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 Global Health  
 Course

BUA Modules

Global Health

0609a_pool
Here you can find the BUA Modules offered in the subject area Global Health.

  • Evolutionary Medicine

    0609aA1.2

    BUA Module with 5 credit points: module description (German)

    Pre-requisites: Deeper knowledge in the life sciences, primarily acquired through modules attended in life sciences and related fields during the first four semesters, or acquired during a completed bachelor degree.

    • 23410a Lecture
      L Evolutionary Medicine (Sophie Armitage, Marcus Fulde, Anne-Maren Herzog, Michael Hochberg, Benedikt Kaufer, Dino McMahon, Jessica Metcalfe, Katja Nowick, Charlotte Rafaluk, Jens Rolff)
      Schedule: semester-long; 22.10.2025 - 04.02.2026; Wed; 16:30 - 19:00 (Class starts on: 2025-10-22)
      Location: 312 (Königin-Luise-Str. 2 / 4)

      Information for students

      Additionally 4 seats for MSc Biochemistry, 2 seats for veterinary medicine and 8 seats for BUA-students.


      Additional module information: Evolutionary Medicine 

      UN Sustainable Development Goals (SDGs): 3

      Additional information / Pre-requisites

      Deeper knowledge in the life sciences, primarily acquired through modules attended in life sciences and related fields during the first six semesters, or acquired during a completed bachelor degree.

      Comments
    • 23410b Seminar
      S Evolutionary Medicine (Sophie Armitage, Marcus Fulde, Anne-Maren Herzog, Michael Hochberg, Benedikt Kaufer, Dino McMahon, Jessica Metcalfe, Katja Nowick, Charlotte Rafaluk, Jens Rolff)
      Schedule: semester-long; 22.10.2025 - 04.02.2026; Wed; 16:30 - 19:00 (Class starts on: 2025-10-22)
      Location: 312 (Königin-Luise-Str. 2 / 4)

      Information for students

      Additionally 4 seats for MSc Biochemistry, 4 seats for veterinary medicine and 8 seats for BUA-students.


      Additional module information: Evolutionary Medicine  

      UN Sustainable Development Goals (SDGs): 3

      Additional information / Pre-requisites

      Deeper knowledge in the life sciences, primarily acquired through modules attended in life sciences and related fields during the first four semesters, or acquired during a completed bachelor degree.

      Comments

  • Current Research Topics in Bioinformatics

    0609aA1.3

    BUA Module with 5 ECTS credit points: module description (p. 349) 

    To complete the module please select one of the following seminars. Please contact the respective lecturers to find out what prior knowledge of the subject is required for successful participation.

    • 19335011 Seminar
      Seminar: Networks, dynamic models and ML for data integration in the life sciences (Katharina Baum, Pascal Iversen)
      Schedule: Di 14:00-15:30 (Class starts on: 2025-10-14)
      Location: T9/137 Konferenzraum (Takustr. 9)

      Comments

      Research seminar of the group Data Integration in the Life Sciences (DILiS). Also open for seminar participation in the Master's program, online participation possible. Please refer to the current schedule on the whiteboard!

      The seminar offers space for the discussion of advanced and integrative data analysis techniques, in particular presentations and discussion of ongoing or planned research projects, news from conferences, review and discussion of current literature and discussion of possible future teaching formats and content, and presentations, as well as final presentations on theses or project seminars. The seminar language is mostly English. Interested students are welcome to attend and drop in without obligation or present a topic of their own choice of interest to the working group as in a usual seminar. Please note: Individual dates may be canceled or postponed. Please contact me in case of questions (katharina.baum@fu-berlin.de)!
    • 19402311 Seminar
      Seminar: Deep Learning for biomedical applications (Vitaly Belik)
      Schedule: Mo 16:00-18:00 (Class starts on: 2025-10-13)
      Location: T9/051 Seminarraum (Takustr. 9)

      Additional information / Pre-requisites

      Master students with a background in physics, chemistry, bioinformatics or computer science

      Comments

      Recent developments in the area of machine learning due to availability of data and computational power promise to revolutionize almost every area of science. The driving technology behind this advancement is deep learning – a machine learning technology based on artificial neural networks consisting of many layers. Deep learning is capable of processing huge amount of data of different nature and already outperforming humans in many decision-making tasks. Biomedical research became now a source of large heterogeneous data, i.e. images, video, activity sensors, omics and text data. Leveraging the opportunities of this deep learning technology in the biomedical field requires particular set of skills combining thorough knowledge of necessary algorithms, specifics of biomedical data and designated programming tools. In this course we aim to offer students with background in computer science an opportunity to acquire the above skills to be able to deploy deep learning technology with a focus on biomedical applications. The course is structured as a seminar, where students under extensive guidance of instructors read fundamental books and recent research articles on deep learning, learn necessary programming tools, and produce their own implementations of computational pipelines in case studies using already published or original data. Starting from fundamental aspects of deep learning we aim to cover its applications to e.g. image data, time series data, text data, complex networks.

       

       

      Suggested reading

      [1] Andresen N, Wöllhaf M, Hohlbaum K, Lewejohann L, Hellwich O, Thöne- Reineke C, Belik V, Towards a fully automated surveillance of well-being status in laboratory mice using deep learning: Starting with facial expres- sion analysis. Plos One, 15(4):e0228059, (2020) https://doi.org/10.1371/ journal.pone.0228059

      [2] Jarynowski A, Semenov A, Kamiński M, Belik V. Mild Adverse Events of Sputnik V Vaccine in Russia: Social Media Content Analysis of Telegram via Deep Learning. J Med Internet Res 2021;23(11):e30529 https://doi.org//10.2196/30529
    • 19402911 Seminar
      Journal Club Computational Biology (Knut Reinert)
      Schedule: Mo 14:00-16:00 (Class starts on: 2025-10-20)
      Location: T9/053 Seminarraum (Takustr. 9)

      Additional information / Pre-requisites

      Open for:

      Master and PhD students

      Comments

      Content:

      In this seminar we will present original work in Computational biology as well as progress reports from PhD students. Master students will either be assigend a paper, or present their MSc thesis plans and results, or report about their research internship. Credits are only awarded for the presentation of papers.

      Please sign up on the Whiteboard (open "Site Browser" and look forJournal Club).

      Suggested reading

      aktuelle Publikationen aus der Forschung
    • 19404611 Seminar
      Open science, data handling and ethical aspects in bioinformatics (Thilo Muth)
      Schedule: Do 14:00-16:00 (Class starts on: 2025-10-16)
      Location: T9/051 Seminarraum (Takustr. 9)

      Comments

      The main objectives of this seminar are (1) to introduce fundamental methods of data handling in bioinformatics research with a particular focus on lab management systems, containerized frameworks and software workflow systems, (2) to provide a general overview of open science, sustainable software development, information security and data protection and (3) to discuss ethical issues, chances and risks with regard to fundamental research and personalized medicine.

      Planned topics are as follows:

      • Open vs. closed Science: chances and risks of open science. Open access and traditional publishing.
      • Sustainable software development and reproducible research: open data and open source, code repositories, maintainability of software and code in the sciences
      • Laboratory information management systems: sample management, integration of instruments and application, data exchange
      • Bioinformatic workflows: Galaxy, Snakemake and KNIME
      • Containerized frameworks: Advantages of using Docker, Bioconda etc.
      • Information security and data protection: securing personalized data, relevance for data analyses in research, efficient handling guidelines of data security, potential issues with open science
      • Ethical issues, chances and risks of omics research: immense opportunities when manipulating genome information, novel ethical questions need to be asked, „right not to know“, danger of discrimination against individuals or groups based on genetic differences

      Organisational note: During the first course at the beginning of the semester, the aforementioned topics will be briefly introduced and course material (e.g. relevant publications) will be provided. In the second course, topics will be assigned to the attendees of the seminar.
    • 19405911 Seminar
      Biochemical networks and disease (Jana Wolf)
      Schedule: Do 12:00-14:00 (Class starts on: 2025-10-16)
      Location: T9/053 Seminarraum (Takustr. 9)

      Comments

      Molecular metabolic, signaling and gene-regulatory networks form complex networks that underly the normal physiological functioning of the cell. Various perturbations within these networks have been described in diseases. We will here use original papers to study and discuss how perturbations can be implemented in models and how they change the network characteristics. We will focus on dynamic models described by ordinary differential equations.
    • 19406411 Seminar
      Journal Club: Public Health Data Science (Max von Kleist)
      Schedule: Mittwochs 10-12, ab der zweiten Semesterwoche
      Location: online

      Comments

      In this seminar, current research in the field of data-driven public health science, as well as the progress reports of PhD students and post-docs, will be presented. Master's students will present either an assigned journal article or their master's thesis, or they will report on their research internship. Credits will be awarded for article presentations only.

      Schedule: online, by arrangement. The link to participate can be obtained from the lecturer.
    • 19406611 Seminar Cancelled
      Journal Club: Biomedical Data Science (Katharina Jahn)
      Schedule: Di 16:00-18:00 (Class starts on: 2025-10-14)
      Location: A3/SR 115 (Arnimallee 3-5)

      Comments

      In this seminar, we study current research publications in biomedical data science. Master students either present a research article, or their master thesis, or they present about their research internship. Credit points can only be earned for the presentation of research articles.