General info for January 2021
The course will be arranged entirely online.
- On Tuesdays 12:15-14:00, and
- On Fridays 12:15-14:00
- First lecture: January 12, 2021
- Most lectures will be arrange as live/online lectures. We will try to make video recordings of the live lectures available after the lectures (for course participants only). Some lectures may be available only as pre-recorded video lectures (for course participants only). In case of video lectures, we will have time for questions and discussion during the lecture time slot.
- For online lectures, we will use zoom program. Link to a zoom meeting will be provided on the course web page a little before the beginning of the lecture.
- Wednesdays 14:15-18:00
- NOTE: There will be only one exercise session starting at 14:15 and continuing after 16:00 if needed
- First exercise: January 13, 2020
- Harri Lähdesmäki, email: email@example.com (office: B358)
- Juho Timonen, email: firstname.lastname@example.org
- Valerii Iakovlev, email: email@example.com
- One assignment
Models of biological networks, covering molecular-level networks of transcriptional regulation, signaling, metabolism and epigenetics, with emphasis on modeling methods. Modeling formalisms include stochastic reaction networks, stochastic and ordinary differential equations, regression, Bayesian and Boolean networks, and dependency and correlation networks. Methods for inference of networks from experimental data, and prediction using the models. Mainly probabilistic and machine learning models.
The course is also accepted as a postgraduate course
- Introduction and chemical reaction network models
- Review of Markov processes in discrete and continuous time
- Chemical and biochemical kinetics
- Stochastic differential equations
- Ordinary differential equation models for biological networks
- Metabolic networks
- Parameter inference for biological networks
- Network structure selection for biological networks
- Bayesian networks as biological networks
- Boolean and dependency networks as biological networks
- Undirected graphical models
- Biological networks as random graphs
- Basic knowledge of probability, statistics and applied math
- Basic programming skills
- Exercises: Participation in the exercise sessions is not mandatory but you need to submit written reports (minimum of 15 points)
- 1 assignment project. Assignment project can be done in pairs (two students).
- Final examination
- Exercises: max. 30 points (4 + 6 + 4*5)
- Assignment project: max. 30 points
- Exam: max. 30 points
- Total: max. 90 points
- 45 points required to pass the course
- Approx. 81-83 points will give you the maximum grade
List of materials:
- Darren J. Wilkinson, Stochastic Modelling for Systems Biology, Chapman & Hall/CRC, 2011
- Ingalls BP, Mathematical Modeling in Systems Biology: An Introduction, MIT Press, 2013
- Murphy KP, Machine Learning: A Probabilistic Perspective, MIT press, 2012
- (tentative) Palsson B, Systems Biology: Properties of Reconstructed Networks, Cambridge University Press, 2006
- (tentative) Junker BH, Schreiber F, Analysis of Biological Networks, Wiley, 2008 or Eric D. Kolaczyk, Statistical Analysis of Network Data: Methods and Models, Springer, 2009
- Lecture notes
Note: The course covers only selected parts of the books. The books are available from our library as traditional printed books and as e-books.
The material may be supplemented by recent articles and possibly by other book chapters
- Exam on Thursday 25.02.2021 between 9-12.
- Exam will be done remotely.
- Exam questions will be made available via mycourses webpage in pdf format.
- Exam questions will be available starting at about 9:00.
- You can use whatever material you may want during the exam, including lecture notes (and even lecture video recordings if you wish).
- Answers must be written by yourself (i.e., direct copy-pasting of any material is not allowed).
- You are not allowed to communicate with anyone during the exam.
- You can prepare your answers either with pen and paper or with computer (or a combination of these two).
- Use of diagrams/drawings/equations are especially encouraged.
- Submission should be in pdf-format (in case pdf-format is problematic, jpg is also accepted), preferably as a single pdf file.
- Answers should be returned via the mycourses webpage by uploading your pdf document.
- Additional instruction will be on the exam question sheet.
- You are not allowed to distribute the exam questions to anyone/anywhere.