Rosalind Problems in Clojure
Later: Exploratory Genomics with Clojure
Earlier: Introduction to Context Managers in Python
This weekend I’ve been having a lot of fun working the Bioinformatics problems from Rosalind. Most people work them in Python, but so far they have been very amenable to Clojure except where BioPython libraries are used for access to online databases. The problems have been straightforward so far but I have enjoyed the elegance and brevity that Clojure lends the solutions.
In particular, I like this short translator from RNA sequences to amino acids:
;;; Translating RNA into Amino Acids
(defmacro deftable [tname & rest]
`(def ~tname (apply hash-map '(~@rest))))
(deftable proteins
UUU F CUU L AUU I GUU V
UUC F CUC L AUC I GUC V
UUA L CUA L AUA I GUA V
UUG L CUG L AUG M GUG V
UCU S CCU P ACU T GCU A
UCC S CCC P ACC T GCC A
UCA S CCA P ACA T GCA A
UCG S CCG P ACG T GCG A
UAU Y CAU H AAU N GAU D
UAC Y CAC H AAC N GAC D
UAA Stop CAA Q AAA K GAA E
UAG Stop CAG Q AAG K GAG E
UGU C CGU R AGU S GGU G
UGC C CGC R AGC S GGC G
UGA Stop CGA R AGA R GGA G
UGG W CGG R AGG R GGG G)
(defn to-protein [s]
(->> s
(partition 3)
(map (partial apply str))
(map symbol)
(map proteins)
(take-while #(not= % 'Stop))
(apply str)))
The body of the proteins table is literally cut-and-pasted from the
problem page (click on “RNA codon table”). I think it’s a good example
of using macros to provide a little bit of syntactic sugar to make the
code just a little more readable and elegant, or to encode domain
facts as directly as possible.
This and my other solutions so far are up on GitHub.
Later: Exploratory Genomics with Clojure
Earlier: Introduction to Context Managers in Python