16:848:405
Differential Equations in Biology (3)
Models for biological processes based on deterministic ordinary and partial differential equations. Topics include stability, bifurcations, periodic phenomena, transport, and diffusion.
Sontag. Prerequisites: Differential equations and linear algebra.
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16:848:503
Introduction to Computational Biology and Molecular Biophysics (3)
Introduction to the phenomena ranging from molecular interactions to biological behavior at the level of cells, tissues, and organisms.
Prerequisites: Linear algebra; calculus; and a good biology, chemistry, and physics background at the high school level.
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16:848:505
Dynamic Models of Biology (3)
A remedial course focusing on differential equations, Fourier and Laplace transforms, and stochastic processes for students interested in quantitative biology.
Prerequisites: Calculus, some undergraduate exposure to ODEs, linear algebra, and basic probability.
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16:848:507
Physics of Living Matter (3)
Review of physical phenomena that determine the properties of biological molecules, molecular assemblies, and fundamental biological processes. Also offered as 750:567.
Prerequisites: Linear algebra, differential equations, thermodynamics, and classical physics (at the junior level).
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16:848:511
Modeling of Biomolecular Networks: An Introduction to Systems Biology (3)
Focuses on a systems approach to biomolecular processes including the ideas, mathematical language, and modeling techniques used to describe the main mechanisms of transferring and processing biological information.
Sengupta. Prerequisites: Differential equations, linear algebra, probability and statistics; good chemistry/biology background at the high school level.
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16:848:513
Molecular Simulations in Computational Biology (3)
Focuses on molecular modeling and simulations of biological macromolecules including proteins and nucleic acids, molecular dynamics and Monte Carlo methods, and solvation. Computer simulations and exercises are an integral part of the course. Also offered as 750:563.
Levy, Olson. Prerequisites: Advanced undergraduate courses in physical chemistry or physics.
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16:848:515
Statistical Methods in Bioinformatics (3)
Broadly applicable, modern statistical tools particularly important in modeling and interpreting noisy bioinformatics data.
Prerequisites: Linear algebra and calculus.
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16:848:601
Protein Physics (3)
Advanced introduction to protein folding, binding, and structure prediction including equilibrium and kinetic aspects of protein folding and binding, classification of protein folds, and structure prediction from sequence.
Levy. Prerequisite: Permission of instructor.
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16:848:611
(Su) Intensive Summer Course (1)
Dai
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16:848:612
(Su) Intensive Summer Course (2)
Dai
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16:848:613
Selected Math Topics in Physiology and Medicine (3)
Mathematical modeling of selected biological phenomena and systems. Cellular homeostasis, regulation of cell function, cardiac rhythmicity, and hormone physiology are potential topics.
Sontag. Prerequisite: Elementary differential equations or permission of instructor.
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16:848:614
Interdisciplinary Quantitative Biology Boot Camp (N0)
An immersive two-week winter program that provides broad
introductory exposure to the language and experimental/theoretical
underpinnings of molecular biology, macromolecular
biochemistry/biophysics, structural biology, computational biology,
systems biology, and bioinformatics. Instruction takes the form of
lectures on fundamental aspects of biology, a broad range of hands-on
wet- and dry-laboratory practical exercises (including simulations of
biological phenomena using statistical physics, mathematical modeling,
and computational chemistry), tours of some of Rutgers' state-of-the-art
facilities for interrogating biological phenomena, and a culminating
symposium for which the participants gather their data (akin to a
scavenger hunt), teach each other about their findings, and prepare a
collaborative presentation. Additional description can be found on the website.
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16:848:615
Interdisciplinary Quantitative Biology Boot Camp (N2)
This course is an immersive two-week winter program that provides broad introductory exposure to the language and experimental/theoretical underpinnings of molecular biology, macromolecular biochemistry/biophysics, structural biology, computational biology, systems biology, and bioinformatics. Instruction takes the form of lectures on fundamental aspects of biology, a broad range of hands-on wet- and dry-laboratory practical exercises (including simulations of biological phenomena using statistical physics, mathematical modeling, and computational chemistry), tours of some of Rutgers' state-of-the-art facilities for interrogating biological phenomena, and a culminating symposium for which the participants gather their data (akin to a scavenger hunt), teach each other about their findings, and prepare a collaborative presentation. Additional description can be found on the website.
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16:848:616
Seminar in Quantitative Biology (BA)
Prerequisite: Permission of instructor.
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16:848:617
Special Topics in Quantitative Biology (BA)
Prerequisite: Permission of instructor.
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16:848:621,622
Laboratory Rotation in Computational Biology and Molecular Biophysics (1-2 BA,1-2 BA)
Introduction to the techniques of BioMaPS research through participation in research projects of selected members of the graduate faculty.
Enrollment restricted to Ph.D. students in the graduate program in quantitative biomedicine. No more than a total of 3 credits of laboratory rotation can be earned.
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16:848:701,702
Research in Quantitative Biomedicine (BA,BA)
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