Dear All,
I'm now deciding to learn Perl, mostly for bio-analysis in my future research. Can you suggest any good textbook with concepts and hands-on for self study of Perl?.
Thank you.
It doesn't hurt to learn multiple languages - I'm sure Khuynh Bui has good reasons to want to pick it up. Traditionally, people start with the llama book (https://en.wikipedia.org/wiki/Learning_Perl). The "perl for bioinformatics" book, also from O'Reilly, isn't that great. Beyond that, I've had by far the best help from perlmonks.org
Ofcourse not. But if someone wants to start from scratch and just don't know whats and hows, its better to direct them towards which is relatively easier. Since they don't know much about this kind of stuff, directing towards better option might be a good option.
The Pythagorean theorem is old. Wheels are old. The shell, C, C++, Fortran, etc. are also old. They all remain useful tools for problem solving.
There is nothing wrong with Perl. A good modern text would be Modern Perl for general purpose programming. You can get it for free as well. The Perl documentation is also good.
Keep in mind it is easy to find outdated materials. Anything that discusses CGI, as if it were still recommended, is worth ignoring.
For more specific things, you might want to check on the Perl Data Language lists, Perl Monks, or the Perl Facebook group.
Amy Johnson
: Rumors of Perl's obsolescence are greatly exaggerated:Extracting coronavirus SARS-CoV-2 spike protein sequences with BioPerl
http://blogs.perl.org/users/zubenel/2020/03/extracting-coronavirus-sars-cov-2-spike-protein-sequences-with-bioperl.html
Amy Johnson
The idea that there can only be 1 way to solve a problem is extraordinarily narrow in the best case, and absolutely false in the common one, where we are trying to balance multiple criteria against one another.https://en.wikipedia.org/wiki/Multiple-criteria_decision_analysis
Quote:
"MCDM is concerned with structuring and solving decision and planning problems involving multiple criteria. The purpose is to support decision-makers facing such problems. Typically, there does not exist a unique optimal solution for such problems and it is necessary to use decision-maker's preferences to differentiate between solutions."
In a multiple criteria decision problem, there can be (and often are) multiple solutions. In programming, we try to balance machine resources (time/space) along with human ones. I'd say this strongly supports the Perl philosophy of TIMTOWTDI (There is more than one way to do it).
As there are many ways to solve a problem, there are also many kind of people. Some talks in a more logical and practical way and some just keep on argues without putting the question in the context.
If pythagoras theorm can solve the bioinformatics problem, or wheel can be rolled to do some task in sequence data analysis, developers are just wasting time. They should be focusing on some circular motion pythgorean algorithm to bioinformatics.
Why the person is using modern computer/laptop or smartphone to argue on this topic, why not switch to vaccume tubes?
Or why to learn Perl? Its just implementation of C. Better to learn C instead?
May be someone has to understand the concept of evolution. Its not just happen in biology, its happens everywhere, even in material world too.
Please so not drag me in any useless discussion of importance of computer language without putting it in the context of main question.
Quote:
"As there are many ways to solve a problem, there are also many kind of people. Some talks in a more logical and practical way and some just keep on argues without putting the question in the context."
Context: Perl was used in bioinformatics for a long period of time before Python became popular.
Your premise: that Python is more suitable than Perl is based on popularity. I'd say you are making the argumentum ad populum fallacy, which is too common in technological discussions.
Your implication that using Python is "logical" is unfounded. There may be an argument that it is practical, but you haven't made that one.
Fact: Popularity and utility are distinct things. Things don't necessarily cease to be useful simply because they are not popular. Perl and Python are very similar languages semantically. But the advantages of Perl (flexibility) don't get noticed enough.
Quote:
"If pythagoras theorm can solve the bioinformatics problem, or wheel can be rolled to do some task in sequence data analysis, developers are just wasting time. They should be focusing on some circular motion pythgorean algorithm to bioinformatics."
If you use any statistical analysis, especially procedures that rely on the normality assumption, you indirectly rely on the Pythagorean theorem every single day. Your elevation of tools (a particular programming language) over declarative knowledge (ie. mathematics) leaves you at the mercy of fad and fashion.
The OP asked about resources to learn Perl. Mentions of Python are -- strictly speaking -- off topic and irrelevant. Only 2 of the multiple posts in this thread that provided specific resources for learning the language.
Try this books
https://www.oreilly.com/library/view/beginning-perl-for/0596000804/
https://www.amazon.in/Programming-Bioinformatics-Biologists-Curtis-Jamison/dp/8126504722
https://www.amazon.in/Mastering-Perl-Bioinformatics-James-Tisdall/dp/0596003072
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