Concerning Bioinformatics and Pearl (PERL)

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SUMMARY

The discussion centers on the programming languages relevant to bioinformatics, specifically addressing the comparison between PERL and R. Participants highlight R's popularity and utility in bioinformatics, suggesting it as a preferable choice for newcomers. The conversation also references the importance of code reusability in R, which allows users to leverage existing algorithms from public repositories. A link to an article comparing bioinformatics programming languages is provided for further reading.

PREREQUISITES
  • Basic understanding of bioinformatics concepts
  • Familiarity with programming languages, particularly PERL and R
  • Knowledge of code reusability and algorithm sourcing
  • Experience with MATLAB for comparative context
NEXT STEPS
  • Explore R programming for bioinformatics applications
  • Research code reusability practices in R
  • Read the article on bioinformatics programming languages for a broader perspective
  • Investigate public repositories for R algorithms and libraries
USEFUL FOR

Bioinformaticians, programmers transitioning to bioinformatics, and anyone interested in optimizing their programming skills with R and PERL.

moriheru
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greetings,
I heard of Pearl and intend on learning it, yet I do have a question:
are there any better programming languages than pearl or more used and popular?
 
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I always hear about R when I hear about bioinformatics, but I have no experience with it, I'm more of a MATLAB guy (braces for python assault).
 
There is such a language as "Pearl", but I would bet that you mean "PERL".
I have not programmed in biometrics, so my advice is limited. Here is an short article by someone who has:http://www.molecularecologist.com/2012/11/a-comparison-of-bioinformatics-programming-languages/

The one thing that is not mentioned in that article is reusing code. If "R" is a language that is commonly used for informatics applications, then it might make sense to go with that one first - since you may very well be able to borrow "R" algorithms from public sources.
 

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