IDK about papers per se, but as a computer scientist who took classes in bioinformatics, there are parallels. At the base level, cells are machines for construc

IDK about papers per se, but as a computer scientist who took classes in bioinformatics, there are parallels. At the base level, cells are machines for constructing proteins, and information on that process is encoded in DNA. Silicon uses 2 bits, DNA has 4 base pairs. Those base pairs groups in sets of 3 called a codon, kinda similar to a byte. Word size is normally a multiple of 8 for computers, but the 6 bit word in DNA is more than sufficient to cover the 20 amino acids, leaving room for both a stop sequence, and some rudimentary error correction -- a mistake in copying DNA somewhere might not end up changing the resulting protein. There's also a level of programmatic structure in terms of transcription promotors and gotos, and probably some level of conditionals. DNA is also special in that it can be read forwards or backwards, and the base pairing means you always have two potentially transcriptable sequences, each starting from one of 3 offsets. Imagine if busybox implemented all of coreutils in one binary by shifting the word alignment 1 bit to produce a completely different program. Finally, at the intracellular level, we have a whole host of message passing between cells using hormones and other signaling molecules, and organs like the pancreas that try to regulate a system using them. As far as 'computation' I don't think the system is Turing complete, and the systems aren't designed to answer decision problems, just construct things, possibly in response to an environmental factor.