In Python: In this section, you will be reading in a file of apple genes and, based on these coding sequences, generate a codon usage bias table for this species.  Some things to keep in mind: This is the first time you'll be using a full dataset.  Expect your numbers to get big We're looking for the frequency of the occurrence of a codon relative to other codons of the same amino acid.  As such, you will have multiple counts to keep track of.  Think about how you want to keep track of these counts, and what combinations of dictionaries, lists, and tuples are best suited to this task. Plan this BEFORE you start. Just as important as it is to get these counts and generate a result, you must also consider how best to present these results. Your code should generate a human-readable file that shows your frequencies in a way that is verbose and makes sense.  Your success in presenting the results will be considered just as important as how you arrived to them. >MD10G1276500 pacid=40089867 polypeptide=MD10G1276500 locus=MD10G1276500 ID=MD10G1276500.v1.1.491 annot-version=v1.1 ATGATGCAGTCCGTGGCTCCTGTGTGCAATGTCTGCGGCGAGCAGGTGGGGCTTGGTGCCAATGGGGAGGTTTTCGTGGC ATGCCACGAGTGTAATTTCCCCATTTGCAAGGCTTGTTTCGATGAAGATGTCAAGGCTGGGCGTAAAGTTTGCTTGCAGT GTGGTATTCCCTATGACGATAACCCGTTGGCGGAGTATGAAACAAAGGTGTCAGGCACTCGATCCACAATGGAAGCTCAC CTGAATAATACACAGGATACAGGAATTCATGCTAGGCATATCAGCAGTGTGTCTACGTTGGATAGTGAATTAAACGATGA ATCTGGCAATCCGATTTGGAAGAATAGAGTGGAAAGTTGGAAGGATAAGAAGGATAAGAAGGATAAAAAGATCAAGAAGA AAAAGGATACACCTAATGGGGAAAAAGAGGCTCAAATTCCACCTGAGAAGCAGATGACAGAGGAATATTCATCAGAGGCT GCGGAACCACTTTCAACTCTCGTCCCACTTCCATCTAACAGAATCACACCATACAGAACTGTTATAATTATGCGATTGAT CATTCTCGCCCTTTTCTTCCATTATCGAGTAACAAATCCTGTTGATAGTGCTTACGGTCTATGGTTCACTTCGATCATAT GTGAGATCTGGTTTGCTTTTTCTTGGGTGTTGGATCAGTTTCCTAAGTGGTCTCCAGTTAATCGGACTACATTTACTGAC AGGTTATCTGCCAGGTTTGAAAGAGAGGGTGAACTCTCCGAGCTTGCTGCTGTGGATTTCTTCGTAAGTACAGTTGATCC GTTGAAAGAACCGCCCTTGATTACTGCCAATACCGTGCTTTCTATCCTTGCTGTAGACTACCCTGTGGACAAAGTTTCCT GCTATGTGTCTGATGATGGTGCTGCCATGCTTACATTTGAATCCCTTGCCGAAACATCTGAATTTGCAACAAAGTGGGTT CCTTTCTGCAAGAAATTTTCAATTGAACCACGTGCACCTGAGTTTTACTTCTCACAAAAGATTGACTACTTGAAGGATAA AGTGCAACCATCTTTTGTGAAGGAGCGCAGAGCGATGAAAAGAGATTATGAAGAGTTCAAAGTGCGAATGAATGCTTTAG TAGCAAAGGCTCAAAAAACACCAGAAGAAGGATGGACTATGCAAGATGGAACTCCATGGCCAGGAAATAACTCGCGTGAC CATCCTGGGATGATCCAGGTGTTCCTTGGACATAGCGGTGCCTATGACATCGAGGGAAATGAACTTCCTCGATTGGTTTA TGTCTCGAGAGAGAAGAGACCCGGCTACCCACATCACAAGAAAGCTGGTGCTGAAAATGCTTTGGTAAGGGTGTCTGCAG TTCTCACAAATGCCCCATACATCCTCAATCTTGACTGTGATCACTACGTTAACAACAGCCAGGCAATTCGTGAGGCAATG TGTTTCTTGATGGACCCTCAAGTCGGTCGAGAAGTATGCTATGTGCAGTTTCCTCAGAGGTTTGATGGTATTGATCGCAG TGATCGATATGCTAATCGCAACACAGTTTTCTTTGATGTTAACATGAAAGGACTGGATGGCATTCAAGGTCCAGTATATG TGGGGACAGGATGTTGTTTCAACAGGCAAGCACTTTACGGCTACGGTCCTCCTTCTATGCCCGCCTTATCCAAGGCTGCT TCCTCATCCTCCTGCTCTTGTTGCTGTCCCTCTAAGAAGCCCTCTAAAGATGTGTCAGAGGCTTATCGAGATGCAAAACA GGAGGAGCTTGATGCTGCCATTTTTAACCTCCGTGATATTGAGAATTATGATGAGCTTGAGAGGTCAATGCTGATCTCGC AGACAAGCTTTGAGAAAACTTTTGGATTATCGTCTGTATTCATCGAATCTACGCTAATGGAGAACGGAGGAGTGGCCGAA TCTTCCAACCCTTCAACATTGATCAAGGAGGCGATTCACGTCATTAGCTGTGGTTATGAAGAGAAGACCGCGTGGGGAAA AGAGATTGGTTGGATATATGGATCAATCACTGAGGATATCTTAACCGGTTTCAAGATGCATTGCCGTGGATGGAGGTCAA TTTACTGCATGCCCTTGAGACCTGCATTCAAAGGGTCAGCTCCCATTAACCTTTCTGATCGACTGCACCAAGTTCTTCGG TGGGCACTGGGATCGGTGGAAATTTTCCTCAGTAGACATTGTCCTCTCTGGTACGGGTTTGCAGGAGGCCGCCTCAAATT GCTTCAGAGAATGGCATATATCAACACTATTGTTTACCCCTTCACATCCCTCCCTCTCGTCGCTTACTGCACACTCCCTG CAATATGCCTTCTCACAGGAAAATTCATCATCCCAACACTTACAAACCTGGCAAGTGCCCTGTTTCTTGGCCTCTTCATC TCCATCATTGCTACAAGTGTGCTTGAGTTGAGGTGGAGTGGAGTCCGCATTGAGGACTTATGGCGTAACGAGCAGTTCTG GGTGATCGGAGGTGTTTCAGCCCATCTCTTTGCCGTCTTCCAAGGTTTCTTAAAGATGTTGGCCGGAATTGACACCAACT TCACCGTCACAACCAAATCAGCCGAAGACACAGAATTCGGAGAGCTCTATCTGATCAAATGGACCACACTTTTGATTCCC CCAACTACACTCCTCATCGTCAACATGGTTGGTGTTGTTGCAGGATTTTCGGACGCCCTCAACAAGGGATACGAAGCTTG GGGGCCACTTTTCGGGAAGGTTTTCTTTGCCTTCTGGGTGATTCTTCATCTATATCCCTTCCTCAAAGGTCTCATGGGAC GCCAAAACCGGACTCCAACCATCGTTGTTTTGTGGTCAGTGCTCTTGGCCTCTGTCTTCTCCCTTGTTTGGGTGAAGATA AATCCATTTGTGAGCAAAGTGGACAGCTCAACGCTTGCTCAAAGCTGCATTTCCATAGACTGCTGA I have included one example from the file but there are more that are similar!

Database System Concepts
7th Edition
ISBN:9780078022159
Author:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Publisher:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Chapter1: Introduction
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In Python:

In this section, you will be reading in a file of apple genes and, based on these coding sequences, generate a codon usage bias table for this species. 

Some things to keep in mind:

  • This is the first time you'll be using a full dataset.  Expect your numbers to get big
  • We're looking for the frequency of the occurrence of a codon relative to other codons of the same amino acid.  As such, you will have multiple counts to keep track of.  Think about how you want to keep track of these counts, and what combinations of dictionaries, lists, and tuples are best suited to this task. Plan this BEFORE you start.
  • Just as important as it is to get these counts and generate a result, you must also consider how best to present these results. Your code should generate a human-readable file that shows your frequencies in a way that is verbose and makes sense.  Your success in presenting the results will be considered just as important as how you arrived to them.

>MD10G1276500 pacid=40089867 polypeptide=MD10G1276500 locus=MD10G1276500 ID=MD10G1276500.v1.1.491 annot-version=v1.1
ATGATGCAGTCCGTGGCTCCTGTGTGCAATGTCTGCGGCGAGCAGGTGGGGCTTGGTGCCAATGGGGAGGTTTTCGTGGC
ATGCCACGAGTGTAATTTCCCCATTTGCAAGGCTTGTTTCGATGAAGATGTCAAGGCTGGGCGTAAAGTTTGCTTGCAGT
GTGGTATTCCCTATGACGATAACCCGTTGGCGGAGTATGAAACAAAGGTGTCAGGCACTCGATCCACAATGGAAGCTCAC
CTGAATAATACACAGGATACAGGAATTCATGCTAGGCATATCAGCAGTGTGTCTACGTTGGATAGTGAATTAAACGATGA
ATCTGGCAATCCGATTTGGAAGAATAGAGTGGAAAGTTGGAAGGATAAGAAGGATAAGAAGGATAAAAAGATCAAGAAGA
AAAAGGATACACCTAATGGGGAAAAAGAGGCTCAAATTCCACCTGAGAAGCAGATGACAGAGGAATATTCATCAGAGGCT
GCGGAACCACTTTCAACTCTCGTCCCACTTCCATCTAACAGAATCACACCATACAGAACTGTTATAATTATGCGATTGAT
CATTCTCGCCCTTTTCTTCCATTATCGAGTAACAAATCCTGTTGATAGTGCTTACGGTCTATGGTTCACTTCGATCATAT
GTGAGATCTGGTTTGCTTTTTCTTGGGTGTTGGATCAGTTTCCTAAGTGGTCTCCAGTTAATCGGACTACATTTACTGAC
AGGTTATCTGCCAGGTTTGAAAGAGAGGGTGAACTCTCCGAGCTTGCTGCTGTGGATTTCTTCGTAAGTACAGTTGATCC
GTTGAAAGAACCGCCCTTGATTACTGCCAATACCGTGCTTTCTATCCTTGCTGTAGACTACCCTGTGGACAAAGTTTCCT
GCTATGTGTCTGATGATGGTGCTGCCATGCTTACATTTGAATCCCTTGCCGAAACATCTGAATTTGCAACAAAGTGGGTT
CCTTTCTGCAAGAAATTTTCAATTGAACCACGTGCACCTGAGTTTTACTTCTCACAAAAGATTGACTACTTGAAGGATAA
AGTGCAACCATCTTTTGTGAAGGAGCGCAGAGCGATGAAAAGAGATTATGAAGAGTTCAAAGTGCGAATGAATGCTTTAG
TAGCAAAGGCTCAAAAAACACCAGAAGAAGGATGGACTATGCAAGATGGAACTCCATGGCCAGGAAATAACTCGCGTGAC
CATCCTGGGATGATCCAGGTGTTCCTTGGACATAGCGGTGCCTATGACATCGAGGGAAATGAACTTCCTCGATTGGTTTA
TGTCTCGAGAGAGAAGAGACCCGGCTACCCACATCACAAGAAAGCTGGTGCTGAAAATGCTTTGGTAAGGGTGTCTGCAG
TTCTCACAAATGCCCCATACATCCTCAATCTTGACTGTGATCACTACGTTAACAACAGCCAGGCAATTCGTGAGGCAATG
TGTTTCTTGATGGACCCTCAAGTCGGTCGAGAAGTATGCTATGTGCAGTTTCCTCAGAGGTTTGATGGTATTGATCGCAG
TGATCGATATGCTAATCGCAACACAGTTTTCTTTGATGTTAACATGAAAGGACTGGATGGCATTCAAGGTCCAGTATATG
TGGGGACAGGATGTTGTTTCAACAGGCAAGCACTTTACGGCTACGGTCCTCCTTCTATGCCCGCCTTATCCAAGGCTGCT
TCCTCATCCTCCTGCTCTTGTTGCTGTCCCTCTAAGAAGCCCTCTAAAGATGTGTCAGAGGCTTATCGAGATGCAAAACA
GGAGGAGCTTGATGCTGCCATTTTTAACCTCCGTGATATTGAGAATTATGATGAGCTTGAGAGGTCAATGCTGATCTCGC
AGACAAGCTTTGAGAAAACTTTTGGATTATCGTCTGTATTCATCGAATCTACGCTAATGGAGAACGGAGGAGTGGCCGAA
TCTTCCAACCCTTCAACATTGATCAAGGAGGCGATTCACGTCATTAGCTGTGGTTATGAAGAGAAGACCGCGTGGGGAAA
AGAGATTGGTTGGATATATGGATCAATCACTGAGGATATCTTAACCGGTTTCAAGATGCATTGCCGTGGATGGAGGTCAA
TTTACTGCATGCCCTTGAGACCTGCATTCAAAGGGTCAGCTCCCATTAACCTTTCTGATCGACTGCACCAAGTTCTTCGG
TGGGCACTGGGATCGGTGGAAATTTTCCTCAGTAGACATTGTCCTCTCTGGTACGGGTTTGCAGGAGGCCGCCTCAAATT
GCTTCAGAGAATGGCATATATCAACACTATTGTTTACCCCTTCACATCCCTCCCTCTCGTCGCTTACTGCACACTCCCTG
CAATATGCCTTCTCACAGGAAAATTCATCATCCCAACACTTACAAACCTGGCAAGTGCCCTGTTTCTTGGCCTCTTCATC
TCCATCATTGCTACAAGTGTGCTTGAGTTGAGGTGGAGTGGAGTCCGCATTGAGGACTTATGGCGTAACGAGCAGTTCTG
GGTGATCGGAGGTGTTTCAGCCCATCTCTTTGCCGTCTTCCAAGGTTTCTTAAAGATGTTGGCCGGAATTGACACCAACT
TCACCGTCACAACCAAATCAGCCGAAGACACAGAATTCGGAGAGCTCTATCTGATCAAATGGACCACACTTTTGATTCCC
CCAACTACACTCCTCATCGTCAACATGGTTGGTGTTGTTGCAGGATTTTCGGACGCCCTCAACAAGGGATACGAAGCTTG
GGGGCCACTTTTCGGGAAGGTTTTCTTTGCCTTCTGGGTGATTCTTCATCTATATCCCTTCCTCAAAGGTCTCATGGGAC
GCCAAAACCGGACTCCAACCATCGTTGTTTTGTGGTCAGTGCTCTTGGCCTCTGTCTTCTCCCTTGTTTGGGTGAAGATA
AATCCATTTGTGAGCAAAGTGGACAGCTCAACGCTTGCTCAAAGCTGCATTTCCATAGACTGCTGA

I have included one example from the file but there are more that are similar!

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