COMP 555 - Bioalgorithms http://www.cs.unc.edu/~prins/Classes/555/ Fall 2012 (Tue Aug 21 - Tue Dec 4) TTh 12:30 - 1:45 PM, SN 115 Instructor: Jan Prins FB 334, Tel: 962-1913, prins@cs.unc.edu Office hours: Mondays 1:30 - 3:00 PM and by appointment

• Assignment 5 (last assignment) available

• Submission of the python Euler Path program for HW3

  • Please construct your python program so it defines a function def euler(G): that, given a graph G whose value follows the input format shown in the assignment, either returns a value that represents an Euler path of G in the output format shown in the assignment or else returns the distinguished python value None if no such path exists in G. Note this means your program should not read G from a file or user input and that it should not rely on printing instead of returning the result. (However your program is welcome to print informational or diagnostic output)
  • Collect your code together into a single file euler.py and place it in directory
    /afs/unc/project/courses/comp555/Submit/< login >/hw3
    on any CS linux machine (e.g. classroom.cs.unc.edu). Replace < login > with your CS login id. The directory will be readable and writeable by you but not by anyone else.
  • If you have problems with this procedure, talk to me in class or send me the file by email.

Overview

Computational methods are fueling a revolution in the biological sciences. Computers are already nearly as indispensable as microscopes for analyzing and interpreting biological data. As a result, two new multidisciplinary fields, bioinformatics and computational biology, have emerged. This course will explore the computational methods and algorithmic principles driving this revolution. It will cover basic topics in molecular biology, genetics, and proteomics. The course also addresses basic computational theory and algorithms including asymptotic notation, recursion, divide-and-conquer approaches, graph algorithms, dynamic programming, and greedy algorithms. These fundamental concepts from computer science will be taught within the context of motivating problems drawn from contemporary biology. Example biological topics include sequence alignment, motif finding, gene rearrangement, DNA sequencing, protein peptide sequencing, phylogeny, and gene expression analysis.

This course is suitable for both computer science and biology students at both undergraduate and graduate levels, and thus has a course number (555) that can provide credit at both levels. Students who wish to take this course should have some programming experience in a modern language. Knowledge of data structures, algorithm design, and biology is helpful but not required. There will be 5 problem sets with short programming assignments, a midterm, and a final exam.

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Prerequisites

• COMP 401, COMP 116, or equivalent introduction to programming.
• Some background in algorithms and data structures such as COMP 410 is helpful.
• Familiarity with discrete math and elementary probability is assumed.