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We are searching the key to understand life – this is how bioinformatics is oriented nowa­

days! It has evolved from data processing, just the assistant and auxiliary science for large

amounts of data, to now establish quantitative theoretical biology. For the first time, theo­

ries about something as complex as living beings no longer remain pure theory, but are

directly verifiable and measurable, and have already led to remarkable results and prog­

ress – from drugs against cancer and HIV to new insights, for example into the exciting

question of why our cells and we age.

Nevertheless, my main motivation for studying medicine and later becoming a bioin­

formatician was not so much the prospect of ploughing through large amounts of data, but

the fascination that biology has always had for people, the eternal questions about the key

to the language of life, about the “water of life” that heals everything. I wanted to recog­

nize and understand what holds us together in our innermost self, that is, how our con­

sciousness and our brain function. Tracing these great questions is precisely the purpose

of this book. Because today’s bioinformatics is doing this to an increasing extent, and

because one can also start from very small, simple examples, we will begin with these. We

provide case-based examples for each chapter and a tutorial in the appendix for you to play

with and discover for yourself. The new English edition 2021 brings everything up to date

and adds further important aspects.

The unbelievable has happened silently: Whereas before the computer was just a stupid

data storage device, new insights into life and the world and ourselves are now emerging

in simulations. This is only possible because life itself is not dead and is permeated by

numerous recognition processes. These are, for example, key-lock relationships between

molecules, but also memory and molecular languages at all levels of life. We want to

explore this in more detail here, first looking at the “how” of bioinformatics, in order to

then better understand in Part II why bioinformatics is so successful right now – similar to

Part I

How Does Bioinformatics Work?