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8

When Does the Computer Stop Calculating?

Abstract

The question of when a bioinformatics problem will be completed is difficult to answer

for problems with built-in combinatorics. Alan Turing generally modeled all comput­

able problems using the Turing machine, an idealized abstract computer. All non-­Turing

computable problems cannot be solved by computers and remain tasks for humans.

Many particularly interesting problems in bioinformatics are NP (nondeterministic

polynomial complexity) problems, such as protein structure prediction and most net­

work and signal computation or image processing. In general, more powerful comput­

ers, the bundling of many computer nodes (parallelisation) and application-specific

chips can also directly increase computer performance, for example with omics data.

We remember that bioinformatics analyses biological data with programs (Sect. 2.1), col­

lects them in databases (Sect. 2.2) and then maps the biological relationships in models.

But how good are bioinformatic models? Well, bioinformatics tries to use computers to

make “good” and comprehensible biology. One can have fundamental reservations about

this. After all, life is a quality rather than a quantity. Experiences are not seldom simply

indescribable, and also a bacterium or also your own mind and even the brain are not sim­

ply a kind of chip (bacterium) or supercomputer (we ourselves). We are infinitely much

more, and who cannot understand this at all, should now go to a good theater play (no

cinema effect, it is better to experience this “live”) or talk for a few minutes with a patient

in a psychiatric ward, then may be he will better fathom what we want to say.

© Springer-Verlag GmbH Germany, part of Springer Nature 2023

T. Dandekar, M. Kunz, Bioinformatics,

https://doi.org/10.1007/978-3-662-65036-3_8