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Next, one can compare the quality of different signal sources: For example, the infor
mation value is very low if the same character is always sent, but very high if very different
characters are always sent in a new sequence, such as a radio station.
After all, you have to take into account what it looks like inside living cells: Countless
reactions take place, there is a lot of hustle and bustle. Therefore, biological signals are
often amplified in signal cascades, so that one can still understand the signal despite the
“noise” (all the other reactions and signals taking place). The quality of the signal depends
on the ratio of signal to background noise (signal-to-noise). Shannon has set up a whole
theory on how communication via communication channels can run as optimally as pos
sible despite interference.
If the bioinformatician wants to model and better understand cell growth, differentia
tion or the death of cells, these theories are taken into account and the amplification,
weakening and modelling of cellular signals in different signalling cascades is investi
gated, as well as the weakening of kinase cascades by phosphatases, for example, so that
the cell stops growing again. At this complex level (function of the various signalling
cascades in the cell), a deeper understanding of the processes surrounding cell growth and
cell differentiation is then indeed possible.
7.2
The Different Levels of Coding
7 How to Better Understand Signal Cascades and Measure the Encoded Information