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        <dc:date>2010-01-24T13:51:27-05:00</dc:date>
        <dc:creator>julia</dc:creator>
        <title>part1</title>
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        <description>Part 1

Hands on code: Sequences and strings 1

As pointed in Beginning Perl for Bioinformatics, a large percentage of bioinformatics procedures deals with strings, especially DNA and amino acids sequence data. As is largely known DNA is composed of four different nucleotides: A, C, T and G and proteins can contain up to 20 amino acids. Each one of these elements have one letter of the alphabet assigned to them. In the DNA case some letters represent one or more nucleotides that can be present a…</description>
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        <dc:date>2009-05-22T11:36:18-05:00</dc:date>
        <dc:creator>nuin</dc:creator>
        <title>part16</title>
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        <description>1


Let's check some database topics in Python. I was asked to create a simple database to organize wet-lab stuff. No relationships needs, no relational tables required. Just a simple table with determined columns, and a nice GUI to go with it so people can edit, search and use.</description>
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        <dc:date>2009-05-22T11:29:23-05:00</dc:date>
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        <title>beginning_python_for_bioinformatics</title>
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        <description>The posts from Beginning Python for Bioinformatics are and will be included here, allowing for a better experience when reading the entries.



Beginning the begin


This website uses as a premise the book:

Beginning Perl for Bioinformatics by James Tisdal</description>
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        <description>1


We created a very elegant script in Python that efficiently counts words in FASTA sequences and then using a basic statistical method, calculates the significance of each word and output the overrepresented ones.

Our script used a little bit less than 50 lines, and if you include the imported fasta module, it won't top 100. But the number of lines is not important. The efficiency, clarity and speed are key here. At the same time, running a script from the command line is not something every…</description>
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