Парсинг Pubmed на противораковые натуральные вещества

В этой статье будет расчет натуральных веществ распарсенных с базы биомедицинских публикаций Pubmed. Для научных целей также полезно высчитывать комбинации молекул, но для этого требуется транскриптом, который можно получить добавляя лекарство на клетку HeLa.

>>> for u in range(1,len(cancelmol)): ...  print(cancelmol[s9[-u]],u) ...  Curcumin 1 Metformin 2 Resveratrol 3 Quercetin 4 Sulforaphane 5 Melatonin 6 Berberine 7 Celecoxib 8 Triptolide 9 Emodin 10 Simvastatin 11 Trametinib 12 Luteolin 13 Baicalein 14 Plumbagin 15 Celastrol 16 Capecitabine 17 Cryptotanshinone 18 Tocotrienol 19 Astragaloside 20 Fisetin 21 Licochalcone 22 Pterostilbene 23 Nobiletin 24 Kaempferol 25 Chrysin 26 Capsaicin  27 Withaferin A 28 Icariin 29 Epigallocatechin-3-gallate 30 Astaxanthin 31 Xanthohumol 32 Rutin 33 Vitamin E 34 Itraconazole 35 Cannabidiol 36 Naringenin 37 Trichostatin A 38 ursolic acid 39 Myricetin 40 Disulfiram 41 Arctigenin 42 Lutein 43 Phenformin 44 Piceatannol 45 Mifepristone 46 Gallic Acid 47 Minocycline 48 Indirubin 49 Deguelin 50 Polydatin 51 Chlorogenic Acid 52 Theophylline 53 Cardamonin 54 Hesperidin 55 Fucoxanthin 56 Indomethacin 57 Thioridazine 58 Valproic acid 59 Urolithin A 60 Diosgenin  61 Calycosin 62 Naringin 63 Palmatine 64 Isorhamnetin 65 Ivermectin 66 Amlexanox 67 Butein 68 Rosmarinic acid 69 Prunetin 70 Lonidamine 71 Ginkgo biloba extract 72 Doxycycline  73 Juglone 74 Verapamil 75 Spermidine 76 Omega-6 77 Carnosol 78 Menadione 79 Trehalose 80 Sodium salicylate 81 Ellagic acid 82 Auraptene 83 Selenomethionine 84 Dihydroxyflavone 85 6-shogaol 86 Pictilisib 87 Carnosic acid 88 Taxifolin 89 Vitexin 90 Naproxen 91 Geldanamycin 92 Lonicera japonica 93 Nordihydroguaiaretic acid 94 Sesamin 95 Thiostrepton 96 Carnosine 97 Carvedilol 98 Rotenone 99 Captopril 100 Acetazolamide 101 Chlorpromazine 102 Cinnamon Extract 103 Ascorbic acid 104 Scutellarein 105 Caffeic acid 106 Lithium Chloride 107 Anisomycin 108 Carbidopa 109 Echinacoside 110 Canagliflozin 111 Gedunin 112 Chicoric acid 113 SkQ1 114 Enoxacin 115 Green tea extract 116 Norcantharidin 117 Protocatechuic acid 118 Diethyldithiocarbamate 119 Sesamolin 120 Tannic acid 121 Vinpocetine 122 Staurosporine 123 4-phenylbutyrate 124 Reserpine 125 Gramicidin 126 Procaine 127 Glaucarubinone 128 Buthionine Sulfoximine 129 Phosphatidylcholine 130 Buformin 131 Secoisolariciresinol Diglucoside 132 Tamarixetin 133 2-deoxy-D-glucose 134 Limonin 135 Geranylgeranylacetone 136 Astemizole 137 Sorbitol 138 Pyrroloquinoline quinone 139 Imatinib mesylate 140 Alpha-lipoic acid 141 Salicylic acid 142 Sulindac Sulfide 143 Naphthazarin 144 Kinetin 145 Kynurenic acid 146 Dehydroabietic acid 147 Phloridzin 148 Promethazine 149 Wortmannin 150 Cadmium chloride 151 Ganoderma lucidum extract 152 Sodium Nitroprusside 153 Scriptaid 154 Rhodiola rosea extract 155 Ciclopirox olamine 156 Antimycin A 157 Benzethonium 158 Myriocin 159 Coix seed oil 160 Propyl gallate 161 Tectochrysin 162 D-glucosamine 163 Tiliroside 164 Vortioxetin 165 Sodium citrate 166 Mercuric chloride 167 Perphenazine  168 Pinitol 169 Cyproterone acetate 170

from Bio import Entrez from Bio import Medline import re MAX_COUNT = 1000 Entrez.email = 'a-nai@yandex.ru'   import time import numpy as np import pickle  drugs2= pickle.load(open("drugs2.pkl","rb")); cancelmol = pickle.load(open("cancelmol.pkl","rb"));  molecules=['Apigenin', 'Chaetocin', 'Chrysin', 'Curcumin', 'Epigallocatechin gallate (EGCG)', 'Luteolin', 'Myricetin', 'Quercetin', 'Resveratrol', 'Wogonin', 'Brusatol', 'Piperlongumine', 'Trigonelline', 'Pentyl isothiocyanate (PEITC)', 'Pleurotin', 'Plumbagin', 'EM23', 'Parthenolid', 'Sulforaphane', 'Melatonin']  import csv drugA=[]; with open('/Users/andrejeremcuk/Downloads/DrugAge Browse (1).csv', newline='') as csvfile:      spamreader = csv.reader(csvfile, delimiter=',', quotechar='|')      for row in spamreader:        print(row);drugA.append(row)  #//print(', '.join(row))  len(drugA) drugA[1:5] drugAb=[] for i in range(1,len(drugA)):   drugAb.append(str(drugA[i][0].split(',')[0]).replace('"', ''))     s=[]; t=drugAb for i in t:        if i not in s:           s.append(i)   drugA=s; drugAb=s

def forfer(l,drug7):      ii0='no';      t1=l.find(drug7);      if t1==-1: return 'no';      t2=l.find('apoptosis');      t4=l.find('Inhibition of cancer');      t5=l.find('cancer');      #t6=re.search('autophagy',fer[u],re.IGNORECASE);      t6=l.find('autophagy');      if t6!=None: print(t6,u);      t7=l.find('Autophagy');      t8=l.find('anticancer');      t9=l.find('antiproliferative');      t10=l.find('apoptotic');      t11=l.find('Inhibits Cancer Metastasis');      t12=l.find('Angiogenesis');      t13=l.find('cytotoxicity');      t14=l.find('anti-tumor');      t15=l.find('anticancer therapy');      t16=l.find('antitumor');      t17=l.find('inhibits');      t5=l.find('cancer');      t18=l.find('cancer growth');      t19=l.find('cancer therapy');      t20=l.find('antiangiogenic');      t21=l.find('anti-cancer');      if (t21!=-1)or(t20!=-1)or(t19!=-1)or(t18!=-1)or(t17!=-1)or(t16!=-1)or(t15!=-1)or(t14!=-1)or(t13!=-1)or(t12!=-1)or(t11!=-1)or(t10!=-1)or(t9!=-1)or(t8!=-1)or(t7!=-1)or(t6!=-1)or(t4!=-1)or(t2!=-1): return 'yes';      else: return 'no';  def ferfor(l,drug7):      t1=l.find(drug7);      t2=l.find('accelerate');      t4=l.find('promotes');      t6=l.find('Stimulates');      t7=l.find('Metastasis');      t5=l.find('cancer');      t8=l.find('promote');      t9=l.find('tumorigenesis');      t10=l.find('metastasis');      t11=l.find('stimulates');      if ((t11!=-1)or(t10!=-1)or(t9!=-1)or(t8!=-1)or(t7!=-1)or(t6!=-1)or(t4!=-1)or(t2!=-1))and(t1!=-1): return 'yes';      else: return 'no';                        cancers=['Liver Cancer', 'Thyroid Cancer', 'Pancreatic Cancer', 'Leukemia', 'Kidney Cancer', 'Non-Hodgkins Lymphoma', 'Bladder Cancer', 'Melanoma', 'Colonorectal Cancers', 'Prostate Cancer', 'Lung Cancer', 'Breast Cancer', 'squamous cell carcinoma', 'gastric cancer'];      

for u in range(len(drugA)):#len(drugA)  MAX_COUNT = 400;  TERM=drugA[u] +' cancer';print(drugA[u],u);ii7.append(('it',drugA[u],u));ii6.append(('it',drugA[u],u))  try: h=Entrez.esearch(db='pubmed', retmax=MAX_COUNT, term=TERM)  except: time.sleep(5);print('error',u);h=Entrez.esearch(db='pubmed', retmax=MAX_COUNT, term=TERM)  result = Entrez.read(h)  ids = result['IdList']  h = Entrez.efetch(db='pubmed', id=ids, rettype='medline', retmode='text')  ret = Medline.parse(h)  fer=[];  for re in ret:   try: tr=re['TI'];   except: tr='0';   fer.append(tr);  for m in range(len(fer)):   i=drugA[u].find(' ');   if i!=-1: i7=forfer(fer[m],drugA[u][:i]);   s=drugA[u];   i8=forfer(fer[m],s);   s=s[0].lower()+s[1:];   i9=forfer(fer[m],s);   i6=forfer(fer[m],s);   if i6=='yes': ii6.append((fer[m],drugA[u]));   if (i9=='yes')or(i8=='yes')or(i7=='yes'): ii7.append((fer[m],drugA[u]));              iii7=[];  for u in range(len(s)):#len(drugA)  iii7.append(('it',s[u],u));  for h in range(len(cancers)):#len(drugA)   MAX_COUNT = 400;   TERM=s[u] +' '+cancers[h];print(s[u],u);#iii7.append(('it',s[u],u));   try: hi=Entrez.esearch(db='pubmed', retmax=MAX_COUNT, term=TERM)   except: time.sleep(5);print('error',u);hi=Entrez.esearch(db='pubmed', retmax=MAX_COUNT, term=TERM)   result = Entrez.read(hi)   ids = result['IdList']   hi = Entrez.efetch(db='pubmed', id=ids, rettype='medline', retmode='text')   ret = Medline.parse(hi)   fer=[];   for re1 in ret:    try: tr=re1['TI'];    except: tr='0';    fer.append(tr);   for m in range(len(fer)):    if (re.search(cancers[h],fer[m],re.IGNORECASE))and(re.search(s[u],fer[m],re.IGNORECASE)): iii7.append((fer[m],s[u],cancers[h])); 

i8cm = pickle.load(open("i8cm.pkl","rb"));  cancelmol = pickle.load(open("cancelmol.pkl","rb"));  i7cm = pickle.load(open("i7cm.pkl","rb"));  ma00pp = pickle.load(open("ma00pp.pkl","rb")); 

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