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Bioinformatics (BINF) Core Courses

5110 Biology Seminar for Bioinformatics (1-0)

Reading and discussions of various topics in the biological sciences related to bioinformatics. Each student is expected to give at least one presentation during the course. Prerequisite: Department approval.

5111 Chemistry Seminar for Bioinformatics (1-0)

Reading and discussions of various topics in chemistry related to bioinformatics. Each student is expected to give at least one presentation during the course. Prerequisite: Department approval.

5112 Computer Science Seminar for Bioinformatics (1-0)

Reading and discussions of various topics in computer science related to bioinformatics. Each student is expected to give at least one presentation during the course. Prerequisite: Department approval.

5113 Mathematics Seminar for Bioinformatics (1-0)

Reading and discussions of various topics in mathematical sciences related to bioinformatics. Each student is expected to give at least one presentation during the course. Prerequisite: Department approval.

5341 Analysis and Modeling of Biological Structures (2-3)

Introduction to the principles and methods used for the three-dimensional structural determination and simulation of macromolecules of biological interest. Molecular recognition, conformational analysis, and molecular dynamics; ligand design and docking; and modern methods for protein structure determination. (BINF 5341 is the same course as CHEM 5341.) Prerequisite: Department approval. Laboratory fee required.

5351 Introduction to Bioinformatics I: Basic Sequence Comparisons (2-3)

Theory and practice of sequence analysis, with an emphasis on nucleic acid comparisons and homologue determination. Includes understanding and use of Internet and computational tools with both public sequencing databases and experimental data.(BINF 5351 is the same course as BIOL 5351.) Prerequisite: Department approval. Laboratory fee required.

5352 Introduction to Bioinformatics II: Gene Finding and Genomic Comparisons (2-3)

A continuation of BINF 5351 with an emphasis on the analysis of protein structural information. Also includes gene annotation and whole genome comparisons. (BINF 5352 is the same course as BIOL 5352.) Prerequisite: Department approval. Laboratory fee required.

5353 Internship in Bioinformatics (0-0-6)

Practical on-the-job experience as an intern academic, industry, or government institution which is a current or potential employer of bioinformatics professionals. No more than 3 hours of BINF 5353 may count toward a graduate degree. Prerequisite: Department approval.

5354 Post-Genomic Analysis (2-3)

The extraction and confirmation of information from entire and partially assembled genome sequences. Includes the design and use of DNA arrays, SNP's, and applied proteomics in the identification and verification of expressed genes of interest. (BINF 5354 is the same course as BIOL 5354 and STAT 5354.) Prerequisite: Department approval. Laboratory fee required.

In addition to the core, there are four other required courses. Course descriptions can also be found in the departmental listings of Biological Sciences (BIOL), Chemistry (CHEM), Computer Science (CS), and Mathematical Sciences of the CoS Graduate Catalog.

Bioinformatics Required Courses

All the Bioinformatics (BINF) Core Courses and the Following:

BIOL 5340 Structure and Function of Macromolecules (3-0)

Functional biology of cells, with emphasis on the relationship between molecular structure and function.

CS 5342 Database Management

Introduction to database fundamentals, database design and implementation, the use of database management systems for application, and current trends for data management. Topics in this course include: relational algebra, entity-relationship models, relational data models, normalization, semi-structured data models, schema design, query processing, data integrity, privacy, security and data analytics.

STAT 5329 Statistical Programming (1-2)

Introduction to statistical programming using statistical software packages such as SAS and R. Emphasis on methods of data entry, data management, and creation of statistical reports. Topics covered include data manipulation, creation of user-defined functions, simulation methods, random variable generation, permutation methods, the bootstrap, the jackknife and methods of increasing computational efficiency.

STAT 5428 Introduction to Statistical Analysis (3-2)

Fundamental techniques for statistical data analysis, including basic probability concepts, inference about means and variances of two populations, analysis of variance and covariance, least squares and logistic regression, categorical data analysis, nonparametric tests and experimental design. Analysis of biological and other data sets using statistical software packages, checking validity of modeling assumptions, and alternatives when modeling assumptions are not satisfied. Computer simulations are used to illustrate concepts such as power and confidence level.

Course descriptions can also be found in the departmental listings of Biological Sciences (BIOL), Chemistry (CHEM), Computer Science (CS), and Mathematical Sciences of the CoS Graduate Catalog.