BUA-Module
Global Health
0609a_pool-
Evolutionary Medicine
0609aA1.2BUA-Modul im Umfang von 5 ECTS-Leistungspunkten: Modulbeschreibung
Voraussetzungen: 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
Vorlesung
L Evolutionary Medicine (Sophie Armitage, Marcus Fulde, Anne-Maren Herzog, Michael Hochberg, Benedikt Kaufer, Dino McMahon, Jessica Metcalfe, Katja Nowick, Charlotte Rafaluk, Jens Rolff)
Zeit: semester-long; 22.10.2025 - 04.02.2026; Wed; 16:30 - 19:00 (Erster Termin: 22.10.2025)
Ort: 312 (Königin-Luise-Str. 2 / 4)
Hinweise für Studierende
Additionally 4 seats for MSc Biochemistry, 2 seats for veterinary medicine and 8 seats for BUA-students.
Additional module information: Evolutionary MedicineUN Sustainable Development Goals (SDGs): 3
Zusätzl. Angaben / Voraussetzungen
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.
Kommentar
Lecture Topics:
Introduction to Evolutionary Medicine: concepts of Evolution, going to the roots and why are we susceptible?
Lifestyle diseases (Katja Nowick);
Phage therapy (Hochberg);
Resistance evolution (Jens Rolff);
Antibiotic resistance (Marcus Fulde);
Tolerance (Sophie Armitage);
Parasite-host evolution (Charlotte Rafaluk);
Evolution of sexual differentiation;
Life history evolution (Jessica Metcalf);
Evolution of aging;
Evolution of viruses (Benedikt Kaufer);
Leaky vaccines (Dino McMahon)
Students will gain insights into evolutionary theoretic concepts and their application in modern medicine to understand health and disease. They will apply fundamental evolutionary concepts across disciplines and derive understanding why such cross disciplinary approach generates deeper knowledge in medicine.
Deeper insights into application of evolutionary theories in modern medicine through applied examples. Topics covered, include viral evolution, evolution of antibiotic resistance, evolutionary roots of lifestyle diseases, evolution of sexual differentiation, aging, and immunity and evolutionary arms races. The adjacent seminar trains to understand topic scpecific scientific publications, to discuss those topics in the context of the current scientific understanding and to present them in a scientific manner. Discussion of selected scientific articles, presentation of ideas, hypotheses and results.
Content:
The lecture and seminar cover general questions in evolutionary medicine. In the seminar and on online platforms current topics in evolutionary medicine will be presented, and critically and controvertially discussed.
Learning objectives:
The lecture links evolutionary theories to and their application in modern medicine. Thereby, the lecture helps to understand health, and how to prevent and treat disease. Topics covered, include viral evolution, evolution of antibiotic resistance, aging, and genetic variability in humans. The adjacent seminar trains to understand topic scpecific scientific publications and to discuss those topics in the context of the current scientific understanding. -
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)
Zeit: semester-long; 22.10.2025 - 04.02.2026; Wed; 16:30 - 19:00 (Erster Termin: 22.10.2025)
Ort: 312 (Königin-Luise-Str. 2 / 4)
Hinweise für Studierende
Additionally 4 seats for MSc Biochemistry, 4 seats for veterinary medicine and 8 seats for BUA-students.
Additional module information: Evolutionary MedicineUN Sustainable Development Goals (SDGs): 3
Zusätzl. Angaben / Voraussetzungen
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.
Kommentar
Lecture Topics:
Introduction to Evolutionary Medicine: concepts of Evolution, going to the roots and why are we susceptible?
Lifestyle diseases (Katja Nowick);
Phage therapy (Hochberg);
Resistance evolution (Jens Rolff);
Antibiotic resistance (Marcus Fulde);
Tolerance (Sophie Armitage);
Parasite-host evolution (Charlotte Rafaluk);
Evolution of sexual differentiation;
Life history evolution (Jessica Metcalf);
Evolution of aging;
Evolution of viruses (Benedikt Kaufer);
Leaky vaccines (Dino McMahon)
Students will gain insights into evolutionary theoretic concepts and their application in modern medicine to understand health and disease. They will apply fundamental evolutionary concepts across disciplines and derive understanding why such cross disciplinary approach generates deeper knowledge in medicine.
Deeper insights into application of evolutionary theories in modern medicine through applied examples. Topics covered, include viral evolution, evolution of antibiotic resistance, evolutionary roots of lifestyle diseases, evolution of sexual differentiation, aging, and immunity and evolutionary arms races. The adjacent seminar trains to understand topic scpecific scientific publications, to discuss those topics in the context of the current scientific understanding and to present them in a scientific manner. Discussion of selected scientific articles, presentation of ideas, hypotheses and results.
Content:
The lecture and seminar cover general questions in evolutionary medicine. In the seminar and on online platforms current topics in evolutionary medicine will be presented, and critically and controvertially discussed.
Learning objectives:
The lecture links evolutionary theories to and their application in modern medicine. Thereby, the lecture helps to understand health, and how to prevent and treat disease. Topics covered, include viral evolution, evolution of antibiotic resistance, aging, and genetic variability in humans. The adjacent seminar trains to understand topic scpecific scientific publications and to discuss those topics in the context of the current scientific understanding.
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23410a
Vorlesung
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Current Research Topics in Bioinformatics
0609aA1.3BUA-Modul im Umfang von 5 ECTS-Leistungspunkten: Modulbeschreibung (S. 349)
Zum Absolvieren des Moduls wählen Sie bitte eines der angebotenen Seminare. Bitte informieren Sie sich bei den jeweiligen Dozierenden, welche fachlichen Vorkenntnisse für die erfolgreiche Teilnahme nötig sind.
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19335011
Seminar
Seminar: Netzwerke, dynamische Modelle und ML für Datenintegration in den Lebenswissenschaften (Katharina Baum, Pascal Iversen)
Zeit: Di 14:00-15:30 (Erster Termin: 14.10.2025)
Ort: T9/137 Konferenzraum (Takustr. 9)
Kommentar
Forschungsseminar der Arbeitsgruppe Data Integration in the Life Sciences (DILiS). Auch offen für Seminarteilnahmen im Masterstudium, Online-Teilnahme möglich. Bitte entnehmen Sie Termine dem aktuellen Plan im Whiteboard!
Das Seminar bietet Raum für die Diskussion weiterführender und integrativer Datenanalysetechniken, insbesondere Vorträge und Diskussion von laufenden oder geplanten Forschungsprojekten, Neuigkeiten von Konferenzen, Besprechung aktueller Literatur und Diskussion möglicher zukünftiger Lehrformate und -inhalte, und Vorstellungen, sowie Abschlussvorträge zu Abschlussarbeiten oder Projektseminaren. Die Seminarsprache ist weitestgehend Englisch. Gern können interessierte Studierende teilnehmen und unverbindlich vorbeischauen oder ein selbst gewähltes Thema von Interesse für die Arbeitsgruppe vorstellen. Achtung: Einzelne Termine können ausfallen oder verschoben werden. Kontaktieren Sie mich gern für Fragen (katharina.baum@fu-berlin.de)!
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19402311
Seminar
Seminar: Deep Learning for biomedical applications (Vitaly Belik)
Zeit: Mo 16:00-18:00 (Erster Termin: 13.10.2025)
Ort: T9/051 Seminarraum (Takustr. 9)
Zusätzl. Angaben / Voraussetzungen
Zielgruppe: Masterstudierende der Physik, Chemie, Bioinformatik oder Informatik.
Kommentar
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.
Literaturhinweise
[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
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19402911
Seminar
Journal Club Computational Biology (Knut Reinert)
Zeit: Mo 14:00-16:00 (Erster Termin: 20.10.2025)
Ort: T9/053 Seminarraum (Takustr. 9)
Zusätzl. Angaben / Voraussetzungen
Zielgruppe:
Master- und PhD-Student*inn*en
Kommentar
Inhalt:
In diesem Seminar werden aktuelle Forschungsarbeiten der Bioinformatik sowie die Fortschrittsberichte der PhD-Student*inn*en vorgestellt. Master-Student*inn*en stellen entweder einen ihnen zugewiesenen Zeitschriftenartikel oder ihre Masterarbeit vor oder sie berichten über ihr Forschungspraktikum. Credits werden nur für die Präsentation von Artikeln vergeben.
Anmeldungen bitte über Whiteboard ("Site Browser" aufrufen und nach Journal Club suchen).
Literaturhinweise
aktuelle Publikationen aus der Forschung
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19404611
Seminar
Open science, data handling and ethical aspects in bioinformatics (Thilo Muth)
Zeit: Do 14:00-16:00 (Erster Termin: 16.10.2025)
Ort: T9/051 Seminarraum (Takustr. 9)
Kommentar
Siehe englische Beschreibung
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19405911
Seminar
Biochemical networks and disease (Jana Wolf)
Zeit: Do 12:00-14:00 (Erster Termin: 16.10.2025)
Ort: T9/053 Seminarraum (Takustr. 9)
Kommentar
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.
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19406411
Seminar
Journal Club: Public Health Data Science (Max von Kleist)
Zeit: Mittwochs 10-12, ab der zweiten Semesterwoche
Ort: online
Kommentar
In diesem Seminar werden aktuelle Forschungsarbeiten im Bereich der datengetriebenen public health Forschung, sowie die Fortschrittsberichte der PhD-Student*inn*en und Post-Docs vorgestellt. Master-Student*inn*en stellen entweder einen ihnen zugewiesenen Zeitschriftenartikel oder ihre Masterarbeit vor oder sie berichten über ihr Forschungspraktikum. Credits werden nur für die Präsentation von Artikeln vergeben.
Termin: online, nach Vereinbarung, der Link zur Teilnahme kann beim Dozenten erfragt werden.
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19406611
Seminar
Abgesagt
Journal Club: Biomedical Data Science (Katharina Jahn)
Zeit: Di 16:00-18:00 (Erster Termin: 14.10.2025)
Ort: A3/SR 115 (Arnimallee 3-5)
Kommentar
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.
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19335011
Seminar
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Entwicklung und Degeneration des Nervensystems 0609aA1.1
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