Symbolic computation in biology

From Pathway Databases: A Case Study in Computational Symbolic Theories by Peter Karp in Science magazine in 2001:

One lesson for computer scientists provided by pathway DBs (and by other bioinformatics applications) concerns the importance of DB content to solving computational problems. Most computer scientists focus their attention on algorithms, thinking that the best way to solve a hard computational problem is through a better algorithm. However, for problems such as predicting the pathway complement of an organism from its genome, or predicting metabolic products that an organism can produce from a given growth medium, I know of no algorithms that can solve these problems without being coupled with an accurate and well-designed pathway DB.

Threads are evil

The docs for Sqlite, under the heading "Threads are evil", pointed me to a paper by Edward A. Lee of UC Berkeley called The Problem with Threads.

Concurrency in software is difficult. However, much of this difficulty is a consequence of the abstractions for concurrency that we have chosen to use. The dominant one in use today for general purpose computing is threads. But non-trivial multi-threaded programs are incomprehensible to humans.

Lee argues that threads are wildly nondeterministic by default, while "nondeterminism should be judiciously and carefully introduced where needed, and should be explicit in programs."