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.

Selbststudium
Kurssprache: English
Digital Health, Expert

Kursinformationen

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

Lernmaterial

  • Week 1: History of DNA and core components of cells:

    Back to school: let's test your current biology background. We will start with a concrete real-world use case from medicine to explain core components of human cells, their function, and how they interact.
  • Week 2: Processing and analyzing of genetic data:

    How to turn genetic raw data into meaningful information is the content of this week. Specific data processing steps are required prior to interpreting genetic data. In this week we will address specific algorithms, IT methods, and processes to assess genetic data. Furthermore, you will gain hands-on experience in analyzing selected genetic variants and evaluating their relevance.
  • Week 3: Online Q&A and final exams :

    In this week you will have the chance to discuss any open questions with the teaching team using our online tools. Furthermore, you will have to complete your final exams of the course in this week. We also encourage you to join our "I like, I wish" discussion providing your feedback of the course.
  • I like, I wish

Für diesen Kurs einschreiben

Der Kurs ist kostenlos. Legen Sie sich einfach ein Benutzerkonto auf openHPI an und nehmen Sie am Kurs teil!
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Lernende

Aktuell
Heute
6.376
Kursende
5. Dezember 2016
4.242
Kursstart
14. November 2016
3.779

Anforderungen für Leistungsnachweise

  • Den Leistungsnachweis erhält, wer in der Summe aller benoteten Aufgaben mindestens 50% der Höchstpunktzahl erreicht hat.
  • Die Teilnahmebestätigung erhält, wer auf zumindest 50% der Kursunterlagen zugegriffen hat.

Mehr Informationen finden Sie in den Richtlinien für Leistungsnachweise.

Dieser Kurs wird angeboten von

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”