Indiana University Purdue University Indianapolis

Graduate Certificate in Biocomputing

Recent developments in science produce a wealth of experimental data of sequences and three dimensional structures of biological macromolecules. With the advances of computer and information science, this data is available to the public from the variety of databases on the internet. Analysis of this data with various computational methods to obtain useful information is an emerging interdisciplinary area of study.

Students completing this certificate will understand structures, functions and evolution of proteins and nucleic acids, retrieve and interpret bioinformation from the internet, learn principles, algorithms and software for sequence alignment, similarity search of sequence databases, estimation of phylogenetic trees, structural prediction and functional interference.

Program Requirements

A graduate certificate will be issued when a student has completed 12 graduate credit hours in one of the specialization areas. After finishing the requirements for the graduate certificate, the student may opt to finish the remaining requirements towards a MS degree.*

  • One Core Course: BIOL 50700 (Molecular Biology) or CSCI 58000 (Algorithms)
  • 3 Specialization Courses:
    • 54800 (Introduction to Bioinformatics)
    • 59000 (Intelligent Systems) or 57300 (Data Mining)
    • 54100 (Database Systems) or 55200 (Visualization)

The Need for Experts in Biocomputing

The popularity and the growth of the Internet and associated networking technologies are allowing a rapidly increasing number of users, representing diverse segments of the society to access an enormous amount of geographically dispersed information available in different electronic form and media. With the successful completion of prominent efforts, such as the Digital Library Initiative, this volume of information will grow at a phenomenal rate. Without effective automated support systems to access and filter such information, an average user runs the risk of being overwhelmed by the sheer volume of irrelevant and possibly unwanted information. Providing a personalized, efficient, adaptive and intelligent access to this plethora of information, without creating an "information overload" on the users, is a major challenge right now, and will become increasingly urgent as we head into the next millennium.

The explosive growth of biological genetic information sources, available over the Internet, has given rise to both opportunities and challenges for biological and medical researchers. The opportunities they provide are both scientific (e.g., understanding the information encoded in elementary biological structures) as well as technological (e.g., new drug discovery for specific diseases). The challenges, on the other hand, lie in how to discover, among the vast volume of data, the items that are relevant or interesting to a given researcher, without an undesirable amount of effort and work load.

The complete information system development is based on an agent-society framework where the elementary information services such as resource discovery and information retrieval, representation, classification, and user interaction are carried out autonomously by independent software units (called agents), and the large-scale information activity is accomplished by means of collaboration between these elementary agents. Such a conceptual agent-based information system is innovative and has the potential to scale up to a broad range of complex information services.

*Admission and completion of Certificate does not guarantee MS program admission.

 


If you have any questions regarding the Computer & Information Science  Graduate Program please contact admissions@cs.iupui.edu.