M.Sc. Bioinformatics

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What is the M.Sc. Bioinformatics all about?

Our 2-year Master’s degree offers a unique interdisciplinary training program that emphasizes the application of computational methods for interpreting complex biological data and understanding the underlying systems. It provides both in-depth theoretical knowledge as well as applied training in bioinformatics. The program is jointly conducted by the Department of Mathematics and Computer Science, the Department of Biology, Chemistry and Pharmacy, and the Charité Medical School.

The program was classified as a BUA joint degree program in June 2021. This classification is given to research-oriented cooperative degree programs of the partners of the Berlin University Alliance*, which are dedicated to topics of global significance and have a distinct interdisciplinary and international profile.

*The Berlin University Alliance is an alliance of Freie Universität Berlin, Humboldt-Universität zu Berlin, Technische Universität Berlin and Charité, funded by the Federal Ministry of Education and Research (BMBF) and the State of Berlin within the Excellence Strategy of the German federal and state governments.

This is a list of typical tasks that a bioinformatician performs on a daily basis:

  • Analyzing large molecular datasets such as microscopy data, genomic sequence data and proteomics data for clinical and basic research purposes.
  • Working with publicly accessible, commercial and proprietary genomic, proteomic and post-genomic databases.
  • Directing the work of technicians to support them in using bioinformatics tools and applications in areas such as proteomics, transcriptomics, metabolomics and clinical bioinformatics.

Tasks on a longer time-scale involve:

  • Developing new software applications and customize existing applications to meet specific scientific project needs.
  • Creating novel computational approaches and analytical tools, as required by research goals.
  • Consulting researchers from other disciplines to analyze problems, recommend technology-based solutions and determine computational strategies.
  • Keeping up to date with new algorithms, technology, instruments and software, by reading scientific literature and attending professional conferences.
  • Compiling data for activities such as gene expression profiling, genome annotation, mathematical modeling of biological systems and structural bioinformatics.

In this project, we will analyze a bio-medical data set from the UCI Machine Learning Database. We will use Exploratory Analysis and Machine Learning algorithms to understand the data and allow the samples' diagnoses.

Link to the pdf