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as a freebie
What do you want doing exactly?
and now have some reading up to do on mass spectrometry and the like. I'm looking for some inside information on what it's like working in the industry, languages they use, most important concepts etc. It'll be in everyone's interest that I succeed because it would mean less posting.
Yes. Yes I do.
but a different type
I've dabbled and worked with bioinformatists... Usually R based and looking at genomics or metabolomics... Can try and help if you've got some specific qs
If you're trying to analyse 23andme data, I'd reccomedn promethease which costs like $5
what languages would it be similar to? And when you say looking at genomics and metabolomics, I have in my head analysing long strings of (big) data, searching for patterns, compiling stats and maximising the efficiency of the code. Is that anywhere near right? I'm used to coding etc but not in this context.
Havent really come across many languages similar to R... but then again im not a bioinformatist, just someone whos done a bit using it. I know people use matlab and SPSS to analyse big data too...
So on a very simple level a lot of the work is rearranging big data (e.g gene expression values, metabolite concentrations) into forms in which you can apply statistics to it. People routinely look to do mulitivariate analyses (PCA, PLS analyses)... so basically need a good understanding of statistical concepts and how to manipulate your data matrix best for a particular analysis.
In terms of applications: so you could be looking at (clusters of) genes, miRNAs, proteins, metabolites etc that are overrepresentated in a given disease, or change in response to drug therapy etc.
Long story short - if youve got a good head for data visualisation, trasnformation and mutlivariate statistics (+ coding), youll be good
Don't work directly in bioinformatics but do economics and med stats. From my limited experienced R is quite similar to Python. Julia looks interesting, because R isn't particularly fast, which can be a limitation for big data manipulation and analysis.
strings of characters?
urgh havent explained this well at all.. will give it another go when I have more time.. but take this as an example that i helped to work on...
we had a massive data set of mirco RNAs (miRNA) levels in disease (breast cancer) and healthy controls. We wanted to identify not only if certain miRNAs were overexpressed, but also if there was any link between these RNAs and regulation by higher oncogenes...