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Level >Graduate >FALL_2005 >List >

Data Mining & Management in Bioinformatics

Course No. CIS 744
Sections 001, 851
Title Data Mining & Management in Bioinformatics
Course Website
Prerequisite(s) Knowledge of C/C++ and SQL or permission from the instructor
Instructor Jason Wang
  • Office Room No. : GITC 4211
  • Office Phone : 973-596-3396
  • Fax : 973-596-5777
  • Email :
  • Website:
  • Lab : Data and Knowledge Engineering Lab
  • Instructor Office Hours
    Description Reviews entity-relationship diagrams and relational database design and their use in modeling biological data. Surveys public genomic databases and tools for managing these databases. Addresses issues concerning data cleaning and integration of multiple biological databases available on the intra and internet. Covers concepts and principles of data management in bioinformatics. Presents methods for indexing, querying, and mining data obtained from molecular and evolutionary biology. Hands-on experience concerning designing a simple information system for querying and mining genomic data using ORACLE and SQL.
    Topics This course covers the concepts and techniques of

    1. Bioinformatics Data Mining and Management

    2. Biosequence Matching and Mining

    3. Multiple Sequence Alignment

    4. Phylogenetic Data Management

    5. Molecular Evolution

    6. Graph Matching, Searching and Mining

    7. Data Cleaning and Integration

    8. Advanced Data Mining and Management in Bioinformatics

    9. New Applications

    Text Book(s) Status: Optional, not required
    Book Title: Algorithms on Strings, Trees, and Sequences: Computer Science
    and Computational Biology
    Author(s): Dan Gusfield
    Publisher: Cambridge University Press
    ISBN: 0521585198
    Edition: 1st edition

    Status: Optional, not required
    Book Title: Data Mining in Bioinformatics
    Author(s): Jason T. L. Wang, Mohammed J. Zaki, Hannu T.T. Toivonen,
    Dennis Shasha (Editor)
    Publisher: Springer
    ISBN: 1852336714
    Edition: 1st edition
    Time & Place Wednesdays 10:00 AM - 12:55 PM, Kupf 205 & DL
    Other Info Academic Honor Code

    Course Workload
    There will be 3 assignments, 1 term project, 1 term paper and a final exam.

    Course Grade
    Assignments -- 30%, Term project -- 20%, Term paper -- 20%, Final exam -- 30%.

    Grading Scale
    A: 88% or above; B+: 84% or above; B: 78% or above; C+: 72% or above; C: 60% or above.

    Honor and Policy

    Students found cheating, plagiarizing, or collaboration (collaboration is allowed for those working together in approved team projects) will be immediately referred to the Dean of Students and the NJIT Committee on Professional Conduct and subject to Disciplinary Probation, a permanent marking on the record, possible dismissal, and an "F" grade in the course. All submitted assignments will be checked for similarities, and plagiarism and guilty students identified.
    In the exam, each student is required to sign the Honor Code Agreement "On my honor, I pledge that I have not violated the provision of the NJIT Student Honor Code."

    Registrar's Website