lect 03 content sensor and Markov chain

lect 03 content sensor and Markov chain - Bioc1808Sequence...

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Bioc 1808 Sequence  Bioinformatics Content Sensor and Markov  chain Instructor Dr. Junwen Wang
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Content sensor A feature is any DNA subsequence of biological significance . For practical reasons, we recognize two broad classes of features: signals short, fixed-length features such as regulatory elements, start codons, stop codons, or splice sites content regions variable-length features such as exons or introns We thus distinguish between two broad classes of feature sensors : signal sensors these typically scan a DNA sequence, using a sliding-window approach, to identify specific locations in the DNA where a signal is likely to reside content sensors these are typically used to assign a score to the region lying between two signals; e.g., a putative exon lying between a putative start codon and a putative donor splice site
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After the class, you are  expected to Generate random sequences based on 0  order, 1 st  or higher order Markov chain  (MC) Build a Markov chain Score and classify a sequence by MC Evaluate the performance of the classifier
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Exercise 1. 0 th  order Markov  chain Assume whole human genome has base  composition {A=0.3, C=0.2, G=0.2, T=0.3},  please generate a 10-nt sequence  according to the base composition rule.
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Exercise 1. 0 th
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This note was uploaded on 07/29/2010 for the course BIOC BIOC2808 taught by Professor Dr.jjwang during the Fall '09 term at HKU.

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lect 03 content sensor and Markov chain - Bioc1808Sequence...

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