assignment2

Assignment2 - program to generate 50 sequences each with 100nt in length based on the rule(20pts 3 Please write a program to model Markov chain The

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BIOC2808 Sequence Bioinformatics Assignment 2: Content sensor, Markov chain and sequence classification It is common practice in the bioinformatics area to generate random sequences for simulation. It is also important to know how to score a sequence with higher order Markov chain, and classify the sequence based on the scores. In this assignment, you are required to demonstrate your understanding of these techniques by coding. The whole assignment will have full 100pts. It has four parts, described below: 1. Given genome base composition of {A=0.3, C=0.2, G=0.2, T=0.3}, please write a program to generate 50 sequences, each with 100nt in length based on the rule (20pts). 2. Given the 1 st order dependencies matrix listed in lect 3, slide 11, please write a
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Unformatted text preview: program to generate 50 sequences, each with 100nt in length based on the rule (20pts). 3. Please write a program to model Markov chain. The program will construct model from each of the above datasets based on 5 th order Markov chain. The program should be able to store/retrieve the model on to/from hard disk (30pts). Remember to use Hash or HashMap. 4. Write a program to score and classify the sequences in two datasets. Evaluate the classification performances of the classification in terms of sensitivity, specificity, and correlation coefficient (30pts). Deadline: midnight 8 th Oct, 2009. Hand in your source code, compiled code and all data files used to generate the final result to webCT....
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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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