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 students will have a comprehensive understanding of fundamental methodological concepts underlying modeling of biological networks and systems. Students will learn to choose appropriate modeling methods for a variety of small- and large-scale problems as well as for different types of experimental data. Students will learn to apply various computational and statistical modeling methods in real interdisciplinary biological problems and have sufficient knowledge to explore the topic further.

Credits: 5

Schedule: 22.10.2024 - 04.12.2024

Teacher in charge (valid for whole curriculum period):

Teacher in charge (applies in this implementation): Harri Lähdesmäki

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:

    Mathematical and statistical models of biological molecular-level networks, such as gene regulation, epigenetics, signaling, and metabolism. Models covered in the course include stochastic chemical reaction networks, differential equations, Bayesian and dependency networks, regression models and random networks. Statistical methods for inference of networks from data, and prediction using the models. Mainly probabilistic and machine learning models.

Assessment Methods and Criteria
  • valid for whole curriculum period:

    Examination, exercises, and assignment problems.
    Details will be specified at the course webpage at the beginning of the course. 

Workload
  • valid for whole curriculum period:

    The course consits of lectures, exercises and assignments, projects, and exam. 
    Details will be specified at the course webpage at the beginning of the course. 

DETAILS

Study Material
  • valid for whole curriculum period:

    To be specified in MyCourses at the start of the course.

Substitutes for Courses
Prerequisites
SDG: Sustainable Development Goals

    3 Good Health and Well-being

FURTHER INFORMATION

Further Information
  • valid for whole curriculum period:

    Teaching Language: English

    Teaching Period: 2024-2025 Autumn II
    2025-2026 Autumn II