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.

自学
语言: English
Digital Health, Expert

课程信息

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

课程内容

  • 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

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Learners

Current
Today
6,376
Course End
12月 05 2016
4,242
Course Start
11月 14 2016
3,779

证书要求

  • 课程证书 授予者需要至少取得课程总分的百分之 50%
  • 参与证明 授予者需要至少学习了所有课程资料的百分之 50%

欲知详情,请访问证书指南.

该课程提供者

Dr. Matthieu-P. Schapranow

Dr. Matthieu-P. Schapranow is Program Manager E-Health at the HPI, Visiting Scientist at the Mass. Veterans Epidemiology Research and Information Center (MAVERIC) of the U.S. Department of Veterans Affairs and at Charité – University Medicine in Berlin, Germany. He is a valued member of the Berlin Cancer Society contributing to the Federal Association for Information Technology, Telecommunications and New Media (BITKOM) and the Global Alliance for Genomics and Health. Dr. Schapranow holds a PhD as well as the MSc and BSc degrees in Software Engineering. He was honored with the Personalized Medicine Convention Award 2015, the European Life Science Award in 2014, and the Innovation Award of the German Capital Region in 2012. Together with Prof. Dr. Plattner, he published the textbook "High-Performance In-Memory Genome Data Analysis" in 2013.