1.1 What is Bioinformatics?

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mitted, received, stored, processed, and interpreted in biological systems” or, more

succinctly, “the application of information science to biology”.

The emergence of information theory by the middle of the twentieth century

enabled the creation of a formal framework within which information could be quan-

tified. To be sure, the theory was, and to some extent still is, incomplete, especially

regarding those aspects going beyond the merely faithful transmission of messages, in

order to enquire about, and even quantify, the meaning and significance of messages.

In parallel to these developments, other advances, including the development

of the idea of algorithmic complexity, with which the names of Kolmogorov and

Chaitin are associated, allowed a number of other crucial clarifications to be made,

including the notion that randomness is minimally informative. The DNA sequence

of a living organism must depart in some way from randomness, and the study of

these departures could be said to constitute the traditional core of bioinformatics.

Although those who argue about the primacy of genes and their immortality might

disagree, biology is, ultimately, about organisms and a set of genes cannot even be

said to specify an organism. In order to survive—and if it did not it would no longer

be alive—an organism must continuously adapt to its environment. Phylogenetic

adaptation, in which the organism’s genes are modified in its descendants, is only one

part of the adaptive survival strategy. Equally indispensable is ontogenetic adaptation,

which involves networks of control and communication within the organism. A

structurally evident example of such a network is the nervous system, ² of which the

simplest example is perhaps the nematode worm C. elegans, but even the simplest

unicellular organisms have signalling networks based on molecular interactions, and

such networks are also found in all higher organisms, including plants. ³ Shannon’s

theory is directly applicable to flows of information in the channels that connect the

nodes of these networks, and bioinformatics is also concerned with the information

processing that takes place within the nodes, with the overall architecture of the

networks. Given the relative ease with which DNA may be reliably sequenced, it is

understandable that deciphering the message of DNA has been the traditional core of

bioinformatics, but with the accumulation of relevant experimental data, elucidating

the architecture and operation of the signalling networks is becoming another core

of bioinformatics.

Alongside information theory, cybernetics developed as a distinctive science at

around the same time and largely within the same constellation. Its definition is well

conveyed by the subtitle of Wiener’s eponymous book (1948): “the study of control

and communication in the animal and the machine”. ⁴ The word itself was coined

by Ampère (as cybernétique) more than a century earlier. It is derived from the

Greek kappa upsilon beta epsilon rho nu eta tau zeta sigmaκυβeρνητζσ, meaning steersman, from which we get our Latin gubernetes,

2 The nervous system provides a good example of the inability of genes to specify essential features

of an organism. As Érdi and Barna have remarked (1984) the neural connexions are not specified,

but an algorithm to select favourable connexions is given genetically.

3 See, e.g., Thellier (2017).

4 Second-order cybernetics explicitly includes the observer within what is being studied (Heylighen

and Joslyn, 2001).