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@@ -7,8 +7,8 @@ You should have received a copy of the GNU General Public License along
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with DiaNA; if not, write to the Free Software Foundation, Inc., 51
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Franklin St, Fifth Floor, Boston, MA 02110-1301 USA
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"""
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-VERSION = "v0.2_beta"
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-RELEASE = "17032020"
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+VERSION = "v0.3_beta"
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+RELEASE = "19032020"
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SOURCE1 = "https://code.03c8.net/epsylon/diana"
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SOURCE2 = "https://github.com/epsylon/diana"
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CONTACT = "epsylon@riseup.net - (https://03c8.net)"
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@@ -19,14 +19,15 @@ DNA-equiv:
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"""
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import re, os, glob, random, time, math
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-brain_path = "datasets/brain.in"
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+brain_path = "resources/BRAIN/brain.in"
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genomes_path = 'datasets/'
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genomes_list_path = "datasets/genome.list"
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+universal_primer_list_path = "resources/PATTERNS/UPL.list"
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+dna_codons_list_path = "resources/PATTERNS/DNAcodon.list"
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genomes = {}
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seeds_checked = []
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repeats = {}
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known_patterns = []
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-dna_alphabet = ["A", "C", "G", "T"]
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max_length = 50
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def convert_size(size):
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@@ -383,27 +384,142 @@ def convert_memory_to_dict(memory): # [index] = genome_name, pattern, num_rep
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def extract_pattern_most_present_local(memory):
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memory_dict = convert_memory_to_dict(memory)
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- if memory_dict:
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+ if genomes:
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+ try:
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+ f=open(dna_codons_list_path, 'r')
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+ codons = f.readlines()
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+ f.close()
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+ except:
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+ pass
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print("[LIBRE-AI] [REPORTING] -RESEARCHING- [STATISTICS]: \n")
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total_genomes = 0
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- total_patterns = 0
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for k, v in genomes.items():
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total_genomes = total_genomes + 1
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- for m in memory:
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- total_patterns = total_patterns + 1
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- max_size_pattern_name, less_size_pattern_name, biggest_pattern_name, biggest_pattern_size, smaller_pattern_name, smaller_pattern_size, total_patterns_all_genomes, most_present_patterns_by_len_list, less_present_patterns_by_len_list = extract_patterns_most_found_in_all_genomes(memory_dict)
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- print(" * Trying -[ "+str(total_patterns)+" ]- [PATTERNS LEARNED!] against -[ "+str(total_genomes)+ " ]- [DNA SECUENCES]:")
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- print("\n + Total [PATTERNS FOUND!]: [ "+str(total_patterns_all_genomes)+" ]")
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- print("\n - [MOST-PRESENT!]: [ "+str(biggest_pattern_size)+" ] time(s) -> [ "+str(biggest_pattern_name)+" ]\n")
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- for k, v in most_present_patterns_by_len_list.items():
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- print(" * [length = "+str(k)+"] : [ "+str(v[1])+" ] time(s) -> [ "+str(v[0])+" ]")
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- print("\n - [LESS-PRESENT!]: [ "+str(smaller_pattern_size)+" ] time(s) -> [ "+str(smaller_pattern_name)+" ]\n")
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- for n, m in less_present_patterns_by_len_list.items():
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- print(" * [length = "+str(n)+"] : [ "+str(m[1])+" ] time(s) -> [ "+str(m[0])+" ]")
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- max_size_pattern_name = max(most_present_patterns_by_len_list, key=most_present_patterns_by_len_list.get)
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- less_size_pattern_name = min(most_present_patterns_by_len_list, key=most_present_patterns_by_len_list.get)
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- print("\n - [LARGEST] : [ "+str(max_size_pattern_name)+" ] bp linear RNA")
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- print(" - [SHORTEST]: [ "+str(less_size_pattern_name)+" ] bp linear RNA\n")
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+ if memory_dict:
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+ total_patterns = 0
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+ for m in memory:
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+ total_patterns = total_patterns + 1
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+ max_size_pattern_name, less_size_pattern_name, biggest_pattern_name, biggest_pattern_size, smaller_pattern_name, smaller_pattern_size, total_patterns_all_genomes, most_present_patterns_by_len_list, less_present_patterns_by_len_list = extract_patterns_most_found_in_all_genomes(memory_dict)
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+ print(" * Trying -[ "+str(total_patterns)+" ]- [PATTERNS LEARNED!] against -[ "+str(total_genomes)+ " ]- [DNA SECUENCES]:")
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+ if total_patterns_all_genomes:
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+ print("\n + Total [PATTERNS FOUND!]: [ "+str(total_patterns_all_genomes)+" ]")
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+ biggest_pattern_name_codon = None
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+ for c in codons:
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+ if c.split(":")[0] == str(biggest_pattern_name):
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+ biggest_pattern_name_codon = str(c.split(":")[1].replace("\n",""))
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+ print("\n - [MOST-PRESENT!]: [ "+str(biggest_pattern_size)+" ] time(s) -> [ "+str(biggest_pattern_name)+" ] "+str(biggest_pattern_name_codon)+"\n")
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+ if biggest_pattern_name_codon == None:
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+ print("\n - [MOST-PRESENT!]: [ "+str(biggest_pattern_size)+" ] time(s) -> [ "+str(biggest_pattern_name)+" ]\n")
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+ other_pattern_name_codon = None
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+ for k, v in most_present_patterns_by_len_list.items():
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+ for c in codons:
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+ if c.split(":")[0] == str(v[0]):
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+ other_pattern_name_codon = str(c.split(":")[1].replace("\n",""))
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+ print(" * [length = "+str(k)+"] : [ "+str(v[1])+" ] time(s) -> [ "+str(v[0])+" ] "+str(other_pattern_name_codon))
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+ if other_pattern_name_codon == None:
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+ print(" * [length = "+str(k)+"] : [ "+str(v[1])+" ] time(s) -> [ "+str(v[0])+" ]")
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+ other_pattern_name_codon = None
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+ smaller_pattern_name_codon = None
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+ for c in codons:
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+ if c.split(":")[0] == str(smaller_pattern_name):
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+ smaller_pattern_name_codon = str(c.split(":")[1].replace("\n",""))
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+ print("\n - [LESS-PRESENT!]: [ "+str(smaller_pattern_size)+" ] time(s) -> [ "+str(smaller_pattern_name)+" ] "+str(smaller_pattern_name_codon)+"\n")
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+ if smaller_pattern_name_codon == None:
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+ print("\n - [LESS-PRESENT!]: [ "+str(smaller_pattern_size)+" ] time(s) -> [ "+str(smaller_pattern_name)+" ]\n")
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+ other_pattern_name_codon = None
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+ for n, m in less_present_patterns_by_len_list.items():
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+ for c in codons:
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+ if c.split(":")[0] == str(m[0]):
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+ other_pattern_name_codon = str(c.split(":")[1].replace("\n",""))
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+ print(" * [length = "+str(n)+"] : [ "+str(m[1])+" ] time(s) -> [ "+str(m[0])+" ] "+str(other_pattern_name_codon))
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+ if other_pattern_name_codon == None:
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+ print(" * [length = "+str(n)+"] : [ "+str(m[1])+" ] time(s) -> [ "+str(m[0])+" ]")
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+ other_pattern_name_codon = None
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+ max_size_pattern_name = max(most_present_patterns_by_len_list, key=most_present_patterns_by_len_list.get)
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+ less_size_pattern_name = min(most_present_patterns_by_len_list, key=most_present_patterns_by_len_list.get)
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+ print("\n - [LARGEST] : [ "+str(max_size_pattern_name)+" ] bp linear RNA")
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+ print(" - [SHORTEST]: [ "+str(less_size_pattern_name)+" ] bp linear RNA\n")
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+ else:
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+ print("\n + Total [PATTERNS FOUND!]: [ 0 ]\n")
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+ try:
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+ f=open(universal_primer_list_path, 'r')
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+ UPL = f.readlines()
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+ f.close()
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+ if UPL:
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+ extract_potential_primer_pairs(UPL, total_genomes, codons)
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+ except:
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+ pass
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+ if codons:
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+ extract_potential_dna_codons(codons, total_genomes)
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+
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+def extract_potential_primer_pairs(UPL, total_genomes, codons):
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+ total_universal_primer_pairs = 0
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+ total_primer_pairs_found = 0
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+ primer_pairs_found_list = {}
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+ for pp in UPL:
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+ total_universal_primer_pairs = total_universal_primer_pairs + 1
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+ for k, v in genomes.items():
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+ pair_name = pp.split(":")[1].upper().replace("\n","")
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+ pair_sec = pp.split(":")[0]
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+ if str(pair_name) in str(v.upper()):
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+ pair_times = v.count(pair_name)
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+ total_primer_pairs_found += pair_times
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+ primer_pairs_found_list[pair_sec] = pair_name, total_primer_pairs_found
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+ print(" * Trying -[ "+str(total_universal_primer_pairs)+" ]- [UNIVERSAL PRIMER PAIRS!] against -[ "+str(total_genomes)+ " ]- [DNA SECUENCES]:")
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+ if total_primer_pairs_found:
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+ total_primer_pairs_found_list = 0
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+ for m, n in primer_pairs_found_list.items():
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+ total_primer_pairs_found_list = total_primer_pairs_found_list + n[1]
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+ print("\n + Total [UNIVERSAL PRIMER PAIRS FOUND!]: [ "+str(total_primer_pairs_found_list)+" ]\n")
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+ for m, n in primer_pairs_found_list.items():
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+ print(" * "+str(m)+" -> [ "+str(n[0])+" ] : [ "+str(n[1])+" ] time(s)")
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+ print ("")
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+ else:
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+ print("\n + Total [UNIVERSAL PRIMER PAIRS FOUND!]: [ 0 ]\n")
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+
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+def extract_potential_dna_codons(codons, total_genomes):
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+ total_codons = 0
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+ total_codons_found = 0
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+ codons_found_list = {}
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+ codons_found_list_by_codon = {}
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+ for c in codons:
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+ total_codons = total_codons + 1
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+ for k, v in genomes.items():
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+ codon_name = c.split(":")[0].upper().replace("\n","")
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+ if str(codon_name) in str(v.upper()):
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+ codons_times = v.count(codon_name)
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+ total_codons_found += codons_times
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+ codons_found_list[codons_times] = c.split(":")[0], str(c.split(":")[1]), k
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+ print(" * Trying -[ "+str(total_codons)+" ]- [PATTERN CODONS!] against -[ "+str(total_genomes)+ " ]- [DNA SECUENCES]:")
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+ if total_codons_found:
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+ for m, n in codons_found_list.items():
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+ codon_sec = str(n[0])
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+ codon_name = str(n[1].replace("\n",""))
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+ if not codon_sec in codons_found_list_by_codon.keys():
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+ codons_found_list_by_codon[codon_sec] = codon_name, m
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+ else:
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+ for r, s in codons_found_list_by_codon.items():
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+ if codon_sec == r:
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+ new_v = s[1] + m
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+ codons_found_list_by_codon[codon_sec] = codon_name, new_v
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+ codons_found_list_by_name = {}
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+ for g,z in codons_found_list_by_codon.items():
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+ if not z[0] in codons_found_list_by_name.keys():
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+ codons_found_list_by_name[z[0]]= z[1]
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+ else:
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+ for e, q in codons_found_list_by_name.items():
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+ if z[0] == e:
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+ new_s = q + z[1]
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+ codons_found_list_by_name[z[0]] = new_s
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+ total_codons_by_codon = 0
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+ for p, f in codons_found_list_by_name.items():
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+ total_codons_by_codon = total_codons_by_codon + f
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+ print("\n + Total [PATTERN CODONS FOUND!]: [ "+str(total_codons_by_codon)+" ]\n")
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+ for p, f in codons_found_list_by_name.items():
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+ print(" * "+str(p)+" : "+str(f)+" time(s)")
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+ print ("")
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+ else:
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+ print("\n + Total [PATTERN CODONS FOUND!]: [ 0 ]\n")
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def extract_patterns_most_found_in_all_genomes(memory_dict):
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present_patterns = []
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@@ -427,7 +543,6 @@ def extract_patterns_most_found_in_all_genomes(memory_dict):
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for i, v in largest_size_by_pattern.items():
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total_patterns_by_pattern = total_patterns_by_pattern + v[1]
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list_total_patterns_by_pattern[v[0]] = total_patterns_by_pattern
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- total_patterns_by_pattern = 0
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biggest_pattern_name = None
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biggest_pattern_size = 0
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smaller_pattern_name = None
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@@ -450,7 +565,7 @@ def extract_patterns_most_found_in_all_genomes(memory_dict):
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less_size_pattern_name = r
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if z > biggest_pattern_size:
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biggest_pattern_name = r
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- biggest_pattern_size = z
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+ biggest_pattern_size = biggest_pattern_size + z
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else:
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if z < smaller_pattern_size:
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smaller_pattern_name = r
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@@ -516,9 +631,9 @@ def extract_storage_sizes():
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total_files_size = '%s %s' % (total_s,total_size_name)
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print(" * Total [FILE SIZES]: "+str(total_files_size)+"\n")
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if total_dataset_size:
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- print(" + [DATASET]: "+str(total_dataset_size))
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+ print(" + [DATASET]: "+str(total_dataset_size)+"\n")
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if total_list_size:
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- print(" + [LIST]: "+str(total_list_size))
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+ print(" + [LIST]: "+str(total_list_size)+"\n")
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if total_brain_size:
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print(" + [BRAIN]: "+str(total_brain_size)+"\n")
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@@ -536,6 +651,9 @@ def extract_total_patterns_learned_from_local(memory):
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def list_genomes_on_database():
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print("[LIST] [REPORTING] [DNA SECUENCES] ... -> [STARTING!]\n")
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+ f=open(dna_codons_list_path, 'r')
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+ codons = f.readlines()
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+ f.close()
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print("-"*15 + "\n")
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f=open(genomes_list_path, 'w')
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for k, v in genomes.items():
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@@ -552,6 +670,12 @@ def list_genomes_on_database():
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if v.count("N") > 0:
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print (" + [N] *ANY* :", str(v.count("N")))
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f.write(str(" + [N] *ANY* : "+ str(v.count("N"))+"\n"))
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+ for c in codons:
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+ codon_sec = str(c.split(":")[0])
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+ codon_name = str(c.split(":")[1].replace("\n",""))
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+ codon_counter = str(v.count(str(c.split(":")[0])))
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+ print (" + ["+codon_sec+"] "+codon_name+" :", codon_counter)
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+ f.write(str(" + ["+codon_sec+"] "+codon_name+" : "+ codon_counter)+"\n")
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print ("")
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f.write("\n")
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print("-"*15 + "\n")
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