Forum:Non biology & computer professional interested in bioinformatics
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2 days ago
ASU • 0

I am from a non biology background. I was in IT profession for 3 years working with DB and into teaching profession in colleges under computer science department. As a PhD work can I go with bioinformatics ( as I am a non biology student but interested in that ) is it a good option. Can you please help me out on this. Also what level of knowledge in this is required to pursue my PhD - bioinformatics in machine learning,

computer-science bioinformatics machine-learning • 241 views
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If you are joining a PhD program then no doubt your department/mentor/PhD committe will make sure that you take appropriate courses to build a strong basic understanding of principals. Depending on your background/departmental regulations this may require more or less formal courses. You will probably learn more from interacting with biologists as you work with them to solve (immediate) problems than in formal classes (at least the biology part).

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You will probably learn more from interacting with biologists as you work with them to solve problems than in formal classes (at least the biology part).

The poster will probably learn more biology needed to solve the immediate problem from those they interact with. I seriously doubt that they will learn through collaborative personal interactions about chemical principles of life, molecular structure, biochemistry, molecular genetics, or any of the foundational biological principles. There is a reason why people take formal classes.

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One would assume that some of these fundamentals would have been covered in secondary education. I did say in my comment that OP's mentors/department will require them take formal courses as needed. My comment was indeed about acquiring immediate knowledge needed to solve biological problems OP may be working on. I have added a word to clarify that above.

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2 days ago

An interest in the topic combined with your computer expertise might be enough to start off.

but, you will (whether you like it or not) have to increase your biological knowledge over the years after that. Bioinformatics is and remains a science that tries to solve BIOLOGICAL problems (and thus not solely computational problems) so a growing knowledge of the biology will only increase your "value" and will makes things clearer along the way.

(just my personal two cents of course :) )

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2 days ago

There's two groups of people in bioinformatics; the biologists who learn some programming, and the programmers who learn some biology. They have different views and solutions and are both very important. Don't worry about not having the background yet, learning and interest is all you need get up to speed.

You will need to understand the state of the art, to ensure your thesis is not redundant or tried-and-failed already. Try to leverage your skills of course, there's plenty of database work in bioinformatics.

This is not an uncommon question by the way.

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There's two groups of people in bioinformatics; the biologists who learn some programming, and the programmers who learn some biology.

This is like saying there are 10 types of people: those who understand binary and those who don't. And then bunch of others who are somewhere on the spectrum. First, there are world-class bioinformaticians who don't program at all, not to mention the whole spectrum of programmers who don't understand any biology beyond what is needed to solve 1-2 problems.

People call themselves bioinformaticians - and legitimately so - for reasons that have little to do with the biology:programming ratio. Some of the best bioinformaticians I know are by education physicists, virologists, crystallographers, mathematicians. In general, these are very bright people who are driven to learn new things and contribute to solving problems, rather than being biologists or programmers.

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You're absolutely right. I was grossly categorizing the mathematician as a programmer, and the virologist as a biologist. From the perspective of an I.T. professional (original poster), it's hard to know the difference in crystallography and genetics, that sort of thing.

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2 days ago
Mensur Dlakic ★ 14k

I don't mean to categorize people in what I write below. It is just a personal opinion and an attempt to lay out different ways of becoming a bioinformatician that are rooted in our individual preferences.

In simple terms, one could argue that becoming a bioinformatician is simply a matter of adding some biology to an existing IT/programming/informatics knowledge or vice versa. One can do a whole RNAseq experiment, from the wet lab experiments to data analysis, with limited biology knowledge other than RNA expression, and with just enough ability to run prepackaged scripts and make tiny modifications to them such as file locations or p-value cutoffs. I have interacted with them frequently, and they do just fine for themselves even with the aforementioned limitations. I wouldn't want to train students with such limited outlook on research, but there is not doubt that ultra-specialization works.

A bigger question for me is why anyone wants to become a bioinformatician, and from there it becomes easier to decide what the missing ingredients are. Some people want to get into bioinformatics because it is hot and pays well - or at least they think so. As I said above, there is nothing wrong with earning a living by knowing just enough of biology and these other fields. In fact, some people who are in this group are so good that they become irreplaceable.

Then there is a bioinformatician who is an excellent collaborator, and is stronger on one side than the other. These are in general very capable and professional, and can get away with being much stronger in biology or in everything else because their expertise is complementary to the whole team rather than driving the whole project.

The most difficult to become, and thus rarest, is a bioinformatician who can lead a group and drive the whole research endeavor. To achieve this means spending a lot of time learning about science and its process in general, and not just biology or just computers/programing/math. It means being able to talk with people who know more in their area of expertise but not necessarily can synthesize all the information. It involves life-long learning to stay abreast of developments in all areas. Not very many people would have this as their goal early in their careers because hardly anyone decides when they are younger than 30 that life-long learning will be what they do. It is usually something that develops later, so I think this group for practical purposes can be eliminated from the early consideration of what kind of bioinformatician one wants to be.

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