Courses

  • ENG BE 991: PhD Dissertation
    Undergraduate Prerequisites: Graduate standing.
    Graduate Prerequisites: BE 900; restricted to post-prospectus PhD students.
    Participation in a research project under the direction of a faculty advisor leading to the preparation and defense of an original PhD dissertation.
  • ENG BF 527: Appl Bioinfmtcs
    Undergraduate Prerequisites: See course description
    This course description is currently under construction.
  • ENG BF 541: Bioinformatics Internship
    Internships provide the bridge between classroom/laboratory study and ?real-world? employment. Each student must complete an internship with a minimum of 400 hours of on-the-job experience (e.g., 10 weeks full-time work in the summer). The format is very flexible, and part-time internships running concurrently with classes or employment are acceptable. Students must consult with their academic advisor to assess the suitability of a proposed internship.
  • ENG BF 571: Dynamics and Evolution of Biological Networks
    Graduate Prerequisites: CAS MA 226 and CAS MA 242; EK102 can be used in lieu of the MA242 pre-req. Familiarity with differential equations and linear algebra at equivalent levels and the consent of instructor can be used in lieu of both pre-reqs.
    The course focuses on mathematical models for exploring the organization, dynamics, and evolution of biochemical and genetic networks. Topics include: introductions to metabolic and genetic networks, deterministic and stochastic kinetics of biochemical pathways; genome-scale models of metabolic reaction fluxes; models of regulatory networks; modular architecture of biological networks.
  • ENG BF 690: Bioinformatics Challenge Project
    Project course for first year Bioinformatics graduate students. Open-ended problems will involve bioinformatics as a key element, typically requiring the use of large data sets and computational analysis to make predictions about molecular function, molecular interactions, regulation, etc. Projects will be proposed by the Bioinformatics program faculty and selected by student in teams of three. The end result will be a set of predictions, some of which can be validated retrospectively using data available through online sources and some of which will require experimental validation. During the last 2 months of the academic year, teams will design feasible validation experiments in consultation with the experimental faculty.
  • ENG BF 752: LAW&Eth Bio Sci
    This course description is currently under construction.
  • ENG BF 768: Biological Database Analysis
    Describes relational data models and database management systems. Teaches the theories and techniques of constructing relational databases with emphasis on those aspects needed for various biological data. Introduces the relational database query language SQL. Describes methods for ensuring data consistency and data retrieval efficiency. Object-oriented programming is introduced primarily as an implementation aid for constructing, loading, and accessing databases. Utilizes web-based programming tools to implement user access to databases. Emphasis will be on solving problems associated with large and complex data sets. Course includes a final project implementing a database using real data from a local biology/medical school lab.
  • ENG BF 778: Physical Chemistry for Systems Biology
    This course introduces students to quantitative modeling in bioinformatics and systems biology. We begin with basic principles of statistical thermodynamics, chemical kinetics, with selected applications in biomolecular systems. Next we describe molecular driving forces in biology, and computation with biomolecular structures. Finally we discuss quantitative models of biomolecular networks, and design principles of biological circuits.
  • ENG BF 810: Phd Lab Rotat'N
    This course description is currently under construction.
  • ENG BF 821: Bioinfo Gradsem
    This course description is currently under construction.
  • ENG EC 311: Introduction to Logic Design
    Introduction to hardware building blocks used in digital computers. Boolean algebra, combinatorial and sequential circuits: analysis and design. Adders, multipliers, decoders, encoders, multiplexors. Programmable logic devices: read-only memory, programmable arrays, Verilog. Counters and registers. Includes lab. 4 cr,
  • ENG EC 327: Introduction to Software Engineering
    Undergraduate Prerequisites: ENG EK 125 or ENG EK 127 or ENG EK 128
    This course aims to introduce students to software design, programming techniques, data structures, and software engineering principles. The course is structured bottom up, beginning with basic hardware followed by an understanding of machine language that controls the hardware and the assembly language that organizes that control. It then proceeds through fundamental elements of functional programming languages, using C as the case example, and continues with the principles of object-oriented programming, as principally embodied in C++ but also its daughter languages Java, C#, and objective C. The course will conclude with an introduction to elementary data structures and algorithmic analysis. Throughout, the course develops core competencies in software engineering, including programming style, optimization, debugging, compilation, and program management, utilizing a variety of Integrated Development Environments and operating systems. 4 cr.
  • ENG EC 330: Applied Algorithms for Engineers
    Undergraduate Prerequisites: ENG EC 327; Recommended: CAS MA 193
    Introduction to the general concept of algorithms. Efficiency and run-time of algorithms. Graph algorithms, priority queues, search trees. Various approaches to design of algorithms and data structures, together with their applications to numerical and non-numerical problems. 4 cr.
  • ENG EC 381: Probability Theory in Electrical and Computer Engineering
    Undergraduate Prerequisites: CAS MA 225.
    Introduction to modeling uncertainty in electrical and computer systems. Experiments, models, and probabilities. Discrete and continuous random variables. Reliability models for circuits. Probability distributions. Moments and expectations. Random vectors. Functions of random variables. Sums of random variables and limit theorems. Signal detection and estimation. Basic stochastic processes. Discrete-time Markov chains. State-diagrams. Applications to statistical modeling and interpretation of experimental data in computer, communication, and optical systems. 4cr,
  • ENG EC 401: Signals and Systems
    Undergraduate Prerequisites: CAS MA 226 and ENG EK 307.
    Cannot be taken for credit in addition to ENG BE 401. Continuous-time and discrete-time signals and systems. Convolution sum, convolution integral. Linearity, time-invariance, causality, and stability of systems. Frequency domain analysis of signals and systems. Filtering, sampling, and modulation. Laplace transform, z-transform, pole-zero plots. Linear feedback systems. Includes lab. 4 cr.
  • ENG EC 402: Control Systems
    Undergraduate Prerequisites: CAS MA 226 ; ENG EK 307 ; ENG EC 401.
    Analysis of linear feedback systems, their characteristics, performance, and stability. The Routh-Hurwitz, root-locus, Bode, and Nyquist techniques. Design and compensation of feedback control systems. 4 cr.
  • ENG EC 410: Introduction to Electronics
    Undergraduate Prerequisites: ENG EK 307.
    Principles of diode, BJT, and MOSFET circuits. Graphical and analytical means of analysis. Piecewise linear modeling; amplifiers; digital inverters and logic gates. Biasing and small-signal analysis, microelectronic design techniques. Time-domain and frequency domain analysis and design. Includes lab. 4 cr.
  • ENG EC 412: Analog Electronics
    Undergraduate Prerequisites: ENG EC 410.
    Continuation of ENG EC 410. Topics include detailed analysis of differential amplifiers, design and principles of operational amplifier including multistage circuit structure, BJT, MOSFET, CMOS, and BiCMOS design principles, active filters and oscillators, negative and positive feedback, and power devices. Includes lab. 4 cr
  • ENG EC 413: Computer Organization
    Undergraduate Prerequisites: ENG EC 311.
    Introduction to the fundamentals and design of computer systems. Topics covered include computer instruction sets, assembly language programming, arithmetic circuits, CPU design (data path and control, pipelining), performance evaluation, memory devices, memory systems including caching and virtual memory, and I/O. Project using design automation tools. Includes lab. 4 cr.
  • ENG EC 415: Communication Systems
    Undergraduate Prerequisites: ENG EC 401; equivalent
    Signal analysis and transmission: amplitude modulation, angle modulation, pulse-amplitude and pulse-code modulation; amplitude shift-keying, frequency shift-keying, phase-shift keying. Case studies of practical communication systems. Includes lab. 4 cr.