Coding for Biology
Foundational programming on biological data: strings, counting, complements and comparisons.
Learn The Language of Modern Biology
Master
Master
Bioinformatics
by coding algorithms.
Sharpen your skills with 52 bioinformatics coding problems in Python and R. Learn the fundamentals, build real skills, and go beyond the textbook.
See how it works ↓✓ 0 practice problems
✓ Python 3 & R 4.0
✓ Real-time code execution
● ● ● dna_nucleotides.py
PYTHON 3
# Counting DNA Nucleotides
def count_nucleotides(dna_string):
return {
'A': dna_string.count('A'),
'C': dna_string.count('C'),
'G': dna_string.count('G'),
'T': dna_string.count('T')
}
# Sample Input: AGCTTTTCATTCTGACTGCA
print(count_nucleotides("AGCTTTTCATTCTGACTGCA"))
✔ Verdict: Accepted (Output: {'A': 5, 'C': 4, 'G': 4, 'T': 7})
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A glimpse of your in-browser coding workspace
52practice problems
3 levelsstart simple, build up
Python + Rpractice with real tools
Instant judgelearn from each run
CHOOSE YOUR STARTING POINT
Follow a learning path
Move from programming fundamentals to computational methods.
Bioinformatics
Applied sequence analysis: motifs, restriction sites, translation, k-mers and assembly.
Computational Biology
Algorithms and models: dynamic-programming alignment, phylogenetics and hidden Markov models.
Python Foundations
A PRACTICE LOOP BUILT FOR LEARNING
Pick a problem
Progress through curated problems: Foundational (nucleotide counts), Intermediate (k-mers, RNA splicing) and Advanced (affine gap alignment, Viterbi HMMs).
Write and run code
Write Python or R in the Monaco editor and run it in your browser against a real judge backend.
Learn from feedback
Every submission is validated against hidden test cases, including edge cases, homopolymers and length limits.
WHY CTRLDOGMA
From the Central Dogma to CtrlDogma
In molecular biology, the central dogma is the flow of genetic information: DNA → RNA → Protein, the principle that governs how life stores, transmits and expresses its code. CtrlDogma lets you control that flow — digitally.
It is the platform to practice bioinformatics algorithms, computational biology and biological data science, in a browser-based Python & R IDE.
Crick's 1958 diagram · Public Domain, Wikimedia Commons
DNA
Read the code
Treat a sequence as data: the foundations.
- Counting nucleotides
- Reverse complements
- GC content
RNA
Copy and search
Transform sequences and find the patterns in them.
- Transcribing DNA to RNA
- Finding motifs
- k-mers and splicing
Protein
Express and model
Go beyond the textbook with real algorithms.
- Translation
- Sequence alignment
- Hidden Markov models
Build fundamentalsFrom the ground up, one problem at a time.
Track your scoreSolved-problem points that add up as you grow.
Share your profileA public track record that strengthens your résumé.
READY WHEN YOU ARE
Your next solution starts here.
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