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Laboratory of Computer and Information Science / Neural Networks Research Centre CIS Lab Helsinki University of Technology

Practical instructions

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Presentation

The presentations should last roughly one hour, and after each presentation there will be 15 minutes for discussion. Those having 2 presentations the same day have to compress to 30-40 minutes. The lecture room has an overhead projector and a video projector, but no computer. If you want to use the video projector you can either bring your own laptop, or tell in advance (at least 2 days before the presentation) to the assistant.

Any slides made for the presentation will be added to the course web site, so please give them to the assistant preferably in PDF. If possible, we would also like to receive the source of the presentation for future use.

During the meetings you will also be giving grades and comments of the presentations given by other students. This is for two reasons: The presenter gets more feedback, and you learn to evaluate scientific presentations. You are also a lot more likely to think about how the presentation could have been improved, and thus will give better presentations later on.

The evaluation form is available as PDF file so that you can take a look at it when preparing your presentation. I will print forms for the meetings, so you do not need to bring one.

Exercises

In order to pass the course you need to solve exercise problems, created by other participants. You need to present your own problem when giving the presentation, and give the model solution to the assistant. Please show a preliminary version of the problem to the assistant in advance, so that it can be modified if needed. The time to return the solutions to problems given by others is 2 weeks, and passing the course requires solving (or at least trying hard) 50% of the problems.

The exercise problems are listed on a separate page.

Project work

The purpose of the project work is to get deeper understanding of the methods presented on the course. In typical form the project work consists for example of implementing (usually simplified version of) an algorithm or model described in the paper and running some experiments with that. Solving this kind of project task helps to understand how exactly the system works, and especially what kind of difficulties or drawbacks it may have. The project work may also be about something else than the presentation, especially in the cases where the article was some kind of review that had little methodological content. It is also possible to do a bit more biologically oriented project work by using existing methods but applying those to real data and interpreting the results.

The project work gives officially two credit points, which can be used to estimate the amount of work required. The intention is not to replicate everything that was made in the paper, but instead focus on some detail and treat that well. No bonus points are given because of too large project works, so try to do a well restricted thing well instead of trying to cover too much.

The project work involves three phases or tasks:
  1. Send an email describing your idea of the project work to the assistant. He will then suggest changes if needed, in order to keep the workload at correct level, and may provide also other feedback (such as help in getting a suitable data set for experiments). If you have trouble coming up with an idea, please contact the assistant.
  2. Do the actual project work, which probably consists of implementing a small method and making some experiments with that. If the original plan turns out to be too difficult you should revise it in the run, and may try consulting the instructor. If your project is related to your presentation(optimal case), it would we advisable to implement your method and experiment on it before the presentation. This helps significantly in understanding what you're talking about in your presentation.
  3. Write a project report, and return that to the assistant by the end of May.

The project report should be roughly 4 pages long (but may include figures or tables as additional appendixes if needed), using the format implemented by the BioMed Central's TeX template. The report should be self-consistent in the sense that it includes the motivation of the biological problem, description of the methodology and possible data sets, as well as the results of your work. You can (and should) naturally cite the paper the work was based on, but instead of sentences like "the problem is the same as in paper X" you should have "the problem is [insert a sufficient description here], also studied in X. Here the difference is that Y is not considered, because of...". The idea is that a reader who is familiar with bioinformatics and machine learning, but has not heard your presentation or read the original paper, should be able to understand what was done, why the general topic is important etc.

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