“What is a k-mer? And this algorithm here, how does it work? Wait, is this code written in Python? Here, even today I have to worry, I have to study, but where do I get this information? "

You cannot imagine how many times I find myself in such situations during my studies in bioinformatics, but my tenacity has led me to devise a lot of ways to fill the various gaps that inevitably present themselves in my path of study in the world of bioinformatics.

Today I will talk to you about how I do my personal study with the aim of becoming a bioinformatician. Obviously with regard to biological issues I am more advantaged, but it is clear even there it is sometimes necessary to review or study something new. In fact, I have a degree in Agricultural Sciences and I am earning a master's degree in Plant Biotechnology, so I inevitably chew organic more.

One of he first things that I realized is that to become a bioinformatician I must have excellent knowledge in statistics. It is clear, we must not get lost in the definitions and mathematical calculations that are hidden behind the different statistical tests applied during a study but understand the principle of that test, that is to understand when it is useful to use it and what it allows to do. Statistics, in fact, is a tool that allows us to clearly understand a phenomenon, the reality that surrounds us without falling into numerous and insidious cognitive errors (the so-called bias) that our damned brain is evolutionarily led to create. However to use statistics, and in particular to analyze and manipulate the biological information, it is necessary to know programming languages ​​in order to communicate and make the computer perform these operations.

Wanting to be schematic and concise, I can tell you that to become a bioinformatician it is necessary:

  1. Know in a very general way how a computer works.
  2. Knowing some programming languages ​​that allow us to communicate with the computer, among these in the bioinformatics field Python, Perl, R are very useful. In addition it is necessary to know how to use commands in bash, but don't worry we'll talk about it.
  3. Learn about molecular biology, genetics, genomics and evolution concepts, as well as pathology and much more.

Where to recover all this? Well there are several tools:

  • The books. I know, buying books is expensive and reading them is tiring sometimes but trust me a good book really makes the difference. I often find myself studying on books or even reading purely divulgative books that help me on my path. In the menu you can discover the appropriate section "Recommended Books" in which you will find a series of useful books that I have purchased and that I consider valid.
  • Scientific researches. When it is necessary to carry out a bioinformatics study it is a must to search Google Scholar for similar scientific research in order to understand which tools are used in that area. I often find myself deepening some themes and gaining greater clarity on some concepts thanks to these readings.
  • Online courses. Online courses are a real blessing at times and there are myriad of them. The portals that I frequent most to find quality courses are Coursera and Edx but believe me the web is full of courses that allow you to simply learn programming languages ​​as well as more specific aspects of bioinformatics. Also in this case you can find at the end of the page several useful links for some courses that I have followed or that I intend to follow.
  • Master in bioinformatics, online or not. Unfortunately I do not have the possibility to follow a specific master in bioinformatics at the moment but there are several useful options. At the bottom I put some useful links about it.
  • Phd in Bioinformatics. Searching the web for jobs as a bioinformatician, I have noticed that many of the vacancies are aimed at individuals who have at least earned a PhD or Master in bioinformatics, so take this route into account as well.
  • Taking a bioinformatics or statistics course in the free choice exams available during the university course can be a beginning but it is not enough.
  • YouTube and podcasts. There are some very good YouTube channels and podcasts available online that can be consulted to acquire programming skills and more. You will find several useful links at the bottom of the article.
  • Finally, I just have to quote the well-known Anglo-Saxon saying "practice makes perfect”, just to tell you, try, try and fail continuously, replicate projects and codes in order to learn more and more how to use certain bioinformatics tools. In this regard, the Rosalind site offers several useful exercises with increasing difficulty based on the Python programming language. (http://rosalind.info/problems/locations/).

Well I think I have said everything for today, I hope that now you have some more tools to start a personal study path in the world of bioinformatics. If you have any comments or questions to ask me, please use the section below in the blog, and in order not to miss the next articles I suggest you subscribe to the blog in order to receive an email notification.

Bye and see you soon.

Useful online course titles (look for them on coursera):

  • Genomic Data Science Specialization. Be a next generation sequencing data scientist. Master the tools and techniques at the forefront of the sequencing data revolution. (Johns Hopkins University)
  • Bioinformatics Specialization. Journey to the Frontier of Computational Biology. Master bioinformatics software and computational approaches in modern biology. (San Diego)
  • Plant Bioinformatic Methods Specialization (University of Toronto)

Interesting master links:

Interesting YouTube links:

Interesting podcast links: