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Conclusion and Summary
Abstract
Bioinformatics is now all the rage because of big data. However, computational biology
also uses computers to provide unprecedented valuable biology insights, which is our
main concern. With more and more new data and the application of data analysis to
fundamental biological questions that can only now be answered by these new data in
the first place, we will enter the fascinating new territory of modern molecular medi
cine and molecular biology in this century. With the help of bioinformatics this data
flood makes us more knowledgeable; without bioinformatics, we will rather drown in
the next big data wave.
In principle, bioinformatics is simple (Part 1): Sequence analyses, such as sequence
comparison with BLAST, allow the language of life to be deciphered, whereby DNA and
RNA sequences can be translated into proteins relatively easily with the computer.
Numerous programs look at protein sequences in particular. The ExPASy server of the
Swiss Bioinformatics Institute is important here. We learned about useful tools for RNA
analysis, such as the RNA Analyzer. Numerous DNA sequences, databases and many elec
tronic books, tips and programs for this purpose are available at the NCBI (National Center
of Biotechnology Information) as well as all important publications (MEDLINE). With
these techniques, we can detect viruses, determine the function of proteins, but also dis
cover new RNA molecules that play a role in cancer or heart failure, for example. In order
to model the metabolism of a cell, we need a list of all enzymes and metabolites that need
to be kept in balance within the cell. From this, the computer can then calculate all possi
ble metabolic pathways, and with a little more data (e.g., on gene expression), it is also
possible to determine flux levels. This makes it possible to find targets for antibiotics, but
also to better understand how bacteria grow, adapt to the environment or optimise the yield
© Springer-Verlag GmbH Germany, part of Springer Nature 2023
T. Dandekar, M. Kunz, Bioinformatics,
https://doi.org/10.1007/978-3-662-65036-3_17