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Well I guess that depends on what you're doing within you're research. In bioinformatics knowing about, say, functional programming and parallel algorithms cou
by Lio 14y ago
Well I guess that depends on what you're doing within you're research.
In bioinformatics knowing about, say, functional programming and parallel algorithms could be really useful where data coming out of sequencers is growing faster than Moore's law can keep up, if you want to scale across many cores as efficiently as possible.
Or graph theory, or... any number of useful techniques waiting for an application.
- dalke 14y agoCertainly. But most aren't so inclined. Most need a way to glue together existing components. For example, "make a web connection to X, call command-line program Y, and use a shared-library extension to do Z. Plot in Excel." The result might be very useful scientifically, and it's definitely programming, but there's no real reason to learn about lambdas, s-expressions, and monads.