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Attractor  Limited system state that pulls nearby system states into this stable basic state,

e.g. health (immune system can cope with slight infections or pulse, returns to normal after

exertion; however, if the disturbances are too great, then the stable system state changes

and one becomes ill; again a new attractor that can last longer until one becomes

healthy again).

Babbage Test  Test for artificial intelligence in which outside people are asked to distin­

guish between a human and a computer (both undercover). If the computer succeeds in

deceiving people into thinking it is human, then the computer has artificial intelligence.

Big Data  Refers to the flood of large amounts of data generated in the course of modern

experimental methods, which, for example, have to be analysed bioinformatically in order

to gain new and exciting insights.

BiNGO  Cytoscape plugin that identifies overrepresented biological functions (with

p-value and corresponding genes) using Gene Ontology grouping in a network (see also

Gene Ontology, GO). 

Bioinformatics  Bioinformatics, or computational biology, is the study of biological

questions using computers. In this process, information (“data”) and findings (“models”)

about organisms are collected (in databases), analysed (by experts, the bioinformaticians,

who use various computer programs for these analyses) and reproduced in models (“simu­

lations”). Essential properties (system properties) for the biological phenomenon under

investigation are worked out (“systems biology”). Biologists often focus on plants and

animals, fungi or lower organisms (bacteria, viruses). The latter are easier to understand

and thus to reproduce in the computer, e.g. the metabolism of bacteria or the reproduction

of viruses. For doctors, other medical professions (human geneticists, molecular physi­

cians) and many interested biologists, however, the focus is on humans. Both health

(“physiology”) and disease are described in detail. The starting point of many bioinfor­

matic studies is the flow of genetic information from DNA (the genome) through tran­

scription (in higher cells in the cell nucleus) to RNA and after translation in the ribosome

via the genetic code to proteins. Programs and software are used to study biological func­

tion. This is done, for example, by means of sequence analyses in order to obtain informa­

tion about a pathogen, but also, for example, to obtain differences between the organisms

involved (e.g. humans and parasites) by genome comparisons. In the case of proteins, but

also regulatory and catalytic RNA, the analysis of the structure helps to better decipher

their function (protein structure analysis, RNA analysis). It is also possible to create meta­

bolic networks and compare them with each other, and finally, for example, to calculate

drugs for important proteins in the parasite that optimally block the parasitic protein but

are tolerated by humans. Signalling networks can also be modelled and studied to better

understand cell maturation (differentiation, embryology) and to better combat or prevent

diseases such as cancer, heart failure and stroke (together over 75% of all causes of death).

Predictions are verified with the help of experimental data. In the meantime, other mole­

cules can also be measured intensively (more complex), such as metabolites (e.g. lipids,

sugars, vitamins, cofactors), proteins, nucleotides. Also new is an increasing amount of

18  Glossary