Forum:How to self-study (get onto) Bioinformatics and Data Analysis for Genomic, for working with real life genomics data?

Question

[WUSCHEL]

My background is wet lab molecular biology & biotechnology and have not taken any bioinformatics course. Also, I have not mastered any programming language, but know some basics of R, a little.

How can I self-study / get into Bioinformatics and Data Analysis for the Genomic field?

Can someone guide me step by step if possible with tips/ with your experiences/ opensource resources /, to get onto the track for analyzing the real-life project with the time?

BTW, I'm 30 years old. Am I too old for the field?

Apologies if this is an off question. But this is the right place to ask this question.

[GenoMax]

BTW, I'm 30 years old.

I am going to suggest that you sit down and do a "risk analysis". Talk with your peers/friends people you trust/respect. While it is good to supplement your experimental knowledge with informatics (and perhaps long term think about switching to it) a drastic about turn may be risky to try at this stage. Do you have a family that you need to support (and in turn have support to do this from)? That should always be factored into any decision you make.

In any case do things gradually so you have an option to turn around and go back, if you must.

[WUSCHEL]

This is a good piece of advice :) genomax! No, I'm not planning to solely turn in to the new subject. Just trying to learn the techniques to analyze my own data!

[GenoMax]

Then you are on the right track. Remember to have fun while you learn. Good luck!

Answer 1

[Joe]

I've changed this to a Forum, as I think it fits better than a question since there isn't going to be a single correct answer.

My feeling about bioinformatics, and programming in general, is that you first and foremost need a problem you want to solve. It is not easy to just sit down in front of a computer and code for the sake of coding.

I don't think your age matters, especially if you're a fairly quick learner. Here are the steps I might take if I were in your position:

1. Learn some practical coding basics.

You can look at resources like Project Rosalind which will teach you the basics. You can learn about file formats and data representations, and also begin to master a programming language. You've tagged the post with Python, which I would strongly advise as a first programming language for the field.

...or...

You can dive in at the deep end. If you have a problem in mind you want to solve, start breaking it down in to its conceptual components and get stuck in writing something to achieve that particular peice of logic.

2. Think of a biological quesion.

It sounds to me like you plan to continue self-studying, rather than lookinf to join a research group or similar. If that's the case, you need to have a biological question you want to answer. Bioinformatics is a tool, but it isn't really the question.

3. Find some data

This is the tricky bit to my mind. Though I've listed it as 3, its probably on par with point 2. If you have a question, you need some data (and the right data) to help you probe the theory. What data you can and cannot use will both influence, and be influenced by, the question.

As a 'lone' researcher, you will be limited to public datasets. While this isn't itself an issue, since there's lots out there, it does mean that you cannot guarantee the data hasn't already been mined for your question. I'm guessing your physical resources such as computing power are going to be limited too, so you might need to be clever with what you want to do. Analysing terabytes of metagenomic data is likely out of your reach at the moment for instance.

4. Get stuck in

If you've got all the above, just dive in and start exploring the data! You will learn the most by doing.

[Joe]

I will just add that I think the short answer is probably that you will struggle somewhat trying to 'go it alone'. Research/science isn't what it used to be. The age of single researchers advancing science in leaps and bounds of inspiration are largely gone. I can count on one hand the single author papers I've seen in recent years I think (especially if you exclude review articles).

[WUSCHEL]

Thank you very much, Dr. Healey. I appreciate your kind suggestions.

Currently, I'm a postgrad student (MolBio), I'm interested to explore the bioinformatics would be great if I can understand how to. Would be great if I can read what questions have been answered (with what kind of tools/approaches have taken) during past, what kind of questions can be answered with the bioinformatics. When I see the papers, I see only the figures, have not any clue how they landed in there :)

Just thinking for the future career, I'm interested to master some techniques in programming/data analysis which would be help.

Thank you.

[Joe]

I would absolutely encourage you to try and learn new informatics skills on top of your molecular biology experience.

Bioinformaticians who have experimental biological experience are a rare and valuable breed - so use informatics as well not instead! :)

Answer 2

[Benn]

If you have a biological background, focus on learning more about the informatics part. You know a little about R, if you want to do bioinformatics, learn a lot about R. Try to make functions, and maybe even packages. Also learn bash, so read books such as unix in 24 hours etc. And last, when you learn stuff, also try to keep using it. When not using the stuff you learn, you lose it again.

Answer 3

[michael.ante]

To learn python for bioinformatics, I'd recommend using Rosalind.

It explains problems, how to solve these, and provides exemplary data.