Please note! Course description is confirmed for two academic years, which means that in general, e.g. Learning outcomes, assessment methods and key content stays unchanged. However, via course syllabus, it is possible to specify or change the course execution in each realization of the course, such as how the contact sessions are organized, assessment methods weighted or materials used.

LEARNING OUTCOMES

After the course the student:

  • understands the concepts of Systems biology and how they can be applied to address various research questions
  • knows how omics technologies are applied to generate data
  • can apply computational tools to treat high-throughput data
  • can differentiate between a reductionistic and a holistic view of a cell
  • can quantitatively describe biological phenomena
  • analyze the behavior of small biological networks using modeling and simulation
  • can model basic microbial metabolism

Credits: 5

Schedule: 02.03.2022 - 02.06.2022

Teacher in charge (valid for whole curriculum period):

Teacher in charge (applies in this implementation): Tero Eerikäinen, Alexander Frey

Contact information for the course (applies in this implementation):

CEFR level (valid for whole curriculum period):

Language of instruction and studies (applies in this implementation):

Teaching language: English. Languages of study attainment: English

CONTENT, ASSESSMENT AND WORKLOAD

Content
  • valid for whole curriculum period:

    The course aims at the analysis and understanding of biological phenomena using omics tools, mathematical models and simulations. In the course students learn to view the cell as a complex system of interacting components (DNA-protein, protein-protein or metabolite-enzyme). As the individual components often are involved in many different reactions, complex networks are evolving which govern the cellular activities. These networks can be deduced from a global analysis of cells using omics tools (transcriptomics, proteomics and metabolomics) and other experimental approaches. Methods and strategies for acquisition and analysis of high throughput data will be discussed. Computer exercises will be used to combine theory with the practice. Modeling of metabolic fluxes, their control and thermodynamic balances are practiced. Programs helping in the interpretation of high throughput data will be used.

Assessment Methods and Criteria
  • valid for whole curriculum period:

    Lectures, computer exercises and assignments

Workload
  • valid for whole curriculum period:

    Lectures and Seminars 18 - 24 h

    Exercises and assignments   56 - 62 h

    Independent studying  51h

    Exam 4 h

     

DETAILS

Study Material
  • valid for whole curriculum period:

    Material to be announced

Substitutes for Courses
Prerequisites
SDG: Sustainable Development Goals

    3 Good Health and Well-being

    13 Climate Action

FURTHER INFORMATION

Further Information
  • valid for whole curriculum period:

    The course is offered in even years.

    Teaching Period:

    (2020, 2021) - No teaching

    2021-2022 Spring IV-V

    Course Homepage: https://mycourses.aalto.fi/course/search.php?search=CHEM-E3170

    Registration for Courses: In the academic year 2021-2022, registration for courses will take place on Sisu (sisu.aalto.fi) instead of WebOodi.

    Sisu