how to convert to computational biology from bioinformatics
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3 months ago
biohubx • 0

Hello,

I have been analyzing different NGS data using available software and custom code. But I have not developed any algorithms. Now I want to convert to computational biology from data analysis. Do you guys think it is possible to get that?

bioinformatics computational-biology • 823 views
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Hi, it's "software" and "code", not "softwares" and "codes". Both of those words are uncountable entities and do not have separate plural forms.

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Of course it's possible. If you want to go deeper in a given direction, study that direction. "Analyzing NGS data" can mean just about anything. But if you want to go deeper into Computational Biology, study that field, study Data Science, study Computer Science. Algorithms, the path for their development, and the reasons for developing them will become clearer.

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yes, I am trying to apply for a postdoctoral position working on computational biology. But it is pretty hard for me. Several labs require more computational background, not data analysis.

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You should apply for jobs the requirements of which match your skills. One employer may label a job as 'Computational Biologist', which, to another employer, may be 'Bioinformatics Analyst' - there is no difference. Please focus on the actual Job Description and the requirements.

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3 months ago

The whole "what is the difference between computational biology and bioinformatics, and is there even a difference" is as old as using computers to do biology, and doesn't really get us very far. Personally, I agree that there are several jobs that connect biology and computers, and they tend to require different sets of skills and background. Your definition of someone who runs analysis tools written by someone else, vs someone who develops those tools is a not uncommon one.

For your post it seems like you have been an analysist and would like to get more into method/tool development? The easiest way to do this is to do it :). By that I mean, I would look at the work you do, and see if there is either:

a) something you do regularly that at the moment is a long process, but that its the same every time and so could be standardized, and which might benefit you and others. So, for example, imagine there is a type of plot that you find you use over and over again, building it from scratch manually each time. Try turning this in a package. Or I realized that I often spent time randomizing read locations of reads within genes, so I wrote a package to do that for me.

b) think of an analysis that you think would be good to be able to do, but there is, as yet, no way of doing it. Write a tool to do it.

In both cases the idea is to do something at will be useful for your current work, but that others might also find useful.

Learning-wise, I think often what people miss out on is statistics, which is such a massive part of methods development, so if you were going to do some formal learning, I recommend doing some advanced mathematical statistics classes.

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wow. Thanks. your suggestions are great! yes, what I am good at doing is perfroming data analysis, such as Hi-C and ATAC-seq and integrative analysis of multi-omics.

So I want to convert to computational biology from my current status.

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3 months ago

Hi, they are virtually the same. Perhaps you could focus more on just acquiring more skills and experience, that is, in place of trying to define yourself as a 'Computational Biologist' or 'Bioinformatician'.

Your post is severely lacking in details, though, and therefore any advice that you receive will be general.

Kevin

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what details you want to get? am currently a postdoc working on data analysis, including Hi-C/ChIP-seq/ATAC-seq/RNA-seq, and perforing integrative analysis of multi-omics. but now I want to go to computational biology.

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There's no difference. Employers don't care whether you call yourself a 'bioinformatician' or a 'computational biologist'. What is the difference between the 2? What matters is the skills that you have, and these are best presented on your CV and during interview.

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3 months ago
Mensur Dlakic ★ 14k

Computational Biology and Bioinformatics are the same in a sense that "articulate" and "to articulate" are, which is to say that there is some overlap between their meanings. Yet Computational Biology is a more general term, which is why Statistical Ecology will fall under Computational Biology but not under Bioinformatics.

The National Institutes of Health Biomedical Information Science and Technology Initiative Consortium put out the following definitions:

Bioinformatics: Research, development, or application of computational tools and approaches for expanding the use of biological, medical, behavioral or health data, including those to acquire, store, organize, archive, analyze, or visualize such data.

Computational Biology: The development and application of data-analytical and theoretical methods, mathematical modeling and computational simulation techniques to the study of biological, behavioral, and social systems.

I don't agree completely with their definitions because they don't emphasize the role of informatics molecules (nucleic acids and proteins) in Bioinformatics, but it is a start. I like the definition of Bioinformatics put forth here (full text is here): Bioinformatics is conceptualizing biology in terms of macromolecules (in the sense of physical-chemistry) and then applying "informatics" techniques (derived from disciplines such as applied maths, computer science, and statistics) to understand and organize the information associated with these molecules, on a large-scale. For my students, I sometimes cobble together some of their keywords and shorten this to: studying macromolecules by applying "informatics" techniques to understand and organize the information on a large-scale.

Definitions aside, anything can be learned. People go to medical or engineering schools and later become lawyers, which I think is at least a comparable stretch to switching from the two fields considered by the original poster.

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I am currently a postdoc working on data analysis, including Hi-C/ChIP-seq/ATAC-seq/RNA-seq, and perforing integrative analysis of multi-omics. but now I want to go to computational biology.

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