(Question has been edited for specificity based on feedback. I followed the guidelines StackExchange recommended to me: Are resource recommendations allowed?)
Within biophysics, I'm looking to build up understanding of statistical mechanics, especially protein folding, DNA mechanics, and cell biology, and of multiscale modeling, especially cell-to-tissue.
I do well with examples that I can follow along, or problem sets with answer keys to check, including problems assigned in Python, R, MATLAB, Mathematica, or C++. Differential equations, complex analysis, topology, probability, and measure theory are all fair game, but I'm also hoping to gain intuitive understanding, so I'm open to both proof-light undergraduate books for intuition and fully theoretic graduate books for rigor.
I have seen:
However, my background is very lopsided and I'm not sure those resources would fit, and the questions are also a few years old – which I thought might matter in a biology-based field, but I could be wrong.
I have a math BS/MS where I studied dynamical systems, and I did a statistics MS/PhD working on Bayesian MCMC computation in forensic genetics. While I assume I have sufficient mathematical background at least for a rudimentary introduction to the field, I have only ever taken a handful of basic science courses. As an undergrad I took a semester of Newtonian mechanics, a trio of biology courses, and a freshman science course that touched on chemistry and physics, but I assume that is hugely insufficient for a foundation in biophysics. However, I would prefer to learn from courses that teach things in a synergized way, if possible, to avoid multiple semesters of general physics, chemistry, and biology all taught separately. I understand if some separation is necessary to gain a foundation, but for career reasons I would rather learn the interaction of the fields from the start as much as possible.
I would appreciate textbook recommendations as well as video lecture series, if any are available.