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Degree requirements for the M.S. in Bioinformatics Animal Sciences concentration
Degree requirements for the M.S. in Bioinformatics Animal Sciences concentration
The Animal Sciences concentration within the M.S. degree program in Bioinformatics requires a minimum of 36 hours, including at least 12 hours at the 500-level. Of the 36 hours, 8 hours must be on thesis research in the Department of Animal Sciences and 28 hours must be on course work distributed as follows:
- Core courses. At least 12 hours distributed as follows:
- Fundamental Bioinformatics (4 hours)
ANSC 542 Applied Bioinformatics
ANSC 543 / CHBE 571 / MCB 571 STAT 530 Bioinformatics - Biology (4 hours)
ANSCI 446 Population Genetics
ANSCI 447 Quantitative Genetics
CPSC 452 Genetics of Higher Organisms
CPSC 568 Recombinant DNA Technology Lab
CPSC 556 Plant Gene Regulation
CPSC 564 Molecular Marker Data Analysis - Computer Science (4 hours)
CS 411 Database Systems
CS 473 Algorithms - Computational, Quantitative and Statistical Biology courses. At least 7 hours distributed as follows:
- One course to be selected between: ANSC 440 Applied Statistical Methods I ANSC 540 Applied Statistical Methods II
- And at least one course to be selected among:
ANSC 441 Human Genetics
ANSC 444 Applied Animal Genetics
ANSC 440 Applied Statistical Methods I
ANSC 540 Applied Statistical Methods II
ANSC 446 Population Genetics
ANSC 447 Quantitative Genetics
ANSC 542 Applied Bioinformatics
ANSC 543 Bioinformatics
ANSC 545 Statistical Genomics
CPSC 432 Genetic Toxicology
CPSC 440 Applied Statistical Methods I
CPSC 452 Genetics of Higher Organisms
CPSC 453 Principles of Plant Breeding
CPSC 454 Plant Breeding Methods
CPSC 540 Statistical Methods II
CPSC 541 Applied Statistical Methods III
CPSC 558 Quantitative Plant Breeding
CPSC 563 Molecular Cytogenetics
CPSC 564 Molecular Marker Data Analyses
CPSC 567 Bioinformatics and Systems Biology
CS 400 Data Structures, Non-CS Majors
CS 411 Database Systems
CS 413 Intro to Combinatorics
CS 418 Computer Graphics
CS 420 Intro to Parallel Programming
CS 446 Machine Learning & Pattern Rec
CS 450 Intro to Numerical Analysis
CS 473 Algorithms
CS 484 Computer Data Acquisition Sys
CS 512 Data Mining
CS 519 Scientific Visualization
CS 542 Artificial Neural Networks
CS 578 / STAT 563 Information Theory
CHBE 580 Laboratory Techniques in Bioinformatics
STAT 424 Analysis of Variance
STAT 425 Applied Regression and Design
STAT 429 Time Series Analysis
STAT 525 Computational Statistics
STAT 571 Multivariate Analysis
VP 554 Mol and Evol Epidemiology
MCB 418 Human Genetics
MCB 421 Microbial Genetics
MCB 423 Evolution in a Microbial World
MCB 432 Computing in Molecular Biology
MCB 554 Genomics, Proteomics, Bioinformation
IB 402 Molecular Evolution
IB 405 Ecological Genetics
IB 504 Genomic Analysis of Insects
LIS 451 Intro to Network Systems
LIS 501 Info Org and Access
BIOP 420 Molecular Biophysics
BIOP 541 Macromolecular Modeling
CHEM 574 Genomics, Proteomics, and Bioinformation - Seminar: 2 hours of Animal Sciences Seminar.
- Elective Graduate Courses
Graduate courses selected by the student in consultation with his/her advisor.
Within the previous list of courses, Animal Sciences courses are favored and highly recommended. No double-counting of course work is allowed; the same course cannot be used to satisfy the Core and the Computational, Quantitative and Statistical Biology requirements simultaneously.
Students must maintain a grade point average of at least 3.00 (4.00=A) while they are enrolled in the program.
Students must defend a thesis that is approved by a committee of at least three UIUC Graduate faculty and submitted to the Graduate College in conformance with Graduate College requirements. All requirements must be completed within five years of initial registration in the Graduate College.
Prerequisites
To ensure the success of all students pursuing this concentration within the M.S. in Bioinformatics in a timely manner, applicants to the program must have a solid background in biology, training in mathematics, and some experience in computer science. Expected background includes:
- at least one Calculus course equivalent to U of I MATH 220 or 234 or more advanced,
- at least one Statistics course equivalent to U of I STAT 100 or ACE 261 or CPSC 241 or MATH 161 or more advanced,
- at least one Plant (Animal) or Microbe Biology course equivalent to U of I ANSC 100 or IB 104 or MCB 100 or more advanced,
- at least one introductory Computer Science course equivalent to U of I CS 101 or 110.
Students with deficiencies in these prerequisites are expected to remediate this situation even when the remediation does not amount to credit towards the Animal Sciences concentration within the M.S. in Bioinformatics degree.
Applications
Students may enter this concentration within the M.S. in Bioinformatics program through the Department of Animal Sciences.
Contact information
Links
Laboratory of Bioinformatics, Department of Animal Sciences
Campus-wide M.S. in Bioinformatics
Department of Animal Sciences