1. Things I'm Glad I Learned

   Skills, concepts, techniques, and models

   WARNING: This post was written with haste and therefore contains all kinds of typos, spelling errors, grammatical issues, and delusions of grandeur, wisdom, and writing ability.

   This post is intended as a living document—a gratitude journal of sorts—of some things that I'm glad I learned. I expect many of the items on this list will be relevant to computation biology, but that may change in the future.

   The big idea is that for every item on this list I am (A) glad that someone introduced me to it, and (B) think more people should know about it. This post is my chance to "pay it backwards", as it were; maybe someone else will be grateful for something they find for the first time on this list.

   It may also double as an inspiration list for future posts.

   My goal is to write a small blurb for each item …

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2. Even pathogens hate a cheater

   I would like to apologize for the long delay since my last post. The excuse (I keep telling myself) is that, having already written too many computational articles, it was time to prove that I could write about biology too. Unfortunately I'm not nearly as good at reading the literature as I should be. Anyway, it's done. You can stop complaining now.

   One barrier to engineering bacteria for biofuel production or any other human endeavor is that evolutionary rates are scaled by population sizes and growth rates. For an organism with massive population sizes (trillions of individuals or more) and doubling times on the order of hours, evolution can occur quite quickly. Genetic variants within the population which are capable of growing faster will quickly take over. For an organism which is, for example, wasting a huge fraction of its energy producing your future gasoline, you can bet this months …

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