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Self-Determination and Participation (Ad 2 and 6)

Self-determination, participation and social diversity are supported by open source pro­

grams, joint development projects, among other things. In general, it is simply important

to be responsive to the user and to listen to feedback in self-developed bioinformatics

software.

Transparency and Clarity (Ad 3, 4 and 10)

Where does my data come from? What is its quality? Where do my conclusions come

from? Indication of all sources! These are general principles (“good scientific practice”)

and mean, for example in bioinformatics and also in the sense of the Manifesto, that the

data are freely accessible and so are the programs. In the best case, this also includes the

source code. However, this also depends on whether the source code is being further devel­

oped. In this case, it is important to make at least the executable freely accessible and to

explain transparently in a tutorial what the program does. The same applies to bioinfor­

matics articles: As a reader, you should be mature and really understand the article, and as

an author, you should make an effort to present the unfortunately mostly quite complex

subject matter as clearly and transparently as possible.

Free Working and Collaborative Coordination on the Network (Ad 5 and 8)

An easy start is to use https://www.startpage.com/ as a browser, which does not immediately

pass on all data to Google etc.. But you should generally use “free browsers”, delete cookies

regularly and use a new web browser from time to time. Digital assistants and coordina­

tion tools (Ad 8) we constantly explain here with regard to bioinformatics and a lot is direct

analysis software (i.e., a digital assistant for bioinformatics). But databases also help to coor­

dinate activities. But bioinformatics in particular has real coordination tools, such as the R

community, which jointly writes the R language, but especially numerous R programs for

statistical and bioinformatics analyses, or the numerous collaborations on the GNU project

and other open source activities (Biojava, Bioperl, etc.). The best example is Wikipedia,

which also attracts a steadily increasing share of bioinformatics wikis (e.g., www.wikidata.

org or introductory https://de.wikipedia.org/wiki/Transkriptionsfaktor).

Conclusion

• We use the computer as a tool to better understand life. Bacteria are already mar­

vels of survival, efficiency and vitality. But with the help of bioinformatics, we

can understand a little better how these fantastic feats work, whether we admire

more the adaptation (phylogeny, sequence analysis), the metabolism (metabolic

modelling, enzyme databases) or the regulation of these adaptations (systems

biology). Convincing results are drug design, for example in infectious diseases

and cancer, but also progress in brain modelling.

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16  Bioinformatics Connects Life with the Universe and All the Rest