baum-WelchLearning.py :
An implementation of Baum-Welch learning to generate the transition and
emission probabilities from a sequence.
baum-WelchLearning.txt :
Example input and expected output

cyclopeptide.py :
This program can determine the possible sequences of a cyclopeptide given an
ideal spectrum (where all subsets of the full length sequence are included).
cyclopeptide.txt :
Example input and expected output

cyclospectrum.py :
This program generates the theoretical spectrum of a cyclic peptide.
cyclospectrum.txt :
Example input and expected output

deBruijnGraph.py :
This program generates a DeBruijn graph using specified lengths of a given
string.
deBruijnGraph.txt :
Example input and expected output

proteinDecoder.py :
Finds all substrings of text encoding a peptide given a peptide sequence and
nucleotide sequence.
proteinDecoder.txt :
Example input and expected output

softDecoding.py :
This program generates the probability of a sequence being in a possible state
given its emission sequence, emission matrices and transition matrices.
softDEcoding.txt
Example input and expected output

viterbiLearning.py :
This program implements Viterbi learning to generate the transition and
emission probabilities from a sequence.
viterbiLearning.txt
Example input and expected output