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python implementations of bioinformatics algorithms to solve Rosalind problems

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BA10 - Hidden Markov Models.ipynb
BA10 - Hidden Markov Models.ipynb
 
 
BA10E -profile HMM_week2.ipynb
BA10E -profile HMM_week2.ipynb
 
 
BA10G - Alignment to profile HMM .ipynb
BA10G - Alignment to profile HMM .ipynb
 
 
BA10H-estimate HMM parameters.ipynb
BA10H-estimate HMM parameters.ipynb
 
 
BA10I - Viterbi Learning.ipynb
BA10I - Viterbi Learning.ipynb
 
 
BA10J - Forward-Backward - Soft Decoding problem.ipynb
BA10J - Forward-Backward - Soft Decoding problem.ipynb
 
 
BA10K - Baum-Welch Learning.ipynb
BA10K - Baum-Welch Learning.ipynb
 
 
BA10f- profile HMM with pseudocounts.ipynb
BA10f- profile HMM with pseudocounts.ipynb
 
 
BA11_A- Graph(spectrum).py
BA11_A- Graph(spectrum).py
 
 
BA11_B - Decode(ideal_spectrum).py
BA11_B - Decode(ideal_spectrum).py
 
 
BA11_C- Vector(peptide).py
BA11_C- Vector(peptide).py
 
 
BA11_D - Peptide(vector).py
BA11_D - Peptide(vector).py
 
 
BA11_E - Peptide Sequencing problem.py
BA11_E - Peptide Sequencing problem.py
 
 
BA11_F - Peptide Identification problem.py
BA11_F - Peptide Identification problem.py
 
 
BA11_G - PSM Search.py
BA11_G - PSM Search.py
 
 
BA11_H - Spectral dictionary count.py
BA11_H - Spectral dictionary count.py
 
 
BA11_I -Prob_spec_dict.py
BA11_I -Prob_spec_dict.py
 
 
BA11_J - Spectral alignment.py
BA11_J - Spectral alignment.py
 
 
BA1_A - count pattern in text.py
BA1_A - count pattern in text.py
 
 
BA1_B - most freq words in a string.py
BA1_B - most freq words in a string.py
 
 
BA1_C - find reverse complement of string.py
BA1_C - find reverse complement of string.py
 
 
BA1_D - find positions of pattern in genome.py
BA1_D - find positions of pattern in genome.py
 
 
BA1_E - find kmer clumps in genome- clump finding problem.py
BA1_E - find kmer clumps in genome- clump finding problem.py
 
 
BA1_F - Minimum skew prefix in genome.py
BA1_F - Minimum skew prefix in genome.py
 
 
BA1_G- Hammond Distance between two seqs.py
BA1_G- Hammond Distance between two seqs.py
 
 
BA1_H - approx matches pattern in seq.py
BA1_H - approx matches pattern in seq.py
 
 
BA1_I - most freq kmers w mismatches.py
BA1_I - most freq kmers w mismatches.py
 
 
BA1_J - find most freq kmer+rev comp combo in seq.py
BA1_J - find most freq kmer+rev comp combo in seq.py
 
 
BA1_K - freq array of a string.py
BA1_K - freq array of a string.py
 
 
BA1_L -Pattern to number.py
BA1_L -Pattern to number.py
 
 
BA1_M- number to pattern.py
BA1_M- number to pattern.py
 
 
BA1_N - d-neighborhood of a string.py
BA1_N - d-neighborhood of a string.py
 
 
BA2_A - motif enumeration.py
BA2_A - motif enumeration.py
 
 
BA2_B - find a median string.py
BA2_B - find a median string.py
 
 
BA2_C - find profile-most prob kmer in seq.py
BA2_C - find profile-most prob kmer in seq.py
 
 
BA2_D - greedy motif search.py
BA2_D - greedy motif search.py
 
 
BA2_E - Random motif search.py
BA2_E - Random motif search.py
 
 
BA2_E- Greedy Motif Search w Pseudocounts.py
BA2_E- Greedy Motif Search w Pseudocounts.py
 
 
BA2_F - Random motif search.py
BA2_F - Random motif search.py
 
 
BA2_G - Gibbs Sampler motifs.py
BA2_G - Gibbs Sampler motifs.py
 
 
BA2_H - Dist(pattern, Seqs).py
BA2_H - Dist(pattern, Seqs).py
 
 
BA3_A - Generate the k-mer composition of a string.py
BA3_A - Generate the k-mer composition of a string.py
 
 
BA3_B - genome from kmers list (trivial).py
BA3_B - genome from kmers list (trivial).py
 
 
BA3_C - Overlap graph from kmers.py
BA3_C - Overlap graph from kmers.py
 
 
BA3_D - Construct DeBruijn graph of seq.py
BA3_D - Construct DeBruijn graph of seq.py
 
 
BA3_E - DeBruijn graph from kmers.py
BA3_E - DeBruijn graph from kmers.py
 
 
BA3_F - Eularian cycle in digraph.py
BA3_F - Eularian cycle in digraph.py
 
 
BA3_G - Eulerian Path in Digraph.py
BA3_G - Eulerian Path in Digraph.py
 
 
BA3_H - Reconstruct seq from reads.py
BA3_H - Reconstruct seq from reads.py
 
 
BA3_I - k-universal circular string problem.py
BA3_I - k-universal circular string problem.py
 
 
BA3_J - reconstruct string from paired reads.py
BA3_J - reconstruct string from paired reads.py
 
 
BA3_K - contigs from reads.py
BA3_K - contigs from reads.py
 
 
BA3_L - genome assembly from read pairs -same as 3J.py
BA3_L - genome assembly from read pairs -same as 3J.py
 
 
BA3_M - Maximal branching paths problem.py
BA3_M - Maximal branching paths problem.py
 
 
BA4_A - Translate RNA to Protein.py
BA4_A - Translate RNA to Protein.py
 
 
BA4_B - find gene ORFs for peptide.py
BA4_B - find gene ORFs for peptide.py
 
 
BA4_C - theoretical mass spectrum of cyclic peptides.py
BA4_C - theoretical mass spectrum of cyclic peptides.py
 
 
BA4_D- exercise-1'6 counting linear subpeptides.py
BA4_D- exercise-1'6 counting linear subpeptides.py
 
 
BA4_E - cyclic peptide matching ideal query spec.py
BA4_E - cyclic peptide matching ideal query spec.py
 
 
BA4_F - Scoring cyclopeptide vs experimental spectrum.py
BA4_F - Scoring cyclopeptide vs experimental spectrum.py
 
 
BA4_G - Leaderboard Cyclopeptide Sequencing.py
BA4_G - Leaderboard Cyclopeptide Sequencing.py
 
 
BA4_G++ -> exercises for tryocidineB1.py
BA4_G++ -> exercises for tryocidineB1.py
 
 
BA4_H - Generate the Spectral Convolution.py
BA4_H - Generate the Spectral Convolution.py
 
 
BA5_A - The Change Problem.py
BA5_A - The Change Problem.py
 
 
BA5_B - Manhattan Tourist Problem.py
BA5_B - Manhattan Tourist Problem.py
 
 
BA5_E - Global alignment.py
BA5_E - Global alignment.py
 
 
BA5_F - Local Alignment problem.py
BA5_F - Local Alignment problem.py
 
 
BA5_G - edit distance.py
BA5_G - edit distance.py
 
 
BA5_G++ - edit distance alignment.py
BA5_G++ - edit distance alignment.py
 
 
BA5_H - Fitting alignment problem.py
BA5_H - Fitting alignment problem.py
 
 
BA5_I - Overlap Alignment.py
BA5_I - Overlap Alignment.py
 
 
BA5_J - Affine gap penalty alignment.py
BA5_J - Affine gap penalty alignment.py
 
 
BA5_K - Middle Edge in linear space align.py
BA5_K - Middle Edge in linear space align.py
 
 
BA5_L - Hirschberg algo - Linear space Alignment*** INCOMPLETE.py
BA5_L - Hirschberg algo - Linear space Alignment*** INCOMPLETE.py
 
 
BA5_L+ middle_edge.py
BA5_L+ middle_edge.py
 
 
BA5_M - Three Seq Alignment- NeedlemanWunsch.py
BA5_M - Three Seq Alignment- NeedlemanWunsch.py
 
 
BA5_M++ -_MSA_pairwise_distance_matrix***INCOMPLETE.py
BA5_M++ -_MSA_pairwise_distance_matrix***INCOMPLETE.py
 
 
BA5_N - Topological sort.py
BA5_N - Topological sort.py
 
 
BA6_1++ how many signed permutations are there for length k.py
BA6_1++ how many signed permutations are there for length k.py
 
 
BA6_A - Greedy reversal sort.py
BA6_A - Greedy reversal sort.py
 
 
BA6_B - Counting Breakpoints.py
BA6_B - Counting Breakpoints.py
 
 
BA6_C - 2-break distance of P,Q.py
BA6_C - 2-break distance of P,Q.py
 
 
BA6_D - 2-break sorting (solved).py
BA6_D - 2-break sorting (solved).py
 
 
BA6_E - Find shared kmers in 2 seqs - creating synteny blocks.py
BA6_E - Find shared kmers in 2 seqs - creating synteny blocks.py
 
 
BA6_E+ - shared_kmers_dot_plot- synteny blocks visually.py
BA6_E+ - shared_kmers_dot_plot- synteny blocks visually.py
 
 
BA6_F - chromosome to cycle.py
BA6_F - chromosome to cycle.py
 
 
BA6_G - Cycle to Chromosome.py
BA6_G - Cycle to Chromosome.py
 
 
BA6_H - coloured edges from chromosomes.py
BA6_H - coloured edges from chromosomes.py
 
 
BA6_I - graph to genome.py
BA6_I - graph to genome.py
 
 
BA6_J - 2 break on edgelist.py
BA6_J - 2 break on edgelist.py
 
 
BA6_K - 2 break on genome.py
BA6_K - 2 break on genome.py
 
 
BA6_L - 2-break sorting.py
BA6_L - 2-break sorting.py
 
 
BA7_A - Distance matrix from tree using Dijkstra.py
BA7_A - Distance matrix from tree using Dijkstra.py
 
 
BA7_B - compute limb lengths from D matrix.py
BA7_B - compute limb lengths from D matrix.py
 
 
BA7_C - Additive phylogeny tree building algo.py
BA7_C - Additive phylogeny tree building algo.py
 
 
BA7_D - UPGMA.py
BA7_D - UPGMA.py
 
 
BA7_E - Neighbor Joining.py
BA7_E - Neighbor Joining.py
 
 
BA7_F - Small Parsimony.py
BA7_F - Small Parsimony.py
 
 
BA7_G - Small_parsimony_unrooted.py
BA7_G - Small_parsimony_unrooted.py
 
 
BA7_G++ Large Parsimony Problem.py
BA7_G++ Large Parsimony Problem.py
 
 

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Python implementations of bioinformatics algorithms

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