As a professional school specializing in information management and systems, GSLIS is a natural fit to offer a concentration within the campus-wide MS in Bioinformatics. In the GSLIS concentration, we define "bioinformatics" broadly as the management of biological information of all types. The bioinformatics program is an entirely separate program from the existing GSLIS MS degree; students may not be simultaneously admitted to both programs; and the new concentration is not accredited by the American Library Association.
In the bioinformatics program, students may take courses in several departments across the University of Illinois campus. This breadth of training provides students with the multidisciplinary skills that are required for a career developing and managing information systems for the biological community. The program provides training from faculty who are international experts in many areas of information management, including bioinformatics, biology, chemistry, statistics, and computer science.
Library and information science (LIS) as a discipline has emphasized the use of information technology to support new approaches to the organization of and access to information. The bioinformatics program provides applied skills in building and evaluating systems that mediate effectively between users and collections. The bioinformatics program emphasizes the range of library and information science including: collection development, classification schemes, information retrieval, knowledge representation, user evaluation, data curation, and policy standards. Our students are taught to develop information management systems in biological applications, with opportunities to consider a broad spectrum of domains including molecular biology, environmental ecology, and biomedicine.
A GSLIS committee for admission to and oversight of the bioinformatics program reviews the suitability of each student's program of study, including any necessary remediation in biology or computing. The bioinformatics program requires a total of 36 hours of coursework, either with 36 hours of core required and elective courses or with 28 hours of core required and elective courses plus 8 hours of thesis work. At least 12 hours must be at the 500 graduate level. Students are allowed up to 4 hours of independent study as elective credit, with approval from their advisor. This program cannot be completed through the LEEP program. A Schedule Planning Guide is available to aid bioinformatics students in planning their coursework.
To satisfy the campus core requirements, one (1) course must be taken from each of the three (3) Core Areas: Biology, Computer Science, and Fundamental Bioinformatics. The courses approved for the core in the Biology, Computer Science, and Bioinformatics areas are listed on the campus-wide MS in Bioinformatics site. Additionally, GSLIS requires one (1) four-hour course in three of the following four (4) areas:
Information Organization and Knowledge Representation
LIS 561 Information Modeling
LIS 590II Interfaces to Information Systems
LIS 590I Indexing and Abstracting
LIS 590DM Document Modeling
LIS 590OD Ontology Development
LIS 590ON Ontologies in Natural Science
LIS 590RO Representing and Organizing Information Resources
Information Resources, Uses and Users
LIS 503 Use and Users of Information
LIS 522 Information Sources in the Sciences
LIS 530I Biological Informatics Problems and Resources
LIS 590TR Information Transfer and Collaboration in Science
Information Systems and Access
LIS 453 Systems Analysis and Management
LIS 456 Information Storage and Retrieval
LIS 556 Implementation of Information Retrieval Systems
LIS 560 Digital Libraries
LIS 566 Architecture of Network Information Systems
LIS 590DP Document Processing
LIS 590EP Electronic Publishing
LIS 590LD Literature-based Discovery
LIS 530B Health Sciences Information Services and Resources
LIS 590HI Healthcare Informatics (Healthcare Infrastructure)
LIS 590BD Biodiversity Informatics
A typical student will thus take 6 required courses (24 hours): 1 Biology, 1 Computer Science, 1 Fundamental Bioinformatics, and 3 GSLIS. The student must then choose 3 courses (12 hours) of electives to complete the degree. It is strongly encouraged that up to 2 courses of these electives (8 hours) are thesis. A recommended list of electives is given below. Our expectation is that each student will arrange a custom program of study, suitable for the information management of their particular bioinformatics application.
A student who has already completed coursework comparable to one or more of the required courses for the MS in bioinformatics prior to enrolling in the degree program may petition to waive enrollment in that required course and replace it with a comparable number of hours of elective credit toward the MS in bioinformatics. Such a petition needs to be approved by the advisor, the GSLIS associate dean, and the Graduate College. Additionally, students may request transfer of credit for graduate level coursework from any accredited institution (maximum 8 hours) that has not already been applied towards a degree.
CS 410 Text Processing Algorithms (joint with LIS)
CS 412 Introduction to Data Mining
CS 413 Introductory Combinatorics
CS 446 Machine Learning
CS 511 Design of Database Systems
CS 512 Data Mining
EPSY/PSYC 594 Multivariate Analysis
STAT 400 Introductory Statistics
PSYC 509 Multidimensional Scaling
UP 519 Spatial Analysis with GIS
IB 441 Plant Ecology
IB 452 Ecosystem Ecology
IB 462 Mammal Classification and Evolution
IB 468 Insect Classification and Evolution
CHLH 421 Health Data Analysis
CHLH 474 Principles of Epidemiology (VP 517)
CHLH 527 Statistics in Epidemiology
CHLH 590 Biostatistics
Note that the thesis option in the GSLIS bioinformatics master's program is OPTIONAL.
If you wish to write a master's thesis as part of your MS degree program, you will work with one faculty advisor negotiated in the same manner as an independent study. Advisors may be from departments outside of GSLIS. Prior to registering for LIS 599, Thesis Research, you should prepare a brief proposal of the thesis. Proposals should be reviewed and approved by the faculty advisor. If the faculty advisor is not from GSLIS, the proposal should also be reviewed and approved by a faculty member from GSLIS. Once the required approval(s) is secured, the proposal should be forwarded to the dean for signature. You will need to fill out the thesis proposal and request form. A maximum of 8 hours of LIS 599 credit can be applied to the MS degree. The thesis must conform to the requirements of the Graduate College as stated in the latest edition of the Handbook for Graduate Students Preparing to Deposit and be deposited in the Thesis Office before the MS degree will be awarded.
Once the thesis is complete, the dean, on recommendation from the faculty advisor, who serves as first reader, appoints a second reader. The first reader (faculty advisor) and second reader will confer and must agree upon the acceptability of the thesis or whether any revisions must be made before final acceptance. Should the two readers be unable to reach agreement about the evaluation of the thesis, a third reader may be appointed. Ordinarily there is no oral defense of the thesis.
The final version of the thesis must have a format check done by Linda Meccoli, the GSLIS departmental format checker, and receive a format approval form before it can be deposited in the Graduate College.
Applicants must have completed a bachelor's degree with a minimum grade-point average of 3.0 on a 4.0 scale. A minimum grade-point average of 3.0 also is required in the last two years of the applicant's undergraduate degree program. The Admissions Committee makes every effort to assess applicants on their probable degree of success in the program, rather than relying only on how well the applicant meets the formal requirements. Contact the GSLIS admissions officer with questions about the admissions process: (217) 333-7197.
Please see the Admissions section of our website for specific application requirements, deadlines, and forms.
Please see the Computer Literacy Requirements for information about expected technical competencies.