Study Group Bioinformatics
In September 2014, bioinformaticians in Germany united in the joint interest group Bioinformatics (Fachgruppe Bioinformatik (FaBI)). FaBI emerged from the respective groups of the four founding societies GI (German Informatics Society), DECHEMA (Society for Chemical Engineering and Biotechnology), GBM (Society for Biochemistry and Molecular Biology) and GDCh (German Chemical Society). In fall 2015, the GMDS (German Society for Medical Informatics, Biometry, and Epidemiology) joined FaBI. FaBI represents more than 750 members today and considers itself as a joint representation of interests of bioinformatics research in Germany and as an interlocutor for politics, economy, and society aiming at a strong informatics-based life science research.
Bioinformatics appliese methods from informatics to scientific problems in life sciences. Starting as a connecting discipline between informatics and the life sciences, bioinformatics became an independant sub-discipline over the last centuries.
High throughput experiments have become increasingly important in chemistry, biology, medicine and pharmacology. They result in huge amounts of complex data in the areas of genome squencing, expression profiles of proteins and structure elucidation of proteins as well as interactions between biomolecules (proteins, RNA, low molecular-weight compounds). Bioinformatics develop software tools to prepare, evaluate and analyze this data. Therefore, bioinformatics take a key role in the modern life sciences: only with the use of sophisticated computer systems knowledge can be gained from the huge amounts of data and applied to predict biological phenomena.
As a basis for their work, FaBI has agreed on the following definition of bioinformatics as the foundation of their work:
"Bioinformatics is an interdisciplinary science. By bioinformatics we understand the research, development and application of computer-based methods used to answer biomolecular and biomedical research questions. Bioinformatics mainly focusses on models and algorithms for data on the molecular and cell-biological level, for example on:
- genomes and genes
- gene and protein expression and -regulation,
- metabolic and regulatory pathways and networks,
- structures of biomacromolecules, esp. DNA, RNA and proteins,
- molecular interactions between biomacromolecules and between biomacromolecules and other substances like substrates, transmitters, neurotransmitters and inhibitors as well as
- molecular characterization of ecological systems."