{"id":1051,"date":"2022-05-03T18:16:50","date_gmt":"2022-05-03T18:16:50","guid":{"rendered":"https:\/\/bioeconomyinnovation.com\/index.php\/numero-maximo-de-cadenas\/"},"modified":"2022-05-03T18:19:07","modified_gmt":"2022-05-03T18:19:07","slug":"numero-maximo-de-cadenas","status":"publish","type":"page","link":"https:\/\/bioeconomyinnovation.com\/index.php\/numero-maximo-de-cadenas\/","title":{"rendered":"N\u00famero m\u00e1ximo de cadenas"},"content":{"rendered":"
\n
\n
\n

Python tiene creada una funci\u00f3n llamadavalues()<\/strong> que nos da los valores de un diccionario y de igual manera hay otra que se llama max()<\/strong> La cual es usada para encontror el n\u00famero m\u00e1ximo en una lista. Con estas 2 usaremos para encontrar el el m\u00e1ximo patr\u00f3n de bases nitrogenadas repetidas en un texto.<\/p>\n

se usar\u00eda de la siguiente manera, mezclando ambas funciones:<\/p>\n

m = max(freq.values)<\/strong><\/p>\n<\/div>\n<\/div>\n<\/div>\n

\n
\n
<\/div>\n
\n
    \n
  • Para poder resolver esto debemos crear una nueva funci\u00f3n, en este caso se le puso FrequentWords en t\u00e9rminos de texto y del K mer (k).<\/li>\n
  • Creamos una lista llamda words vac\u00eda, en la que almacenaremos el patr\u00f3n o patrones que m\u00e1s se repiten.\n
      \n
    • A la funci\u00f3n creada anteriormente llamada Frecuencymap, la guardamos en una variable, en este caso le pusimos freq.<\/li>\n
    • Usaremos la mezcla de las funciones values y max, que es m = max(freq.values()). El freq.values, nos da una lista de los valores de la variable freq.<\/li>\n
    • Realizamos un for que recorrer\u00e1 cada valor de la variable freq, cada varlo recorrido ser\u00e1 guardado en en variable key<\/li>\n
    • Con la condicion if compraremos cada valor del key con la funci\u00f3n m\u00e1xima “m”, para ver si es el maximo.<\/li>\n
    • Si es el m\u00e1ximo se agregar\u00e1 a la lista words.<\/li>\n<\/ul>\n

      Usaremos el m\u00edsmo texto que en el ejercicio anterior para poder verificar nuestro resultado<\/li>\n<\/ul>\n<\/div>\n<\/div>\n<\/div>\n

      \n
      \n
      <\/div>\n
      \n
      In\u00a0[12]:<\/div>\n
      \n
      \n
      \n
      Text<\/span> =<\/span> 'ATCAATGATCAACGTAAGCTTCTAAGCATGATCAAGGTGCTCACACAGTTTATCCACAACCTGAGTGGATGACATCAAGATAGGTCGTTGTATCTCCTTCCTCTCGTACTCTCATGACCACGGAAAGATGATCAAGAGAGGATGATTTCTTGGCCATATCGCAATGAATACTTGTGACTTGTGCTTCCAATTGACATCTTCAGCGCCATATTGCGCTGGCCAAGGTGACGGAGCGGGATTACGAAAGCATGATCATGGCTGTTGTTCTGTTTATCTTGTTTTGACTGAGACTTGTTAGGATAGACGGTTTTTCATCACTGACTAGCCAAAGCCTTACTCTGCCTGACATCGACCGTAAATTGATAATGAATTTACATGCTTCCGCGACGATTTACCTCTTGATCATCGATCCGATTGAAGATCTTCAATTGTTAATTCTCTTGCCTCGACTCATAGCCATGATGAGCTCTTGATCATGTTTCCTTAACCCTCTATTTTTTACGGAAGAATGATCAAGCTGCTGCTCTTGATCATCGTTTC'<\/span>\nk<\/span> =<\/span> 3<\/span>\n\ndef<\/span> FrequencyMap<\/span>(<\/span>Text<\/span>,<\/span> k<\/span>):<\/span>\n    freq<\/span> =<\/span> {}<\/span>\n    n<\/span> =<\/span> len<\/span>(<\/span>Text<\/span>)<\/span>\n    for<\/span> i<\/span> in<\/span> range<\/span>(<\/span>n<\/span>-<\/span>k<\/span>+<\/span>1<\/span>):<\/span>\n        Pattern<\/span> =<\/span> Text<\/span>[<\/span>i<\/span>:<\/span>i<\/span>+<\/span>k<\/span>]<\/span>\n        freq<\/span>[<\/span>Pattern<\/span>]<\/span> =<\/span> 0<\/span>\n        for<\/span> x<\/span> in<\/span> range<\/span>(<\/span>n<\/span>-<\/span>k<\/span>+<\/span>1<\/span>):<\/span>\n            if<\/span> Pattern<\/span> ==<\/span> Text<\/span>[<\/span>x<\/span>:<\/span>x<\/span>+<\/span>k<\/span>]:<\/span>\n                freq<\/span>[<\/span>Pattern<\/span>]<\/span> +=<\/span>1<\/span>     \n    return<\/span> freq<\/span>\n\n\ndef<\/span> FrequentWords<\/span>(<\/span>Text<\/span>,<\/span> k<\/span>):<\/span>\n    words<\/span> =<\/span> []<\/span>\n    freq<\/span> =<\/span> FrequencyMap<\/span>(<\/span>Text<\/span>,<\/span> k<\/span>)<\/span>\n    m<\/span> =<\/span> max<\/span>(<\/span>freq<\/span>.<\/span>values<\/span>())<\/span>\n    for<\/span> key<\/span> in<\/span> freq<\/span>:<\/span>\n        if<\/span> m<\/span> ==<\/span> freq<\/span>[<\/span>key<\/span>]:<\/span>\n                words<\/span>.<\/span>append<\/span>(<\/span>key<\/span>)<\/span>\n    return<\/span> words<\/span>\n\nprint<\/span>(<\/span>FrequentWords<\/span>(<\/span>Text<\/span>,<\/span> k<\/span>))<\/span>\n<\/pre>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n
      \n
      <\/div>\n
      \n
      \n
      \n
      \n
      ['TGA']\n<\/pre>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n
      \n
      \n
      <\/div>\n
      \n
      Si comparamos con los resultados de los patrones en el frecuencymap, podemos ver TGA, est\u00e1 25 veces, entonces estamos en lo correcto.<\/p>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n","protected":false},"excerpt":{"rendered":"
      Python tiene creada una funci\u00f3n llamadavalues() que nos da los valores de un diccionario y…<\/p>\n","protected":false},"author":2,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"_links":{"self":[{"href":"https:\/\/bioeconomyinnovation.com\/index.php\/wp-json\/wp\/v2\/pages\/1051"}],"collection":[{"href":"https:\/\/bioeconomyinnovation.com\/index.php\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/bioeconomyinnovation.com\/index.php\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/bioeconomyinnovation.com\/index.php\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/bioeconomyinnovation.com\/index.php\/wp-json\/wp\/v2\/comments?post=1051"}],"version-history":[{"count":2,"href":"https:\/\/bioeconomyinnovation.com\/index.php\/wp-json\/wp\/v2\/pages\/1051\/revisions"}],"predecessor-version":[{"id":1066,"href":"https:\/\/bioeconomyinnovation.com\/index.php\/wp-json\/wp\/v2\/pages\/1051\/revisions\/1066"}],"wp:attachment":[{"href":"https:\/\/bioeconomyinnovation.com\/index.php\/wp-json\/wp\/v2\/media?parent=1051"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}