Universities here have final year honours projects where you work within a group for a few months then write it up as part of your final mark. Do you know if you have anything similar? Ask your course organisers if it would be ok to approach a Bioinformatics Group or Core Facility to inquire if they would be willing to provide a suitable project.
I believe that learning at least the basic command line tools and programming language like python (it has commonly used bioinformatics packages) can help me get up to speed most easily. It will also enable me to apply whatever I learned in molecular genetics quickly to programming.
And having the ability to code and using tools makes it easier to find a lab position as @efjir mentioned.
I will be completing "Python for Genomic Data Science", "Command Line Tools for Genomic Data Science", and "Algorithms for DNA Sequencing" over the next 4 months. Hopefully by then I have a general understanding of what bioinformatics would be like.
A big Thank You for everyone who helped me here, this forum is really awesome :D
I always thought that most of these online bioinformatics courses are more focused on (wetlab) biologists that want to get into bioinformatics. For a computer science student I would rather recommend to take some molecular biology courses about basics like DNA, RNA, Proteins, whats is a promotor, how is a gene structured, modifications, mutations etc. You may be able to read these things when they show up in your workflow but I would not want to work on something without having a big picture about where I am.
Should have clarified that I also have some background in biology/chemistry, taken university level biology courses like cell biology, genetics, organic chemistry.
But I totally agree, having strong domain knowledge is crucial to bioinformatics. Now the question is how should I improve on that? If anyone here were to re-take university, given their experience now, what are some best ways to learn (by oneself)?
In biology, you might want to take a look at evolutionary biology+population genetics / gene regulation (eukaryotic) / modern genomics / cancer biology+ DNA repair pathways.
Immulogy/virology/neuroscience are not needed unless you want to specialize in one of them. Lab work helps a lot (just basic techniques like gels, PCRs, cloning plasmids, using a microscope).
Bioinformatics is a very large field.... In graduate school you will truly get the occasion to specialize. And university level courses are nice but give only a very broad overview.
Statistics are a must, probability courses on Bayesian statistics/Markov chains can be nice as well.
I think everyone who wants to do work in genomics, even if you want to do something really specific in just humans say, should take a course or two in molecular evolution and pop gen. Invaluable and in my opinion utterly necessary for interpreting observed mutations, polymorphisms, and thinking about how genomes work.
And heartily second stats that focuses on models, markov chains and processes, etc. They, along with BWT and the like, underpin pretty much all of the important algorithms used in every bioinformatics program out there.
Checked out rosalind and it seems to focus on the programming part more. But since I am not familiar with graduate research, what is the most time consuming part of bioinformatics research? Is it reading paper? Or is it more coding, learning about libraries?
I'd like to at least be familiar with the "busy" work first, than the "hard" work
Graduate research is research, and it differs from coursework in that exactly what will take the most time varies depending on where you are in your project and over time. You'll likely do some course work and you are always reading papers. That's a matter of course as a scientist and it never stops. One recommendation there is to set up some automated searched and subscribe to the table of contents of various bioinformatics and domain-specific journals (as well as the big generalist science journals). If you can schedule a delivery day it is nice to have them all come on the same day of the week. Through lots of my graduate school I did a lot of paper reading on Fridays.
As a bioinformatician, you may or may not do a lot of coding (sounds like you will as that is the direction you want to go). I'd say most of my grad school work was composed of experimenting, analyzing, and coding along with reading, etc. Learnign libraries is like reading the literature, although you typically only need to do it when you need to use a specific library or you come across one that seems interesting and potentially useful. I'd say it is a rather minor part of your career.
Automated searches are nice for specialized topics, but the quick and easy way is to suscribe to some science journals RSS feeds (it also works well with webcomics...). I also see a lot of scientists in the US using Twitter to advertise papers/tools in their fields, you can follow them.
Yup, that's why I added the ToC alerts (same thing as RSS feeds usually). I get a mixture of both, some automated Pubmed searches every friday plus the ToC for PNAS, Nature Gentics, PLoS Genetics, PLoS Computational Biology, several BMC journals, etc.
My advice is plenty of relevant activity which include attending conferences and getting to meet people, volunteering in bioinformatics projects if you can identify a research group nearby, or joining bioinformatics associations. In my experience, it will come to you.
Getting involved in an actual lab would be my dream (as an undergrad). From what I heard though, I do need decent knowledge to build meaningful tools and project. I'd like to prepare for such project so that later on I don't scramble to read up textbooks or going through tons of documentations just to get some code to work.
Any recommendations for learning the everyday tasks/tools? (biopython? bioperl?)
There's a great Coursera course on Python for Genomics you could enroll in for free. Before you're done with that, I'm sure you'll know the next thing to do - ideas will start budding in a specific interest area which will narrow the things you'd have to pour through significantly.
The everyday tasks and tools vary a lot. Really depends on your personal preference and the lab you start out in. I started my graduate school doing mosty work in perl. In my post-doc I switched almost entirely to python. While biopython is actively developed I rarely use it. There are a whole slew of genomics specific packages people put together as standalone packages that typically do a far better job IMHO. But it is always useful to know it and know it is there.
Universities here have final year honours projects where you work within a group for a few months then write it up as part of your final mark. Do you know if you have anything similar? Ask your course organisers if it would be ok to approach a Bioinformatics Group or Core Facility to inquire if they would be willing to provide a suitable project.