• ENG BE 568: Systems Biology of Human Disease
    This course will train students to apply or develop computational network, modeling, and machine learning concepts to probe into the systems biology of disease. The aim of this course is to cover general concepts in biological computing that provide the foundation of thinking computationally about anomalous behavior in biological systems that cause diseases. The course also aims to teach students to work in teams and develop the skills to plan and coordinate a scientific project. The course will cover computational frameworks, such as biological networks (including metabolic, regulatory, and signal transduction networks), micro array analysis, proteomic analysis, next generation sequencing, imaging, machine learning, probabilistic inference, genetics, pathway analysis, network and graph theory, and other technologies to medical diseases initially focusing on clincal problems such as cancer, diabetes, inflammation, and aging. The course is aimed at seniors and graduate students in biomedical engineering or bioinformatics; however, students from other disciplines ranging from medicine to physics or computer science can attend the class with some prerequisites. 4 cr.
  • ENG BE 569: Next Generation Sequencing
    Undergraduate Prerequisites: ENG BE 200, ENG BE 401 or permission of instructor.
    The advent of high throughput sequencing is virtually changing biology and medicine. The technology enables us to catalog the entire functional parts list of living organisms from bacteria to human, develop and validate regulatory networks for controlling gene expression in systems biology models and develop novel biomarkers for personalized medicine that guide pharmacological treatments. In this course we will review the foundations of the field, starting from the biophysical foundations of current or emerging single molecule DNA sequencing techniques, through an introduction to the analytical tools to model and analyze NGS Data, and finally discussing clinical applications such as predicting drug response focusing on cancer. The course will involve bi-weekly homework assignments that include theoretical analysis and modeling, working with multiple analysis tools for NGS data including assembly, re-sequencing, alignments, RNA-seq, ChIP-seq, DNA methylation, mutation analysis and detection, copy number variation detection, and their applications to cancer. 4 cr
  • ENG BE 570: Introduction to Computational Vision
    Undergraduate Prerequisites: Working knowledge of the material covered in ENG BE 401 or EC 401, ENG BE 200 and working knowledge of MATLAB.
    Introductory course in biological visual neuroscience and computational vision. Provides a survey of the psychophysical, neuroanatomical and neurophysiological substrates of visual mechanisms underlying perception of visual motion, depth, objects, and space and of decision making mechanisms. Discussion of theoretical, explanatory, paradigms for these visual mechanisms. Topics addressed include psychophysics, methods from single cell recording physiology and low field potentials (LFP),multimodal imaging and computational modeling of various visual tasks and their modulation by attention. We will briefly address learning mechanisms and their relationship to brain plasticity. A term project is required for graduate credit. 4 cr.
  • ENG BE 571: Introduction to Neuroengineering
    This course covers current and future neurotechnologies for analyzing the brain and for treating neurological and psychiatric diseases. It focuses on the biophysical, biochemical, anatomical principles governing the design of the current neurotechnologies, with a goal of encouraging innovations of new generation of therapies. Topics include basic microscopic and macroscopic architecture of the brain, the fundamental properties of individual neurons and ensemble neural networks, electrophysiology, DBS, TMS, various imaging methods, optical neural control technologies, optogenetics, neuropharmacology, and gene/stem-cell therapies. Discussions of related literatures and design projects will be involved. Enrollment is limited to 30 students. The course is open to MS, MEng, and PhD students, as well as qualified undergraduate seniors. This course meets with BE 771. 4 cr.
  • ENG BE 592: Biomed Elective
  • ENG BE 593: ENG Elective
  • ENG BE 594: Prof Elective
  • ENG BE 601: Linear Algebra
    The first of four math modules designed to reinforce basic mathematical and computer programming concepts pertinent to graduate research in biomedical engineering. This course will emphasize the five cornerstones of applied linear algebra: Linear combinations, decompositions, orthogonality, metric, and linear transformations. Topics include LU and QR factorizations, finite difference methods for solving partial differential equations (PDEs), least squares, Fourier series and wavelets, solid mechanics, Markov chains, principal component analysis, and signal processing techniques. This course will provide the necessary linear algebra background needed to solve problems in BE 602, 603 and 604. 2 cr.
  • ENG BE 602: Ord Diff Eqtns
    This math module will focus on four key ODE concepts: Linear dynamical systems, nonlinear conservative and excitable systems, discrete- time state machines, and generalized Fourier series solutions to Sturm- Liouville problems. Topics include: Filters, enzymatic networks, mechanical models for biomaterials, oscillators and limit cycles, phase- locked loops, nonlinear Leslie matrices, Legendre polynomials, Bessel functions, and a prelude to solving PDE problems associated with heat transfer, diffusion, and electrostatics. Prior exposure to linear algebra (BE 601 equivalent), and working knowledge of a programming language (Matlab, Python, etc.) is helpful. 2 cr.
  • ENG BE 603: Partial Diff Eq
    This math module will focus on elliptical and parabolic PDEs associated with transport phenomenon problems in biomedical engineering. We will visit four PDE concepts: Separation of variables, integral transform solutions, superposition principles, and numerical approximations using finite-difference schemes. Topics include: 2D and 3D anisotropic Laplace's, Poisson's, and the heat equations in different coordinate systems, Fourier and Laplace transform solutions, 2D ADI methods, Green's functions, and the method of images. Prior exposure to linear algebra (BE 601 equivalent), ODEs (BE 602 or MA 226 equivalent), Fourier series, Fourier and Laplace transforms (BE 401 equivalent), and working knowledge of a programming language (Matlab, Python, etc.) is highly recommended. 2 cr.
  • ENG BE 604: Stat & Num Meth
    In the final math module, we will focus on how linear algebra, ODEs, statistics, and signals & systems techniques can be used to interrogate data from biological and engineering experiments. The lecture topics include: Jacobi, Gauss-Seidel, and SOR iterative solvers for large linear systems; Gauss-Newton iterations (nonlinear least-squares); the ANOVA table, multi- factor regression, and intro to the general linear model (GLM); data deconvolution; Monte Carlo, bootstrap, and kernel density estimation. Prior exposure to linear algebra (BE 601 equivalent), basic probability and statistics (BE 200 equivalent), and working knowledge of a programming language (Matlab, Python, etc.) is highly recommended. 2 cr.
  • ENG BE 605: Molecular Bioengineering
    Undergraduate Prerequisites: Required for biomedical engineering graduate students.
    Provides engineering perspectives on the building blocks of living cells and materials for biotechnology. Focuses on origins and synthesis in life and the laboratory, including biological pathways for synthesis of DNA, RNA and proteins; transduction, transmission, storage and retrieval of biological information by macromolecules; polymerase chain reaction, restriction enzymes, DNA sequencing; energetics of protein folding and trafficking; mechanisms of enzymatic catalysts and receptor-ligand binding; cooperative proteins, multi- protein complexes and control of metabolic pathways; generation, storage, transmission and release of biomolecular energy; and methods for study and manipulation of molecules which will include isolation, purification, detection, chemical characterization, imaging and visualization of structure. 4 cr
  • ENG BE 606: Quantitative Physiology for Engineers
    Undergraduate Prerequisites: Required for biomedical engineering graduate students.
    Course in human physiology for biomedical engineering students. Fundamentals of cellular and systems physiology, including the nervous , muscular, cardiovascular, respiratory, renal, gastrointestinal, endocrine and immune systems. Quantitative and engineering approaches will be applied to understanding physiological concepts. 4 cr
  • ENG BE 694: Biomedical and Clinical Needs Finding
    This course requires students to directly observe clinical procedures in selected medical specialties in appropriate hospital settings. Students will document biomedical technologies associated with the current standard of care, evaluate clinical needs and identify opportunities for developing new biomedical technologies. This course compliments and requires co-registration in BE695: Advanced Biomedical Design and Development. Fall only. 1cr.
  • ENG BE 695: Advanced Biomedical Design and Development
    This two-semester 8-credit course is a required sequence for students enrolled in the BME Master of Engineering program. Students will work with leading clinicians to observe and identify unmet clinical challenges, design and develop innovative engineering solutions to those challenges, and explore the regulatory, intellectual property, and reimbursement pathways that will ultimately advance the standard of patient care through the deployment of their innovations. During the first semester, students will qualify for Medical Observer Status and the Boston Medical Center and project teams will conduct formal Needs Finding protocols, select projects, and design alternative solutions. During the second semester, project teams will develop their designs, and make multiple prototypes. Formal Design Control, Life Cycle, Risk Analysis, Project Management, and Intellectual Property Strategies will be introduced. Using formal Product Develop Protocols, students will prepare a detailed regulatory and implementation pathway analysis for completing the commercialization process needed to eventually bring their innovations into clinical practice. 8 credits over 2 semesters - must enroll for both semesters
  • ENG BE 696: Advanced Deployment of Biomedical Innovations
    This three-credit course is complementary to BE 695 Advanced Biomedical Design and Development and provides an opportunity for QST Health Sector Management graduate students to work directly with graduate engineering students to develop technical, economic, and commercial implementation plans for medical technologies developed in BE 695. The course has limited enrollment and is restricted to SMG Health Sector MBA students. There are no prerequisites. Permission of instructor is required.
  • ENG BE 700: Advanced Topics in Biomedical Engineering
    Undergraduate Prerequisites: Graduate standing or consent of instructor.
    Advanced study of a specific research topic in biomedical engineering. Intended primarily for advanced graduate students. Variable cr.
  • ENG BE 703: Numerical Methods and Modeling in Biomedical Engineering
    Undergraduate Prerequisites: Graduate standing.
    This course offers an advanced introduction to numerical methods for solving linear and nonlinear differential equations including ordinary differential equations and partial differential equations. Topics include numerical series, error analysis, interpolation, numerical integration and differentiation, Euler & Runge-Kutta methods, finite difference methods, finite element methods, and moving boundary problems. This course requires knowledge of multivariable calculus, linear algebra, and differential equations. Some knowledge in one computer programming language, such as MATLAB, is required. 4.0 cr
  • ENG BE 710: Neural Plasticity and Perceptual Learning
    Undergraduate Prerequisites: ENG BE 200 (or an introductory course in probability and statistics);GRS BI 755 (or any other introductory course in neuroscience). Recommended: ENG BE 570
    This course explores the capacity of cortical sensory and motor maps in the adult brain to change as a result of alterations in the effectiveness of the input, direct damage, or practice. The lectures will describe and discuss (1) the physiology and anatomy underlying adult dynamics; (2) psychophysical methods and experimental paradigms that have been used to study cortical plasticity in the early stages of the sensory and motor pathways; (3) evidence for perceptual learning; and (4) biologically plausible computational models of learning. We will discuss applications of functional neuroimaging to study perceptual learning and restorative plasticity in the human brain. 4 cr
  • ENG BE 716: Quantitative Medical Imaging: Theory and Methods
    The theory of quantitative medical imaging is studied systematically using the pixel value equation as the unifying mathematical concept. The physics foundations of electromagnetism, quantum mechanics, and NMR dynamics are studied at an intermediate level thus providing a solid foundation for the development of quantitative techniques as applicable to x-ray CT and MRI.