This is the preliminary (or launch) version of the 2023-2024 VCU Bulletin. This edition includes all programs
and courses approved by the publication deadline; however we may receive notification of additional program
approvals after the launch. The final edition and full PDF version will include these updates and will be available
in August prior to the beginning of the fall semester.
Michael S. Rosenberg, Ph.D.
Director
The Center for Biological Data Science is a multidisciplinary focus of research and scholarly activity within VCU Life Sciences. The mission of the center is to teach and advance interdisciplinary quantitative and computational data science for the life sciences, to provide experiential education in bioinformatics, and to promote collaborative and reproducible research.
BNFO 501. Introduction to Physical Implementation of Databases. 1 Hour.
Semester course; 1 lecture hour. 1 credit. Prerequisite: permission of instructor. Basic searching and sorting algorithm design, and advanced data structures including hashing and B-trees.
BNFO 505. Essentials of Statistics in Bioinformatics. 2 Hours.
Semester course; 2 lecture hours. 2 credits. Prerequisites: Statistics and permission of instructor. An intensive course designed for graduate students in either the biology/genomics or the computational science tracks of the bioinformatics program, aimed at providing the background in statistical concepts necessary for them to participate in graduate-level courses involving statistics. The course will focus on areas of particular interest in bioinformatics, including probability, combinatorics and linear models.
BNFO 507. Essentials of Molecular Biology in Bioinformatics. 2 Hours.
Semester course; 2 lecture hours. 2 credits. Prerequisites: Cell biology and permission of instructor; Pre- or corequisite: Organic chemistry or permission of instructor. An intensive course designed for graduate students in either the quantitative/statistics or the computational science tracks of the bioinformatics program, aimed at providing the background in molecular biology necessary for them to participate in graduate-level courses involving molecular biology. The course will focus on areas of particular interest in bioinformatics, including DNA, RNA and protein synthesis, gene structure, function and regulation, protein structure, activity and regulation, and the tools by which formation in these areas has been discovered.
BNFO 508. Introduction to Bioinformatics Research. 2 Hours.
Semester course; lectures and 3 laboratory hours. 2 credits. Prerequisites: graduate status and permission of instructor. Introduction to all active research programs in bioinformatics. Presentations of research programs by investigators and rotation of students through track-appropriate faculty labs to gain direct exposure to individual research projects. Graded as S/U/F. Required of all first-year students pursuing the thesis option (M.S.).
BNFO 514. Modeling Biocomplexity. 3 Hours.
Semester course; 2.5 lecture and .5 laboratory hours. 3 credits. Prerequisite: one year of calculus. Introduction to the modeling and simulation of the behavior of complex biological systems, including models in both continuous and discrete time. Numerical methods using mathematica, analytical methods using calculus and laboratory experiments using computer interfaces will be used to study population dynamics and the behavior of physiological systems exhibiting such properties as oscillations and chaotic biological dynamics. Crosslisted as: PHYS 514.
BNFO 530. Bioinformatics and Genomics in Drug Research. 3 Hours.
Semester course; 3 lecture hours. 3 credits. Covers the basic elements of cellular pathways and drug interactions, and how modern genomics comes into play. Presents bioinformatics principles being used every day in data-intensive fields of research. Introductory and concept-oriented, the course will prepare students for grasping how bioinformatics is being used in many areas of biomedical sciences. Geared toward students coming from a variety of backgrounds in biology, biochemistry and chemistry. While many of the analytical approaches are statistical in nature, there is no requirement for a background in statistics or mathematics. Each student will have the opportunity to design a small project applying bioinformatics concepts. Crosslisted as: MEDC 530.
BNFO 531. Quantitative Methods in Bioinformatics. 3 Hours.
Semester course; 3 lecture hours. 3 credits. Enrollment is restricted to students with graduate status or permission of instructor. Students will be introduced to quantitative methods including probability and statistical theory in order to recognize and interpret the underlying mathematics behind common bioinformatic analyses. Students will learn to apply these bioinformatic data analysis principles using packages and tools in the R software environment. Topics covered include regression, differential expression, t-SNE and principal component analyses.
BNFO 540. Fundamentals of Molecular Genetics. 3 Hours.
Semester course; 3 lecture hours. 3 credits. Prerequisite: BIOL 310 or consent of instructor. The basic principles and methodologies of molecular biology and genetics are applied to genome organization, replication, expression, regulation, mutation and reorganization. Emphasis will be placed on a broad introduction to and integration of important topics in prokaryotic and eukaryotic systems. Crosslisted as: BIOL 540.
BNFO 541. Laboratory in Molecular Genetics. 2 Hours.
Semester course; 1 lecture and 4 laboratory hours. 2 credits. Pre- or corequisite: BIOL 540 or equivalent. Experiments are designed to apply advanced techniques and concepts of molecular biology and genetics using prokaryotic and eukaryotic systems. Emphasis will be placed on experimental design, integrating results throughout the semester, making use of relevant published literature, scientific writing and providing hands-on experience with advanced equipment and methodologies. Crosslisted as: BIOL 541.
BNFO 591. Special Topics in Bioinformatics. 1-4 Hours.
Semester course; 1-4 lecture hours. 1-4 credits. May be repeated for a maximum total of eight credits, with the provision that no more than eight combined credits of BNFO 591 and BNFO 593 can apply toward graduation. Adviser's approval is required for counting each special topics course toward meeting specific requirements of the master's program. An introductory, detailed study of a selected topic in bioinformatics unavailable as an existing course. If multiple topics are offered, students may elect to take more than one.
BNFO 592. Independent Study. 1-9 Hours.
Semester course; 1-9 independent study hours. 1-9 credits. Determination of the amount of credit and permission of instructor, adviser and curriculum committee must be obtained prior to registration for this course. Designed to provide an opportunity for independent study at an introductory graduate level in a bioinformatics-related area of interest and significance to the student outside what is available through the courses and other options in the Bioinformatics Program. Graded as satisfactory/unsatisfactory.
BNFO 593. Special Topics in Bioinformatics. 1-4 Hours.
Semester course; 1-4 lecture hours. 1-4 credits. May be repeated for a maximum total of eight credits, with the provision that no more than eight combined credits of BNFO 591 and BNFO 593 can apply toward graduation. An advanced, detailed study of a selected topic in bioinformatics unavailable as an existing course. If multiple topics are offered, students may elect to take more than one. Adviser's approval is required for counting each special topics course toward meeting specific requirements of the B.S. or M.S. programs. Graded as satisfactory/unsatisfactory.
BNFO 600. Basic Scripting Languages. 3 Hours.
Semester course; 3 lecture hours. 3 credits. Basics of programming in Python or other appropriate scripting language.
BNFO 601. Integrated Bioinformatics. 4 Hours.
Semester course; 3 lecture and 3 laboratory hours. 4 credits. Enrollment requires permission of instructor. Presents major concepts in bioinformatics through a series of real-life problems to be solved by students. Problems addressed will include but not be limited to issues in genomic analysis, statistical analysis and modeling of complex biological phenomena. Emphasis will be placed on attaining a deep understanding of a few widely used tools of bioinformatics. Crosslisted as: BIOL 601.
BNFO 620. Bioinformatics Practicum. 3 Hours.
Semester course; 3 lecture hours. 3 credits. BNFO 601/BIOL 601 or permission of instructor. Practical application of bioinformatics to genomic, proteomic and pharmacogenomic analyses. Students will work in small groups to plan, develop and execute a project designed to solve practical challenges in the realm of bioinformatics. Proficiency in various aspects of bioinformatics will be developed.
BNFO 621. Business and Entrepreneurship Essentials for Life Scientists. 3 Hours.
Semester course; 3 lecture hours. 3 credits. Consists of presentations on the core concepts of business, including intellectual property, patents and patent law, entrepreneurship, launching a "start up," raising capital, financial management, marketing, managerial accounting, planning, and project management. Course includes lectures and discussions on core concepts of business and their real-world application. Students will develop a business plan and/or a plan to manage a research project. Business case studies and team projects with presentations are required. Focus is on the biotechnology and pharmaceutical industries.
BNFO 637. Networks Biology. 3 Hours.
Semester course; 2.5 lecture hours. 3 credits. Prerequisite: prior course work in cell biology or molecular biology, or permission of instructor. Covers in detail networks as a basic tool for the systems biology approach to biology and medicine, particularly on the molecular level. Qualitative and quantitative aspects of biological systems and processes will be identified and analyzed. The course focuses on the biochemical networks formed in the cell from genes, proteins and metabolites. Network structure and dynamics will be characterized proceeding from graph theory and other mathematical methods. Essential part of the course is the practical work with basic software for building, manipulation and analysis of biological networks, as well as for identifying structural motifs and modules, and comparative network organisms (human, drosphila, yeast, C. elegans).
BNFO 650. Sequence Analysis in Biological Systems. 3 Hours.
Semester course; 1 lecture and 2 laboratory hours. 3 credits. Prerequisite: BNFO 601/BIOL 601 or permission of instructor. This course will treat the computational theory behind algorithms that are used for nucleic acid and protein sequence analysis. Students will be exposed to the theory and methodology of computational biology that has led to the development of current sequence analysis software. The objective of the course is to provide students with a basic knowledge of how current software tools have been developed and how they function, which will permit them to then apply this knowledge to the development of new algorithms and technology.
BNFO 653. Advanced Molecular Genetics: Bioinformatics. 3 Hours.
Semester course; 3 lecture hours. 3 credits. Prerequisites: Cell/molecular biology or permission of instructor. An advanced course on contemporary bioinformatics. Topics covered include the principles and practice of DNA, RNA and protein sequence analysis, computational chemistry and molecular modeling, expression array analysis and pharmacogenomics. The course includes lectures, reading, computer lab, homework problem sets and projects. Crosslisted as: MICR 653.
BNFO 690. Seminars in Bioinformatics. 1 Hour.
Semester course; 1 lecture hour. 1 credit. Presentation and discussion of research topics of current interest in the field of bioinformatics. Graded as satisfactory/unsatisfactory.
BNFO 691. Special Topics in Bioinformatics. 1-4 Hours.
Semester course; 1-4 lecture hours. 1-4 credits. May be repeated for a maximum total of eight credits, with the provision that no more than eight combined credits of BNFO 691 and BNFO 693 can apply toward graduation. Adviser's approval is required for counting each special topics course toward meeting specific requirements of the master's program. An advanced, detailed study of a selected topic in bioinformatics unavailable as an existing course. If multiple topics are offered, students may elect to take more than one.
BNFO 692. Independent Study. 1-9 Hours.
Semester course; variable hours. Variable credit. Determination of the amount of credit and permission of the instructor, adviser and curriculum committee must be obtained prior to registration for this course. A course designed to provide an opportunity for independent study in a bioinformatics-related area of interest and significance to the student outside what is available through the courses and other options in the Bioinformatics Program.
BNFO 693. Special Topics in Bioinformatics. 1-4 Hours.
Semester course; 1-4 lecture hours. 1-4 credits. May be repeated for a maximum total of eight credits, with the provision that no more than eight combined credits of BNFO 691 and BNFO 693 can apply toward graduation. Adviser's approval is required for counting each special topics course toward meeting specific requirements of the master's program. An advanced, detailed study of a selected topic in bioinformatics unavailable as an existing course. If multiple topics are offered, students may elect to take more than one. Graded as satisfactory/unsatisfactory.
BNFO 697. Directed Research in Bioinformatics. 1-9 Hours.
Semester course; variable hours. 1-9 credits. May be repeated for credit. Directed research leading to the M.S. degree in bioinformatics. Graded as S/U/F.
BNFO 700. Externship in Bioinformatics. 1,2 Hour.
Semester course; variable hours. 1 or 2 credits. Prerequisites: BNFO 601/BIOL 601 and BNFO 620, or permission of instructor. Typically off-campus planned experiences for advanced graduate students designed to extend professional competencies, carried out in a professional setting under supervision of an approved professional. Externship activities monitored and evaluated by university faculty. Plan of experience designed by extern and external adviser with prior approval of department. An externship class will meet weekly using online technology to accommodate students doing out-of-town summer externships. Each externship will be a defined project leading to a required final report or product and offering real potential benefits to the sponsoring company/lab. Subsequent to the externship, a presentation to program faculty and students is required.