em></strong><strong><em>* Space charge neutrality
</em></strong><strong><em>* Ion concentration
</em></strong><strong><em>* Ion pumps
</em></strong>__ * Pump flux
_____<strong><em>* Superposition of potentials
</em></strong><strong><em>* Current produced by neurotransmitters
</em></strong><strong><em>* Fourier transform/series (difficult)
_</em></strong>* Neural networks
_<strong><em>* Georgopoulos Tuning Model
_</em></strong>* Impedance/force/pressure on middle ear (modeled as an acoustic impedance matcher)</p></li>
<li><p>Biomechanics
_<strong><em>* Stress/strain
</em></strong><strong><em>* Yield, ultimate, & failure stress/strain
_</em></strong>* Maxwell & Kelvin-Voigt material
____* Free body diagram of force on body parts</p></li>
<li><p>Biostatistics
_<strong><em>* Population/sample mean, standard deviation, & standard error
_</em></strong>* T- & P-tests
_<strong><em>* Mann-Whitney Rank Sum Test
_</em></strong>* Bonferroni Correction</p></li>
<li><p>Biomolecular
_<strong><em>* Gold nanocubes
_</em></strong>* Red shift for various-shaped objects
_<strong><em>* Codons & genes
_</em></strong>* Amino acids
____* Enzyme kinetics (differential equations used here)</p></li>
<li><p>Biotechnology
_<strong><em>* PCR
_</em></strong>* mRNA
_<strong><em>* More codons & genes
_</em></strong>* More enzyme kinetics
_<strong><em>* Rayleigh scattering
_</em></strong>* Model for finding spherical cavity in proteins (don’t know its name)
_<strong><em>* MRI
_</em></strong>* Migration of cells into a graft (differential equations and [Gaussian</a> function](<a href=“http://en.wikipedia.org/wiki/Gaussian_function]Gaussian”>http://en.wikipedia.org/wiki/Gaussian_function) used here)</p></li>
</ol>
<p>The first two topics are pretty difficult, and take place before the withdraw date. There is one midterm, and it covers those two topics.</p>
<p>Biostatistics is a mini-module (1 lecture) and is essentially a rushed summary of the first semester of AP Statistics, for anyone who’s taken it. The last two topics are much easier, and the homework has little to nothing to do with the lectures.</p>
<p>
Calculus 3 is of some help, as you’ll learn about vectors and stuff, but really, I didn’t feel like I learned that much at all in Calculus 3, save the vector calculus at the end of the semester. Topics such as partial derivatives and Fubini’s theorem seemed self-explanatory to me. I don’t recall vector calculus being used in the class, but I’m sure that having Calculus 3 can’t help.</p>
<p>Either way, most of the math stuff you need to know that you don’t is from differential equations.</p>
<p>
Either way is fine if you have the motivation to do it. All you need to know from general physics is torque (which you should already know) and how to solve complicated free body diagrams.</p>
<p>Differential equations, on the other hand, will definitely be useful. I highly recommend teaching yourself differential equations if you are the type of person who feels the need to understand every step when a professor’s lecturing about something. Differential equations is an odd sort of topic; there are no particularly difficult or significant universal concepts. Instead, you just group differential equations into various types (order, linearity, homogeneity, etc.) and use specific algorithms to solve them; it’s often referred to as a cookbook course. I don’t think you will have much difficulty teaching it to yourself.</p>