Problems? Is your data what you think it is? | |
PerlMonks |
comment on |
( [id://3333]=superdoc: print w/replies, xml ) | Need Help?? |
Hi Madragh Rua,
Disagree with you. "Use right tool for right job" is a good phrase in theory but not so practical. How many languages can u master properly? Max 2 or 3. If u know more than that then u must be genius or u can't judge ur mental capacity. While with any one language u can touch the altar, sometimes a second language is needed to fill in deficiencies of first language u learn. That's it. Don't start telling people to learn more and more things. Then they can't write efficient code and also can't master different application areas (eg: DBMS, Networking etc. all).
Hi Tritan,
This is for u. Believe my words and u will be successful. Two languages to learn for bioinformatics.
1) Perl
2) C We can a) exploit R with perl b) develope graphics with perl (check openGL + perl combo) c) do parallel processing d) develop web apps (using catalyst framework,modperl combo) e) do anyting u can imagine. Use "C" in-between for efficiency. Over a period of time, we will have much more faster interpreter in perl and also an unparalleled amount of free libraries added to CPAN. Ignore others comments on perl as write only language. Just write clean perl code following some good rules. That's it. I already used perl for heavy graphics, parallel processing, microarray analysis etc. so my experience is first hand. Java is good too but I don't like weight. Choose Moose for OOP in perl. Cheers, ur man In reply to Re^2: perl's long term place in bioinformatics?
by Anonymous Monk
|
|