Corey
by Corey
1 min read

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  • articles

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  • Bioinformatics

I’ve been studied bioinformatics for more than three years, but still not a bioinformatician yet.

To be a bioinformatician is my dream since I stepped into this mysterious world. In my opinion, there are two essential skills for a seasoned bioinformatician: coding and scientific writing.

Coding holds a crucial role in bioinformatics. The amount of biological data is expanding. Steady coding ability will facilitate your experience when dealing with multi-omics data and biomedical text data. When dealing with text data, python is an excellent choice to parse text, analyze segment and yield information. While when you need some statistics or visualization, R is impassable. The whole task processed under *nix operating system. When an algorithm is fully developed, you should deploy it as software to let others use. It is a tough step because build a user-friendly software is not an easy thing. So, with all these considerations, coding can never be too vital to a bioinformatician.

Besides, scientific writing is just as critical as coding, which I haven’t noticed for a very long time. As a bioinformatician, or to-be bioinformatician, speak out of your idea in a proper way is essential for the whole career. Put forward a problem you want to investigate. Tell the reader why you want to do this (Introduction), explain how you do that (Method) and what did you get (Result). Finally, a concrete discussion can make your manuscript complete.

At last, polish the manuscript to a real paper. Please bear in mind that Method and Result cannot disperse with each other. In this part, the logical chain is the backbone to all subject. The best paper is written with a proper logical chain and specific evidence. To me, logical chain first. Unfold a logical node from a logical chain is a skillful method, which needs to input my whole life into it.

At the end of this small piece of text, I know where I want to go, do you?