The reason why CS analogies don't work very well is that molecular biology is very context driven, and we often don't know what the context is.
For example, in eukaryotes, the same piece of DNA can can produce different amounts of different proteins (i.e. with different amino acid sequences and different post-translational modifications), depending on things like DNA methylation (there's a number of different types), genomic location, accessibility, transcript methylation, multiple mRNA isoforms - the list goes on. A combination of these and other still unknown factors produces the final product, which may vary within a cell, between cells in a tissue, and between tissues.
Things behave consistently and predictability, except when they don't. Makes the field interesting and frustrating.
Analogies obviously don't hold for many cases. But it's a good entry point to explain some basic concepts such as the Central Dogma. I am a biologist who has to teach molecular biology to computer scientists in our Bioinformatics department. It was the only way to bridge the gap. Once we got it we could start on the more detailed stuff.
For example, in eukaryotes, the same piece of DNA can can produce different amounts of different proteins (i.e. with different amino acid sequences and different post-translational modifications), depending on things like DNA methylation (there's a number of different types), genomic location, accessibility, transcript methylation, multiple mRNA isoforms - the list goes on. A combination of these and other still unknown factors produces the final product, which may vary within a cell, between cells in a tissue, and between tissues.
Things behave consistently and predictability, except when they don't. Makes the field interesting and frustrating.