Step-by-step Guide To Start Bioinformatics As A Career
Why Become A Bioinformatician?
Let’s start by asking: “What did I (you) care for Bioinformatics?.” If you know the answer to this question, progress will be much easier for you and you may define a clear goal on this basis.
You really have to understand why and what you really want to do in bioinformatics, or in any other discipline. If not, it will be very difficult to make any kind of development.
You’ll continue to ask the old question: “What is bioinformatics, and what can I do about it?” Any answers you receive from people are probably too complicated for a novice and most crucially possibly not useful.
You should first achieve a specific objective, which concentrates on a problem you want to explore, address and resolve.
Many of us are not going to obtain an answer to this issue and it’s difficult to get started. Don’t worry, you should have a very good understanding after reading this post about free resources available and be able to construct an action plan.
My approach is different, as my background is in computer science. I’ll show you in this article what you need to get started, whether you are graduating or not. We will examine some clearly defined processes and readily accessible sources that will help you start bioinformatics and develop a path to study. This is also how I began my shift from a generalist bioinformatics programming career.
What if you try to resolve bioinformatics difficulties without a sufficient understanding of the underlying programming?
We will concentrate on the most universal programming language, Python. It is easy to choose because of the enormous number of libraries (module/packages), the simplicity of the language and the vast community that Python provides as a fantastic language. This allows you to write a programme of any kind.
During the lecture on bioinformatics, I witnessed a number of students write 120 code lines with 4-7 functions to solve a pretty basic problem. A problem that can and should be resolved in three to five lines, if you know the tool you are using very well. In our situation, Python and the data structures are this tools.
Trying to utilise a tool to address an issue without knowing how to use it normally leads to a lack of motivation. Some (most?) things can not be solved otherwise, save one with a comprehensive understanding of the basic concepts of the instrument that you try to utilise. Without that, you will continue to try to tweak your code until it works (this will not work with more sophisticated algorithms).
In both circumstances, you won’t grasp it since you don’t have the underlying understanding of the data structures and logic utilised in the example.
You will also continue to write very awful code that works, but will slow and difficult to maintain or update in the future. Trying to solve difficulties with programming by copying code from the Internet or from video lectures is another thing you should avoid doing without knowing why this code works (or doesn’t).
Master programming fundamentals!
I strongly advocate learning Python from two sources by completing programming challenges on websites such as HackerRank. What do “fundamentals” mean? It is a minimal collection of things (programming) you must understand and practise before trying to solve any problem.
Fortunately, the list is not long at all. It is here (in a particular order):
- Variables/Data Types (integer, float, string, byte, char, boolean, etc.)
- Logic/Branching (if, else, not, or, is, >, <, ==, !=, etc.)
- Loops (for, while)
- Functions (returning a value, passing a value)
- All base data structures (arrays, lists, maps, dictionaries, etc.)
Understanding just a few things will allow you to develop a modest genetic data processing application already. You can start working on more advanced algorithms to search patterns in the genome data when you have been confident in everything described above.
You must begin learning how to learn. It’s like learning how to drive a car, you learn all the basic regulations (signs, types of roads, the logic of a road light and the operation of a car). You never drove before even in places and countries.
This is why mastering biological and/or programming fundamentals is a step you need to take. It’s no way around it.
Work on a little project to compile all you have learned.
What do I need to get started?
Before getting into the plan of action, it is important to mention these prerequisites:
- A computer.
- A good code editor that helps you (I recommend VSCode/VSCodium for simplicity. I have a VSCode for bioinformatics setup article/video here).
- A course and a book.
- A supportive community.
A supportive community can go a long way to increase your understanding if you need assistance. First, make sure you are willing to spend your time learning the foundations and foundations to get the most of whatever community you join.
If you ask basic queries in a community chat/forum, or copy the code from the internet and ask the community to repair it for you, it can come as slothful and in the majority of cases, people won’t even bother to help you.
Nobody wants to be a lazy enabler. Make sure that you establish the foundations on which you can learn and that you reach and connect with people when you are stuck somewhere along the route because then you can aid the one who stuck to the next time.
It is crucial to have these items for your success. You offer these needs and I give you all the resources needed and my personal recommendations.
A plan of action
So here we are, at the most important step. Below is a list of resources to get you started. It will give you a very strong background in bioinformatics and programming, a clear understanding of where to go next, and it will help you to choose your first project.
You only need to focus on 3 things:
- Bioinformatics course
– Free Introduction course: Coursera Course
– Rosalind bioinformatics challenges: rosalind.info
- Python Book/Video Series
– A free Python book in PDF and some other formats: Link
– Corey Schafer’s Beginners Python course: Link
- Python exercise platform
– HackerRank: Python HackerRank
Let’s talk about all of the above. Probably the best course to start with bioinformatics is this free course. It takes 4 weeks and covers biology as well as programming. There is no biology book or course on the list, thus. The website of Rosalind Herausforderungen is the same group of persons that have designed and are related to this free course.
The free course tackles some of the challenges of Rosalind. A huge 7 module course is required to complete Rosalind. Further information in Part 6 of this topic. A Rosalind profile full of resolved bioinformatics problems, with a game-like performance badge, will be a big part of your summary.
As I mentioned earlier, you should simultaneously learn Python from two sources. Reading a book and viewing videos on the same subject (Python part) will have a far better influence than just one. The videos of Corey are renowned and easy to follow. It covers most of the programming language of Python. The free library, linked above, also provides extensive coverage of Python.
Finally, after each book chapter and a video, make sure that you use the HackerRank website to solve tasks. HackerRank also offers a social profile, which you add to your curriculum vitae.
Okay! You are now ready to act. Regardless of the level of your programming or biological understanding, this first lesson is a requirement. Upon completion, you will have a pretty solid concept of the field and you will have a lot of hints and suggestions on where to go and what the bioinformatics issues are there.
You are ready to take your next step, a full seven-module course is good for the same team. Further statistics and algorithms and books, which are discussed in the following section, are also recommended.