This course introduces statistical and computational methods for analyzing various biomedical data in genetics, bioinformatics and personalized medicine problems, including e.g. biomarker identification, survival analysis, genetic association analysis and drug response modeling.
The course is organized in a problem-based learning format (very similar to that of CS-E4880 - Machine Learning in Bioinformatics). During the lectures the teachers introduce you a collection of biomedical problems together with standard and state-of-the-art computational and statistical methods to address those problems and to make biological conclusions at the end. After the set of lectures, you will apply some of these computational techniques on real biomedical data in a selected project work.
Prerequisite knowledge for this course include basic bioinformatics and basic statistics/machine learning (e.g. CS-E5860 - Computational Genomics, CS-E5870 - High-Throughput Bioinformatics, NBE-E4030 - Experimental and Statistical Methods in Biological Sciences, CS-E3210 - Machine Learning: Basic Principles) or equivalent knowledge.
- Credits: 5 ECTS
- Teachers in charge: Gleb Tikhonov and Harri Lähdesmäki
- Lecturers: Juho Timonen, Gleb Tikhonov, Siddharth Ramchandran and Mine Ögretir
- Contact person: Gleb Tikhonov, email: gleb <dot> tikhonov <at> aalto.fi
To pass the course you need to attend to 3 out of 4 lectures and complete the following (see Instructions page for more details):
- Learning diaries from all lectures
- Preliminary report of your project work
- Peer-review of two other reports
- Project work poster presentation
- Final report of your project work
- 28.02: Lecture 1: Modelling longitudinal biomedical data, Juho Timonen
- 06.03: Lecture 2: Principles of multivariate analysis for biomedical data, Gleb Tikhonov
- 13.03: Lecture 3: Deep generative modelling for biomedical data, Siddharth Ramchandran
- 20.03: Lecture 4: Survival Analysis and Event Risk Prediction from Biomarkers, Mine Ögretir
- 25.03: Project work topics released
- 29.03: Project topic priority form submission deadline
- 31.03: Project topics assigned
- 01.04-15.05: Project work
- 05.04: Learning diary deadline
- 25.04: Preliminary project report deadline
- 30.04: Peer-review assignments distributed
- 07.05: Project work poster presentations upload deadline
- 08.05: Project poster online session starts
- 11.05: Project poster online session finishes
- 14.05: Peer-review submission deadline
- 21.05: Final project report submission deadline
Project work meetings:
Between the last lecture and the poster presentation session there will be several scheduled meeting sessions with the lecturer responsible for the student's project topic. These meetings are primarily designed to provide the student an opportunity to receive a scientific guidance regarding his/her project work in if such guidance is desired. Students' attendance to these meetings is voluntary.
The exact dates and times will be announced later.
Adjustments due to university policies on COVID-19
Starting from Lecture 3 the course will move to completely distant teaching basis. This effectively means that
- Lectures 3 and 4 will be given online
- The attendance requirement will be waived due to inability to credibly monitor it
- Project work meetings with lectures will be held online
- The project work poster presentation session will be also organised in some online manner that would try to mimic a classic poster presentation. The teachers are currently developing the exact format and will announce the details closer to the submission date. Our preliminary vision so far is that groups will prepare standard posters as pdf documents and then we will distribute those among several other groups, which would be asked to fill in and return a questionnaire based on received posters.