Code of Life - When Computer Science Meets Genetics

Kurs
  • Digital Health

Code of Life - When Computer Science Meets Genetics

Welcome to the class: we are very excited that you are interested in learning more about the foundations of life. In this openHPI course, we will give an introduction about components of human cells and their functions. We dive into the cell core to explore the Deoxyribonucleic Acid (DNA), its structure, and how it stores the code of life. Furthermore, we will explore how to discover genetic variants and mutations and how to assess their impact on the cell functions and the whole human body. Ultimately, we will outline how individual genetic variants can be connected to complex diseases, such as cancer. Just two decades ago, all these tasks would have been impossible due to missing knowledge about the DNA and a lack of computational power. As a result, you will learn basic concepts about how to incorporate latest computer science aspects to explore the code of life interactively.

Angeboten von Dr.-Ing. Matthieu-P. Schapranow | Zuletzt aktualisiert am 15. Juli 2026 | 6810 Einschreibungen

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  • EN
  • Zertifikat
Kursinformation

Welcome to the class: we are very excited that you are interested in learning more about the foundations of life. In this openHPI course, we will give an introduction about components of human cells and their functions. We dive into the cell core to explore the Deoxyribonucleic Acid (DNA), its structure, and how it stores the code of life. Furthermore, we will explore how to discover genetic variants and mutations and how to assess their impact on the cell functions and the whole human body. Ultimately, we will outline how individual genetic variants can be connected to complex diseases, such as cancer. Just two decades ago, all these tasks would have been impossible due to missing knowledge about the DNA and a lack of computational power. As a result, you will learn basic concepts about how to incorporate latest computer science aspects to explore the code of life interactively.

News: Pre-course reading materials as well as additional information about our projects focusing on digital health are available on our Analyze Genomes website.

Join openHPI's official Twitter Feed: @openHPI. Use the hashtag #codeoflife to join and contribute to social media conversations about this course.

Additional video lecturing material can be found at www.tele-task.de .
Photo source: © Sergey Nivens / Fotolia

Attention: This course is currently in self-study mode, in which you do not have access to graded assignments/exams. Therefore, we can only issue you a certificate of participation.

Anforderungen für Nachweise
  • Teilnahmebescheinigung: Du erhältst automatisch eine kostenlose Teilnahmebescheinigung, sobald du mindestens 50% der Kursinhalte durchgearbeitet hast.
  • Zertifikat: Du erhältst ein Zertifikat, wenn du in der Summe aller benoteten Aufgaben mindestens 50% der Höchstpunktzahl erreicht hast.

Mehr Informationen findest du auf der Seite für Nachweise und Richtlinien.

Unsere Dozent:innen

Dr. Matthieu-P. Schapranow

Dr. Matthieu-P. Schapranow ist Manager des Programms „E-Health“ am Hasso-Plattner-Institut, Gastwissenschaftler am Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC) des U.S. Department of Veterans Affairs und an der Charité – Universitätsmedizin Berlin. Darüber hinaus engagiert sich ehrenamtlich u.a. in der Berliner Krebsgesellschaft, im Bundesverband Informationswirtschaft, Telekommunikation und neue Medien e.V. (BITKOM) in der Arbeitsgruppe e-Health, sowie in der Global Alliance for Genomics and Health. Dr. Schapranow wurden die wissenschaftlichen Abschlüsse Dr.-Ing., M.Sc., sowie B.Sc. in Software Engineering verliehen. Er wurde u.a. ausgezeichnet mit dem Personalized Medicine Award Convention 2015, dem European Life Science Award 2014, sowie dem Berlin-Brandenburger Innovationspreis 2012. Anlässlich des “World Health Summit 2013“ veröffentlichte Dr. Schapranow gemeinsam mit Prof. Dr. Plattner das Buch „High-Performance In-Memory Genome Data Analysis”