Department of Bioinformatics and Computational Biology  George Mason University

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BINF Course Descriptions


  • BINF 354 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. Interdisciplinary course designed as an introduction to life sciences for physicists, chemists, engineers, and mathematicians. Combines knowledge from the core General Education areas of natural sciences, social and behavioral sciences, quantitative reasoning, and information technology. Covers selected topics in ecology, physiology, biochemistry, and behavior. May include biochemical reaction kinetics, Hodgki Huxley model for cellular electrical activity, continuous and discrete population interactions, and neural network models of learning. Techniques utilized include ordinary differential equations, difference equations, algebraic equations, and computer simulations.

  • BINF 401 Bioinformatics and Computational Biology I (3:3:0). Prerequisites: BIO 213, IT 108, IT 208, STAT 344 or STAT 250. Topics are presented as 3-week units: protein sequence, structure prediction and modeling methods; nucleic acid sequence and structure prediction and evolutionary models; gene structure prediction in prokaryotes and eukaryotes; image analysis and biomedical applications.

  • BINF 402 Bioinformatics and Computational Biology II (3:3:0). Prerequisites: BINF 401 and BINF 403. Topics are presented as 3-week units: the design and use of parallel genomics platforms, mapping the measurements to biomolecules; approaches for inferring biological pathways; simulation methods for the dynamics of biomolecules; systems approaches to biology.

  • BINF 403 Bioinformatics and Computational Biology Lab I (1:0:3). Prerequisites: concurrent enrollment in BINF 401. Laboratories will introduce students to bioinformatics tools designed to answer research problems in the topics covered in lectures, such as sequence alignment, sequence pattern recognition, structural conformation modeling, phylogenetic analysis methods and image comparisons.

  • BINF 404 Bioinformatics and Computational Biology Lab II (1:0:3). Prerequisites: concurrent enrollment in 402 and a passing grade in BINF 401 and BINF 403. Laboratories will introduce students to research bioinformatics tools relevant to lecture topics such as: the correspondence of measured fragments to parent biomolecules, inference methods for gene and protein networks, predicting system outputs given specified inputs.

  • BINF450 Bioinformatics for Life Sciences (4:3:3). Prerequisites: BIOL 213 and either BIOL 482 or CHEM 463/BIOL 483. The use of bioinformatics has become pervasive throughout the life sciences. This course will teach the students how to understand the basis of and use of bioinformatics software in database searching, sequence analysis, gene identification, genomics, protein structure and phylogeny.

  • BINF 470 Molecular Biophysics (3:3:0). Prerequisites: PHYS307 or CHEM331 or permission of instructor. The course offers a broad introduction into molecular biophysics. The course demonstrates that the application of methods of physics provides a unique opportunity to tackle complex biological problems. The course is mainly designed for the students majoring in physics or chemistry, but it is also useful for the biology majors interested in bioinformatics and computational biology. This course is cross-listed with PHYS 370.

  • BINF 491 Senior Thesis in Bioinformatics (1:1:3). Prerequisites: the bioinformatics minor core classes. A project is chosen and completed under the guidance of a bioinformatics department faculty member. An oral progress report with a poster at the fall semester Bioinformatics Student Research Day is required.

  • BINF 492 Senior Thesis in Bioinformatics (1:1:3). Prerequisites: BINF 492. A project is chosen and completed under the guidance of a bioinformatics department faculty member. A written thesis in standard format is required.

  • BINF 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.

  • BINF 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.

  • BINF 633 Molecular Biotechnology (3:3:0). Prerequisites: Graduate standing or permission of instructor. Lecture-based course introducing the theory and practice of biotechnology, with emphasis on molecular biotechnology. The lectures address how biotechnology and recombinant DNA technology affects society. Topics include a review of protein and nucleic acids technology, a review of recombinant DNA principles and applications, topics in prokaryotic and eukaryotic gene expression and products purification, medical applications and agricultural applications. Lectures reflect the recent advances and applications in the field.

  • BINF 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.

  • BINF 636 Microarray Methodology and Analysis (3:3:0). Prerequisite: BINF 633 or permission of instructor. 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.

  • BINF 637 Forensic DNA Sciences (3:3:0). Prerequisites: Graduate standing or permission of instructor. Intensive introduction to parameters affecting data QC and analysis, including factors arising from biochemistry, chemistry, genetics, statistics, instrumentation, and software.

  • BINF 639 Biometrics (3:3:0). Prerequisites: Programming experience (e.g. CSI 603 and 604) or permission of instructor. Introduction into methods for measuring humans. Topics include face recognition, speaker recognition, fingerprint recognition, shoeprint recognition, hand writing analysis, and other topics as time permits. Students will develop computer programs to perform many of these tasks.

  • BINF 650 Data Modeling for Bioinformatics (3:3:0). Prerequisites: BINF 634 or equivalent, or written permission of the instructor. Bioinformatics Databases and Data Models Students will acquire skills needed to exploit public biological databases, and establish and maintain personal databases that support their own research; such skills include learning underlying data models and the basics of DBMS, and SQL.

  • BINF 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 programs to solve the problem. Efficiency and readability of code will be emphasized.

  • BINF 701/BIOS 701 Biochemical Systematics (Biochemistry)(3:3:0). Prerequisite: Admission to the Ph.D. program in biosciences or bioinformatics, CHEM 663 or equivalent. Introduction to biochemical systems now in use to investigate complex, multicomponent, dynamic functions of cellular systems. Such studies employ myriad conceptual and technical approaches in their application. Articles from current literature are basis of 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 of the course.

  • BINF 702/BIOS 702 Research Methods (3:3:0). Prerequisite: Admission to the Ph.D. program in bioinformatics or biosciences or permission from instructor. 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.

  • BINF 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.

  • BINF 704 Colloquium 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 Ph.D. students, and professional visitors. May be repeated for credit.

  • BINF 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.

  • BINF 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.

  • BINF 731 Protein Structure Analysis (3:3:0). Prerequisite: Permission of instructor, or coursework in molecular biology, biochemistry, and computer programming. Computational 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.

  • BINF 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.

  • BINF 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.

  • BINF 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, web programming. Students will complete a bioinformatics programming project.

  • BINF 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.

  • BINF 740 Introduction to Biophysics (3:3:0). Prerequisites: The students are expected to be familiar with basic physical concepts, calculus, and biology on undergraduate level. This graduate course is designed as a broad introduction into the field of biophysics for the students with the background in biology, chemistry, computer science, or physics. The goal of the course is to present basic concepts of physics and chemistry and map them on a rapidly expanding interdisciplinary interface, combining biology, chemistry, and physics. The course reveals multiscale nature of biophysics by exploring macroscopic and microscopic applications. The course aims to balance the need for rigorous mathematical treatment with the simplicity of presentation.

  • BINF 741 Computer Simulation of Biomolecules (3:3:0). Prerequisites: Students are expected to be familiar, on an undergraduate level, with basic concepts in physics, calculus, and programming language suitable for numerical computations. Knowledge of biological aspects of simulations is not required. This course is intended to serve as an introduction to computational methods for simulating biological macromolecules, such as proteins, DNA and RNA. It is designed for the students who are interested in computational biology and whose background is in physics, chemistry, biology, computer science, or mathematics.

  • BINF 751 Biochemical & Cellular Models (3:3:0). Prerequisites: Calculus and knowledge of a programming language. Knowledge of differential equations is helpful. A student in this course will learn concepts and techniques that will enable them study cellular and subcellular processes using computational and mathematical methods. They will learn to describe a cellular or subcellular process by mathematical equations and analysis this system using mathematical and computational methods in order to get insight into cellular function in normal and diseased organisms.

  • BINF 760 Machine Learning for Bioinformatics (3:3:0). Prerequisites: Familiarity with bioinformatics methods and databases (e.g., BINF630), molecular cell biology (e.g., BINF631), bioinformatics programming (e.g., BINF634), or permission of the instructor. The course introduces machine learning and data mining methods relevant to application to problems in computational biology. Methods include decision trees, random forests, rule learning methods, support vector machines, neural networks, genetic algorithms, instance based learning, Bayesian networks, and evaluation metrics for learning systems. Applications include cancer prediction, gene finding, protein function classification, gene regulation network inference, and other recent bioinformatics applications selected from the literature. In addition to lectures from the instructor, students will present papers from the literature, and complete a machine learning project.

  • BINF 796 Directed Reading and Research (3:3:0). Prerequisites: Permission of the instructor. Reading and research on a specific topic in bioinformatics under the direction of a faculty member. May be repeated as necessary.

  • BINF 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.

  • BINF 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.

  • BINF 820 Advanced Topics in Molecular Cell Biology (3:3:0). Prerequisites: Molecular Cell Biology for Bioinformatics or permission from the instructor. This course will provide a molecular and cellular biology foundation for bioinformatics students, especially those with non biology backgrounds. It will also provide an opportunity to polish verbal presentation skills. The course will cover advanced topics in biochemistry, cellular biology, molecular biology and genomics, based on the foundations of Molecular Cell Biology for Bioinformatics. Continued background for bioinformatics research. May include reviews of Molecular Cell Biology for Bioinformatics.

  • BINF 831 Structural Genomics Project (3:3:0). Prerequisites: BINF 731. This is a project-based course, in which students work under the supervision of the instructor on solving the real-world problems in structural genomics. The course is designed to mimic a full cycle of the research enterprise: from developing and defending a proposal to peer reviewed publication. Most projects will involve applications of various knowledge based methods to the large scale protein structure analysis.

  • BINF 841 Research Topics in Biomolecular Simulations (3:3:0). Prerequisites: BINF 741 or good knowledge of one of the programmic languages and protein molecular structure and properties. This course, which is a sequel to BINF 741, is designed for students who are interested in computer simulations of biomolecules. The goal is to introduce students to cutting-edge research work in computer simulations on the basis of individual research projects. Each of the projects represents a small novel problem, which offers the potential for new original results. To maximize the productive participation of students in their research, the course emphasizes individual work with the instructor. Suggested research topics include a wide range of problems in the area of protein structure dynamics, folding and unfolding, docking, and aggregation. Students may also select several computational approaches, from molecular dynamics to Langevin dynamics or Monte Carlo simulations.

  • BINF 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 bioinformatics under the direction of a faculty member. May be repeated as needed.

  • BINF 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.

  • BINF 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.



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