Format the document in a consistent manner
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Notebook.org
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Notebook.org
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* Biology Meets Programming: Bioinformatics for Beginners
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** Week 1
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*** DNA replication
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**** Origin of replication (ori)
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@ -95,7 +97,6 @@ def PatternMatching(Pattern, Genome):
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We find out that the /9-mers/ with the highest frequency appear in cluster.
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There is strong statistical evidence that our subsequences are /DnaA boxes/.
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**** Computational approaches to find ori in any bacteria
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Now that we're pretty confident about the /DnaA boxes/ sequences that we found,
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@ -119,6 +120,7 @@ We have to try another computational approach,
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find clusters of /k-mers/ repeated in a small interval.
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** Week 2
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*** DNA replication (II)
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**** Replication process
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@ -257,7 +259,6 @@ def SkewArray(Genome):
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return Skew
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#+END_SRC
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**** Finding /DnaA boxes/
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When we look for /DnaA boxes/ in the minimal skew region,
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@ -383,6 +384,7 @@ def Count(Motifs):
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***** Exercise: Form the most frequent sequence of nucleotides
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Finally, we can form a Consensus string, to get a candidate regulatory motif:
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#+BEGIN_SRC python
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def Consensus(Motifs):
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consensus = ""
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@ -493,8 +495,7 @@ def Pr(Text, Profile):
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return probability
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#+END_SRC
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Now we're finally ready to assemble all the pieces and implement a Greedy Motif
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Search Algorithm:
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Now we're finally ready to assemble all the pieces and implement a Greedy Motif Search Algorithm:
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#+BEGIN_SRC python
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def GreedyMotifSearch(Dna, k, t):
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@ -583,9 +584,7 @@ def Pr(Text, Profile):
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***** Motifs in tuberculosis
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Tuberculosis is an infectious disease, caused by a bacteria called /Mycobacterium
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tuberculosis/. The bacteria can stay latent in the host for decades, in hypoxic
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environments.
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Tuberculosis is an infectious disease, caused by a bacteria called /Mycobacterium tuberculosis/. The bacteria can stay latent in the host for decades, in hypoxic environments.
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Our Greedy Algorithm can help us identify a motif that might be involved
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in the process.
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