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Computational Approach in BioInformatics & Related Area

Course No. CIS 786
Sections 115
Title Computational Approach in BioInformatics & Related Area
Course Website
Prerequisite(s) Basic knowledge of data structures, algorithms, and heuristic search methodologies— a previous bioinformatics course is preferred but not required.
Instructor Usman Roshan
  • Office Room No. : GITC 3802
  • Office Phone : 973-596-2872
  • Fax : 973-596-5777
  • Email :
  • Website:
  • Lab : N/A
  • Instructor Office Hours
    Description The lectures will cover computational approaches used in comparative bioinformatics with an emphasis on heuristic techniques. Some of the topics to be covered are phylogenetics, sequence alignment, microarray analysis, protein structure and function prediction and analysis, phylogeny-centric methods in comparative proteomics, and some statistical modelingsuch as hidden markov models. The required biology will be covered.

    Course goals This course will expose you to various bioinformatics problems and how to solve them in practice using heuristics. You will learn various heuristic techniques (which can be applied to related areas as well), various software programs which implement these heuristics, and also learn how to analyze and interpret the results of these programs. The course project will give you further depth in a particular area of bioinformatics
    Topics Date Topic
    09/07/05 Heuristic methods—complexity, local moves, local search
    iterated local search, ant colony optimization, TSP, SAT
    09/14/05 Phylogenetics—distance based methods, likelihood
    parsimony, heuristic searches
    09/21/05 Phylogenetics—large-scale phylogeny reconstruction
    divide-and-conquer methods, parallel methods, supertree methods
    09/28/05 Sequence alignment—pairwise, heuristic pairwise, FASTA, BLAST
    10/05/05 Multiple sequence alignment—various heuristics
    including progressive and iterative approaches
    10/12/05 Phylogenetic motifs—methods, implications, real data analysis
    10/19/05 Correlated mutation analysis
    10/26/05 Student presentations
    11/02/05 Student presentations
    11/09/05 Student presentations
    11/16/05 Student presentations
    11/23/05 Student presentations
    11/30/05 Student presentations
    12/07/05 Student presentations
    Text Book(s) The course will be based upon lecture notes and journal and conference publications.
    The following textbooks may be used for reference:

    _ Algorithms on strings, trees, and sequences: computer science and computational biology, Dan Gusfield

    _ Introduction to computational molecular biology, Setubal and Medianis

    _ Introduction to bioinformatics, Arthur Lesk

    _ An Introduction to Bioinformatics Algorithms, Neil Jones and Pavel Pevzner

    _ Biological sequence analysis: probabilistic models of proteins and nucleic acids, Durbin et. al.

    _ Protein bioinformatics, Eidhammer et. al.
    All the textbooks are available from the NJIT library and Amazon.
    Time & Place Wednesday 6:00 PM - 9:05 PM, Info 4415
    Other Info Course grade This will be depend upon a course project and a paper presentation. The course project can be, (1) an experimental performance study where you apply existing software for solving a problem and then analyze and interpret the results, or (2) a programming project where you implement an algorithm or heuristic and report on its performance. Other projects which may not fall under this category can also be considered. After completion, the project must be described in a report complete with methodology, results, and conclusion. The presentation should describe a recent published conference or journal paper. The paper must be approved by the instructor before presentation

    Cheating The NJIT Honor Code will be upheld and any violations will be brought to the immediate attention of the Dean of Students

    Changes to syllabus Students will be consulted and must agree to any modifications or deviations from the syllabus throughout the course (major deviations are not expected).

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