Basic guidelines
Submission
- Assignments are submitted via Moodle.
- Results should be submitted as a single PDF file. Submission in other formats will not be accepted.
- For assignments written in the R language, you might find this RMarkdown homework template useful.
- Assignments need to be submitted by the deadline announced here. Submissions received 1 day late will lose 50% of the points, later submissions will not be accepted. If you miss a deadline, you can earn extra points from bonus exercises that will be posted occasionally.
Plagiarism
Bioinformatics course follows exactly the same rules that applied to the Data Mining course.
The homeworks are meant to be solved alone. If you struggle with something you are welcome to write to the Piazza forum, attend the consultations or ask directly from TA's. You are of course allowed to discuss the main ideas with other students, but you have to solve the tasks by yourself, it shouldn't be a team effort. This is necessary because of the format of the course, which is very strongly based on individual work so if you don't do it you will not acquire all the knowledge you need during the course.
Usually during the course we use existing functionality of R and Python (or something else) for the data mining algorithms and you are not forced to implement them yourself (there can be exceptions). If a considerable part of your solution is based on some material you found online (more than just how to use some function), you should definitely add a citation to that source, otherwise it could also be called as plagiarism.
So in principle:
Do your work yourself. Do not share your work with others, if they need help, give them hints or guidelines. If you get a lot of help from some online source, cite it! If you get caught with a clear case of plagiarism:
If there are no previous problems depending on the situation you might get away with just getting 0 points for the task and get a warning from us. If the problem appears many times or we know that you have already warnings from other courses, an official warning follows. If you have already other official warnings, this can lead to expelling. We will be using automatic plagiarism detection programs to avoid and detect these situations!
Datasets
- Raw RNA-seq data
- Full gene expression dataset as SummarizedExperiment object
- Small gene expression dataset in which some of the samples have been swapped
- Transcript expression estimates from Salmon
- BigWig files
- Eigengene values
- ChIPSeq files
Assignment
Assignments are submitted via Moodle.
- Assignment 1 - Deadline 20 February 2023 @ 11:59PM
- Assignment 2 Protein sequences - Deadline 27 February 2023 @ 11:59 PM
- Assignment 3 - Deadline 13 March 2023 @ 11:59 PM
- Assignment 4 - Deadline 13 March 2023 @ 11:59 PM
- Assignment 5 - Deadline 20 March 2023 @ 11:59PM
- Assignment 6 - Deadline 27 March 2023 @ 11:59PM
- Assignment 7 - Deadline 03 April 2023 @ 11:59PM
- Assignment 8 - Deadline 10 April 2023 @ 11:59PM
- Assignment 9 - Deadline 17 April 2023 @ 11:59PM
- Assignment 10 - Deadline 24 April 2023 @ 11:59PM
- Project report - Deadline 14 June 2023 @ 11:59PM