Course Review: Introduction to Bioinformatics

After the New Year’s break, our battle field shifts from Karolinska to Stockholm University, where we are going to learn bioinformatics now!

A few weeks before, our course teacher Professor Arne Elofsson had already sent us the link to course website. According to the course website, the upcoming course “Introduction to Bioinformatics” will consist of 17 lectures (2 hours each), 9 programming-lab sessions (3 hours each) and 9 bioinformatics-lab sessions (3 hours each). Believe it or not, the whole course is designed to be finished within four weeks! At that time, I was still indulged in my excellent academic results in the first term at Karolinska, and had no idea of how tough the coming 3 months would be and how much I would learn.

My google calendar from 16 Jan to 5 Feb.

1. The course teacher

Our course teacher is Arne Elofsson. He is a full Professor of Bioinformatics at Stockholm University as well as one of the Principal Investigators at Science For Life Laboratory. Arne is specialized in protein structure prediction using bioinformatics tool, and one of his most recognizable achievements is the development of Pcons series for predicting
protein residue contact. Arne is certainly one of the most efficient people I have ever seen: any Email from
students will ALWAYS be replied within one hour. Personally I am impressed by his erudition in the field: he can answer all the questions from us and share his deep insight with us. According to, Arne has an H-index of 55.

2.  Lectures

Unlike any lectures that I had previously in primary, secondary, and undergraduate schools, in the course Introduction to Bioinformatics, all the lecture slides and videos were uploaded to Youtube. Students were required to 1. watch the video, 2. study the slide and 3. put their own questions to the course website before coming to a lecture. Therefore, during the 2-hour lecture, Arne will only be responsible to answer our questions and perhaps explain the core concept regarding to this lecture. In my opinion there are both advantage and disadvantages:


If you don’t understand the lecture, it is always possible to go through the video at any time


It is really a matter of self-discipline. It would be a vicious cycle if you don’t prepare for the lecture!

3. Programming Labs in Python

The most wonderful thing of these labs is that we are assumed to have no background in programming. Hence, the labs are designed so that we  pick up the basis in the beginning, and accelerate gradually towards a capable bioinformatician. In the first lab, we started by creating strings, lists and dictionaries and making simple calculation; while in the last one, we were asked to extract the data from a high-throughput biological experiment, integrate them and present them graphically using python, which are all critical and bonus techniques in a modern wet lab.

Plotting thousands of raw data from wet lab experiment

4. Bioinformatics Labs

In parallel with programming labs, the bioinformatics labs integrate our knowledge acquired from lectures to solve bioinformatics problem. The tasks in these labs could be a re-enforcement of the concepts we learned, such as drawing a  relation tree for a few species; or dealing with a practical issue confronted by daily researchers such as compare and contrast different database and software tools and select the most suitable for the assigned task, or apply some of the most popular and useful bioinformatics tools on our own.

Finding out the structure of a whole protein from a sequence fragment

No Pain, No Gain

Although it is such a painstaking process, all of our classmates agree on the fact that we learned a lot in the process and it is such a good investment of time and energy. And most importantly, bioinformatics is FUN!

Summary to the links mentioned in the blog:

  1. Course website of Introduction to Bioinformatics:
  2. Arne’s profiles at Stockholm University:  Science For Life Laboratory: and Google Scholar:
  3. Arne’s Youtube channel of the course:

6 thoughts on “Course Review: Introduction to Bioinformatics”

  1. Hi Tianlin, my name is Shuhan. I have heard that predicating RNA structure is much more difficult than that for protein. Furthermore, the timescale for RNA folding could be days instead of seconds. I am wondering if you have meet any tutors who has experience in RNA structure prediction.

  2. Hello Shuhan! Do you study biotechnology as well? Seems that you know a lot in this field!
    There are different kinds of RNA, such as mRNA, sncRNA, ,miRNA and the newly discovered long non-coding RNA……I can’t pretend that I know all of them very well but for the cases that I am most familiar with, say miRNA or siRNA, it is much easier to determine their folding compared to protein, because protein structure consists of primary -> secondary -> tertiary -> quandary levels, but in contrast RNA folding is predominantly dictated by only the complementarity between its purine and pyrimidine bases. They should be also able to fold properly once they are exported from nucleus. But for the other RNA classes I am not sure, so you could also be right!
    At Stockholm University we learn more about protein, because Arne himself is a figure in the field. As I can recall we were taught about RNA structure determined by Weng-on Lui at Karolinska Institutet last semester, and one of the task was to determine the folding of a miRNA using RNAfold web server. Check this out if you have RNA prediction problem 😉

  3. Hello Tianlin, I am currently taking a course on computational biology and simulation so I have learnt a little bit about molecular dynamics and monte carlo. RNA also have tertiary structures and finding out the tertiary structure can allow us to understand how it interacts with protein. For instance the secondary structure of tRNA is clover leaf while its tertiary structure is a L-shape which allows it to fit into the Ribosome. RNAfold can only predict the secondary structure of RNA. So I wonder if there is any professor who uses computer simulation to predict RNA tertiary structure.

    Btw, I am applying for MTLS. Hehe 🙂

  4. Thank you for the insight! To be honest I never thought of simulation of RNA structure as we do for protein before.
    When I searched on the Sci-for-lab webpage, I found David Van der Poel whose research description is the closest “Applications focus on 1) RNA structure and dynamics in the context of viral genomes, 2) binding of small molecules to proteins in order to….” But I don’t know any in person.
    If you are interested and even do a master thesis about it, I can pass your questions to Arne or Olof, the coordinator of MTLS.
    It is so lovely to hear that you are applying for MTLS! Not sure if our department sent notification a week in advance also this year, but it is very likely that I (as student ambassador) will contact you in the coming few days (so I am excited about the release of results on 24/03 as well)! Keep in touch 😀

  5. Don’t worry about it. There will be plenty of opportunities for me when I go to Stockholm. I look really forward to the results. Yes, let’s keep in touch!

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