Hi Meg, I was wondering if I could get your insight on something... I'm interested in bioinformatics as a career but am not sure whether I should pursue just a Master's or try for a PhD. How did you decide how far you want to go with your education? I noticed you mentioned you hope to do a PhD someday? Thank you so much!
hey anon! okay, so in this answer I'ma focus on two things:
my thought process behind finalizing on a PhD
my approach to furthering education
I. Why PhD?
1. I love my subjects. I love the interdisciplinary nature of computational biology and it's sister subjects and I can see myself in academia- constantly learning and researching and exploring.
2. Even on the off chance that if I don't pursue a career in academia, I think I need a PhD anyway? Most high level positions in the industry for life-sciences requires a level of expertise that only comes with a doctorate, and I think my career opportunities (+ growth) will be rather limited without it.
Considering these two points, a PhD would be most suitable for me.
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Now, choosing the right type of graduate program can always be challenging because there are so many ways to go about it, and I am a very indecisive person so this was especially difficult for me. Here is my approach
II. Factors I considered before taking my next steps
My Primary Short-Term Goal(s)
I opted for a B.Tech in Biotechnology after 12th grade, and it is through the course of this degree that I realized my interest in computational biology and bioinformatics. My undergrad focused on too many topics and often emphasized wet lab over dry lab, so although I'm graduating with a specialization in Medicinal and Computational Biology, I don't know nearly enough regarding the computational aspects
Thus, my short-term goal is to expand my theoretical understanding of the important aspects of bioinformatics & computational biology.
2. Course Options that Work
Now, I know that I want to continue my education, I've got two options- Masters and PhD. When I considered my immediate goal against these two options, I realized four things:
a. I'm not equipped with the required dry lab skills to dive headfirst into research.
b. I don't know enough bioinformatics to commit to anything long term right now
c. I'm looking for a course that feels like an extension of my undergrad
d. I want to keep my options open and consider all career opportunities
Given these three options (+ course-related expenses + my skill level), it made most sense for me to choose a MSc at the moment rather than a PhD.
3. How the Course Ties in to My Long Term Goals
As I mentioned, my long term goal is to do a PhD. However, my upcoming graduate course is actually an MSc by Coursework degree, which- unlike a Thesis program, focuses on skill development (especially industry related) rather than research. In fact, most Thesis Masters can be converted to a PhD, but my program does not have that option.
At first glance, this course might seem like it's going against my long term goal but consider:
- Industry related or not, I need to develop computational skills before I can pursue research
- After this course I might prefer to gain work experience for a couple years before opting for a PhD.
- My preferred uni(s) for PhD are different from my preferred uni for Masters.
[^To give an example on the last point, for masters i considered countries/unis known for their quality of education + closer to my home country (this will be my first time living abroad alone) but for my PhD, I'm looking at countries/unis that are pioneers in research for my subjects of interest (even if they are a lot farther away from home)]
So essentially, I'm relying on this course to give me the skills and knowledge I need for a PhD in the future, while also giving me a buffer to understand and align my future goals and plans. Jumping from this to a PhD would be a lot harder than from a Thesis Masters, but that's a risk I'm willing to take.
So yeah, this was the way I went about choosing both my short term and long term academic goals. I hope this provides a good starting point for you! Don't stress out too much about it though; the truth is that there is no right or wrong choice, whatever decision you make will warp around your intentions and work for you the way you want it to. Best of luck for your future endeavors!!! I'm sure it'll all work out <3
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Hey Meg! I was just catching up on your posts and wow, congrats on publishing the paper! I'm so excited for you and how far you'll go (it's so cool that you're working with alpha fold!!)! π₯³ How did you learn bioinformatics? Are there any resources you'd recommend for a complete beginner? (I'm trying to learn how to do proteomics analyses rn, but I can't seem to find many resources I can easily understand π)
hii!! thank you so much for the wishes! the paper was a part of my final project with my team + guide so it was really a group effort <3 my teammates and I are all first authors, they were just kind enough to put my name first xD and yes! my current alphafold work is a lot of fun ^=^ I'm really enjoying my internship hehe
okay so I learnt bioinformatics as a part of my uni curriculum, and we mainly relied on these two textbooks
Essential Bioinformatics by Jin Xiong
Bioinformatics: Sequence and Genome Analysis
In addition to this, I also recently found this textbook titled Bioinformatics: An Introductory Textbook by Thomas Dandekar, Meik Kunz which focuses both on basic bioinformatics concepts and how to use the available tools. I especially like this book because I found it super easy to understand
EMBL also offers courses! even for synchronous online/in person courses that have ended, they tend to upload course materials. There's one for proteomics analyses as well- I've checked out the mass spectrometry videos under this course and they start with the very basics
In addition to these, here are some playlists on youtube that've helped:
Foundations of Systems and Computational Biology, MIT OpenCourseWare // classroom videos, I'd suggest to check specific videos for a topic of your choice rather than actually going through all of them
Computational Systems Biology, IITM // videos on the basics of systems biology, networks and modelling
Bioinformatics 101 // videos on how to use a lot of tools, however this primarily focuses on gene expression and RNA seq data
lastly, I don't know if this would be particularly helpful given what you're looking for, but this textbook on Computational Genomics with R is a blessing for Omics related Data Analysis. So if you ever need to use R in a biological context, this would be a great place to start
yeah! so these are the majority of the resources that I've used, I hope they help! Just a heads up that the links to the textbooks I mentioned in the beginning are direct download links and won't take you to any website.
If there's anything else I can help with, feel free to reach out ^=^ best of luck!
