Bioinformatics (BINF)School of Computational Sciences354 Foundations in Mathematical Biology (3:3:0). Prerequisites: Completion or concurrent enrollment in all other required general education courses; chemistry and integral calculus; or permission of instructor. This interdisciplinary course is designed as an introduction to the life sciences for physicists, chemists, engineers, and mathematicians. The course combines knowledge from the core General Education areas of natural sciences, social and behavioral sciences, quantitative reasoning, and information technology. Covers selected topics in the fields of ecology, physiology, biochemistry, and behavior. The topics may include biochemical reaction kinetics, the HodgkinHuxley model for cellular electrical activity, continuous and discrete population interactions, and neural network models of learning. The techniques utilized in the course include ordinary differential equations, difference equations, algebraic equations, and computer simulations. 630 Bioinformatics Methods (3:3:0). Prerequisites: Graduate standing or permission of instructor. Introduction to bioinformatics methods and tools for pairwise sequence comparison, multiple sequence alignment, phylogenetic analysis, protein structure prediction and comparison, database similarity searches, and discovery of conserved patterns in protein sequence and structures. 631 Molecular Cell Biology for Bioinformatics (3:3:0). Prerequisites: Undergraduate background in biochemistry or cell biology, or permission of instructor. Intensive review of aspects of biochemistry, molecular biology, and cell biology necessary to begin research in bioinformatics. Topics include cell structure and cell cycle; DNA replication, transcription, and translation; molecular structure of genes and chromosomes. 633 Molecular Biotechnology (3:3:0). Prerequisites: Graduate standing or permission of instructor. A laboratory intensive course introducing the theory and practice of modern biotechnology. Includes study of recombinant DNA, gene expression, and genetic analysis and associated methods. Laboratory exercises change to reflect the more recent advances in the field. 634 Bioinformatics Programming (3:3:0). Prerequisites: Graduate standing and computer programming experience or permission of instructor. Data representation, control structures, file input/output, subroutines, regular expressions, debugging, introduction to relational databases. An emphasis on bioinformatics applications including DNA sequence analysis, parsing FASTA and GenBank files, processing BLAST output files, SQL or equivalent query language. 636 Microarray Methodology and Analysis (3:3:0). Prerequisite: BINF 633 or permission of instructor. Introduces the theory and practice of genome analysis, including the genetics, biochemistry, and tools for analysis of global gene expression, as well as the detection and quantification of genes and gene products. 637 Forensic DNA Sciences (3:3:0). Prerequisites: Graduate standing or permission of instructor. A laboratory intensive course that introduces the theory and practice of modern forensic DNA science, including the biochemistry, chemistry, genetics, statistics, instrumentation, software, and wetware required for applications of DNA science to forensic science. 639 Introduction to Biometrics (3:3:0). Prerequisites: Programming experience (e.g., CSI 603 and 604) or permission of instructor. Introduction to methods for measuring humans. Topics include face recognition, speaker recognition, fingerprint recognition, shoeprint recognition, handwriting analysis, and other topics as time permits. Students will develop computer programs to perform many of these tasks. 690 Numerical Methods for Bioinformatics (3:3:0). Prerequisites: Calculus and knowledge of a programming language, e.g., CS 112 and MATH 113, or permission of the instructor. Computational techniques for solving scientific problems focusing on applications in bioinformatics and computational biology. The student will develop the ability to convert a quantitative problem into computer pro grams to solve the problem. Efficiency and readability of code will be emphasized. 701/BIOS 701 Biochemical Systematics (Biochemistry) Core for Doctoral Studies in Biosciences and Bioinformatics (3:3:0). Prerequisite: Admission to the PhD program in biosciences or bioinformatics, CHEM 663 or equivalent. The course introduces students to the biochemical systems now in use to investigate complex, multicomponent, dynamic functions of cellular systems. Such studies employ an array of conceptual and technical approaches in their application. Articles from the current literature highlight this aspect of research in the molecular biosciences and are used as the basis of this course offering. The application of molecular techniques within biosciences is now universal. The cell: What is its structure and how does it function? This is the underlying question that a student should keep in mind as the course proceeds. 702/BIOS 702 Research Methods (3:3:0). Prerequisite: Admission to the PhD program in bioinformatics or biosciences. This course trains students in research methodologies for the life sciences. The course will cover the three phases of biological research projects: experimental design, data collection, and data analysis. 703 Bioinformatics Lab Rotation (1:0:1). Prerequisite: Permission of instructor. Short-term introductory research on a specific topic in computational sciences and informatics under the direction of a faculty member. May be repeated as necessary. 704 Seminar in Bioinformatics (1:1:0). Prerequisite: Graduate standing. Seminar presentations in a variety of areas of bioinformatics and computational biology by School of Computational Sciences faculty, staff, advanced PhD students, and professional visitors. May be repeated for credit. 705 Research Ethics (1:1:0). Prerequisite: Permission of instructor. An examination of ethical issues in scientific research. The course begins with a reflection on the purpose of scientific research and a review of the foundational principles used for evaluating ethical issues. It provides skills for survival in scientific research through training in moral reasoning and teaching of responsible conduct. Students learn to apply critical thinking skills to the design, execution, and analysis of experiments and to the analysis of current ethical issues in research. Such issues include the use of animals and humans in research, ethical standards in the computer community, and research fraud. In addition, currently accepted guidelines for behavior in areas such as data ownership, manuscript preparation, and conduct of persons in authority may be presented and discussed in terms of relevant ethical issues. 730 Biological Sequence Analysis (3:3:0). Prerequisites: BINF 702 or previous courses in programming, molecular biology, and probability, or permission of instructor. Fundamental methods for the analysis of nucleic acid and protein sequences, including pairwise alignment, multiple alignment, database search methods, profile searches, and phylogenetic inference. Development of probabilistic tools, including hidden Markov models and optimization algorithms. Survey of current software tools. 731 Protein Structure Analysis (3:3:0). Prerequisite: Permission of instructor, or previous courses in molecular biology, biochemistry, and computer programming. Com putational methods for the analysis, classification and prediction of three-dimensional protein structures. The course covers theoretical approaches, techniques, and computational tools for protein structure analysis. 732 Genomics (3:3:0). Prerequisites: BINF 730 or previous courses in biology, numerical methods, and programming, or permission of instructor. A survey of computational tools and techniques used to study whole genomes. The biological basis of genome analysis algorithms will be explored. Lecture topics include genome mapping, comparative genomics, and functional genomics. 733 Gene Expression Analysis (3:3:0). Prerequisites: Programming experience and a course in molecular biology, or permission of instructor; S-Plus or Matlab experience may also be helpful. This course will focus on the analysis of gene expression data. Particular topics include: cluster analysis and visualization of expression data; inference of genetic regulatory networks; and theoretical models of genetic networks. 734 Advanced Bioinformatics Programming (3:3:0). Prerequisites: BINF 634 or permission of the instructor. Selected topics including algorithm design, complex data structures, object oriented programming, relational databases, designing modules, graphics programming, and web programming. Students will complete a bioinformatics programming project. 739 Topics in Bioinformatics (3:3:0). Prerequisite: Permission of instructor. Selected topics in bioinformatics not covered in fixed-content bioinformatics courses. May be repeated for credit as needed. 796 Directed Reading and Research (3:3:0). Reading and research on a specific topic in computational sciences and informatics under the direction of a faculty member. May be repeated as necessary. 798 Research Project (3:0:0). Prerequisites: Twelve graduate credits and permission of instructor. Project chosen and completed under the guidance of a graduate faculty member, which results in an acceptable technical report. 799 Master's Thesis (1-6:0:0). Prerequisites: Twelve graduate credits and permission of instructor. Project chosen and completed under the guidance of a graduate faculty member, which results in an acceptable technical report (master's thesis) and oral defense. Graded S/IP. 996 Doctoral Reading and Research (1-12:0:0). Prerequisites: Admission to doctoral program and permission of instructor. Reading and research on a specific topic in computational sciences and informatics under the direction of a faculty member. May be repeated as needed. 998 Doctoral Dissertation Proposal (1-12:0:0). Prerequisite: Permission of advisor. Covers development of a research proposal, which forms the basis for a doctoral dissertation, under the guidance of a dissertation director and the doctoral committee. May be repeated as needed; however, no more than 12 credits of BINF 998 may be applied toward satisfying doctoral degree requirements. 999 Doctoral Dissertation (1-12:0:0). Prerequisite: Admission to doctoral candidacy. Doctoral dissertation research under the direction of the dissertation director. May be repeated as needed; however, no more than a total of 24 credits in BINF 998 and 999 may be applied toward satisfying doctoral degree requirements. |
