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LSA Course Guide Search Results: UG, GR, Fall 2007, Dept = ENGR
 
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Title
Section
Instructor
Term
Credits
Requirements
ENGR 100 — Intro Engineering
Section 500, LEC
Biotechnology and Human Values

Instructor: Schmedlen,Rachael Hope
Instructor: Adam,Miriam E

FA 2007
Credits: 4

Biotechnology combines the engineering principles of analysis, design, and optimization with the tools of cellular and molecular biology. It impacts nearly every aspect of our daily lives, from the food we eat to the medicine we take. The primary purpose of this course is to teach a basic vocabulary in biotechnology and expose students to the breadth of biotechnology and its impact on our daily lives. Topics will cover a broad range of applications in genetics, molecular diagnostics, molecular imaging, and clinical devices. A key additional component will be to investigate human values issues, such as ethical questions and cost effectiveness, arising from these technologies. Teamwork in the lab and through an independent project is emphasized. Report writing and presentations are required throughout the term, culminating with a final report and public presentation.

Welcome! This course brings together students in the life sciences and engineering to explore basic issues facing biotechnologists. In addition to introducing basic sciences, this course will explore some of the dominant trends in biotechnology, not only in terms of their scientific and technological impact, but also in terms of their implications for human values. Our objective is to provide you with the real life challenge of designing a solution for a client and allow you to experience the complex dynamics that govern the design process in the interdisciplinary field of Biotechnology.

The Lab
Unique to this course are two hands-on labs: DNA analysis and molecular imaging. These labs will allow you to assess the efficacy and feasibility of existing technologies, as well as explore their suitability for a spectrum of social, political, and economic realities.

The Project
As another unique opportunity of this course, you will conduct an investigative study for a real client, the University of Michigan School of Medicine. Your project will consist of designing a test capable of detecting hereditary disease before the onset of symptoms. You will be assigned to a project team, which, in turn, will be assigned to a client physician. Your team will collaborate with the physician to determine how the prognosis of a target disease could benefit from genetic testing. This will require research into the genetics of the target disease, the disease process, treatments, and evaluation of the potential impact of early detection for the individual patient, health care management, and society at large. Given the needs of the patient and physicians, you will draw on your research and lab experiences to determine the most useful and appropriate methods for pre-symptom testing. This will require a quantitative, as well as qualitative, evaluation of your proposed technology and its effect on disease outcome, health care delivery, and patient quality of life.

Course Organization and Resources
This course is conducted by a multi-disciplinary team of instructors led by Professor Matthew O'Donnell. Your time in the classroom will be divided into biweekly lectures, a weekly lab and a weekly discussion section. In addition, each team will meet periodically with instructors in scheduled workshops held during evening hours. Deliverables will consist of technical assignments, lab reports, oral presentations, and a final formal oral presentation and report for our clients and other interested parties.

In this course, we rely heavily on independent study, instructor-student interaction, and on-line resources. Topics addressed include microbiology, gene sequencing and expression, testing technology, statistics, ethics, legal issues, team management, technical communications, problem-solving strategies, and the design process. We conduct on-line discussions and provide a wealth of resources via our course website.

This course is highly challenging and demanding, and our expectations are high. However, students who take the challenge seriously have the opportunity to experience that sense of achievement that comes from meeting and even exceeding their own expectations. For students interested in pursuing a degree in cellular and molecular biology, biotechnology, or biomedical engineering, this course is a must. Join us. We look forward to another high-powered semester.

Advisory Prerequisite: ENGIN

ENGR 371 — Numerical Methods for Engineers and Scientists
Section 001, LEC

FA 2007
Credits: 3

Credit Exclusions: No credit granted to those who have completed or are enrolled in MATH 471 or 472.

Background and Goals: This is a survey course of the basic numerical methods which are used to solve practical scientific problems. Important concepts such as accuracy, stability, and efficiency are discussed. The course provides an introduction to MATLAB, an interactive program for numerical linear algebra, and may provide practice in FORTRAN programming and the use of a software library subroutine. Convergence theorems are discussed and applied, but the proofs are not emphasized.

Content: Floating point arithmetic, Gaussian elimination, polynomial interpolation, spline approximations, numerical integration and differentiation, solutions to non-linear equations, ordinary differential equations, polynomial approximations. Other topics may include discrete Fourier transforms, two-point boundary-value problems, and Monte-Carlo methods.

Alternatives: Alternatives: Math 471 (Numerical Analysis) provides a more in-depth study of the same topics, with a greater emphasis on analyzing the accuracy and stability of the numerical methods. Math 571 (Numerical Linear Algebra) is a detailed study of the solution of systems of linear equations and eigenvalue problems, with some emphasis on large-scale problems. Math 572 (Numerical Methods for Differential Equations) covers numerical methods for both ordinary and partial differential equations. (Math 571 and 572 can be taken in either order).

Subsequent Courses: This course is basic for many later courses in science and engineering. It is good background for 571 — 572.

Advisory Prerequisite: ENGR 101; one of MATH 216, 256, 286, or 316, and one of MATH 215, 217, 417, or 419.

ENGR 371 — Numerical Methods for Engineers and Scientists
Section 002, LEC

FA 2007
Credits: 3

Credit Exclusions: No credit granted to those who have completed or are enrolled in MATH 471 or 472.

Background and Goals: This is a survey course of the basic numerical methods which are used to solve practical scientific problems. Important concepts such as accuracy, stability, and efficiency are discussed. The course provides an introduction to MATLAB, an interactive program for numerical linear algebra, and may provide practice in FORTRAN programming and the use of a software library subroutine. Convergence theorems are discussed and applied, but the proofs are not emphasized.

Content: Floating point arithmetic, Gaussian elimination, polynomial interpolation, spline approximations, numerical integration and differentiation, solutions to non-linear equations, ordinary differential equations, polynomial approximations. Other topics may include discrete Fourier transforms, two-point boundary-value problems, and Monte-Carlo methods.

Alternatives: Alternatives: Math 471 (Numerical Analysis) provides a more in-depth study of the same topics, with a greater emphasis on analyzing the accuracy and stability of the numerical methods. Math 571 (Numerical Linear Algebra) is a detailed study of the solution of systems of linear equations and eigenvalue problems, with some emphasis on large-scale problems. Math 572 (Numerical Methods for Differential Equations) covers numerical methods for both ordinary and partial differential equations. (Math 571 and 572 can be taken in either order).

Subsequent Courses: This course is basic for many later courses in science and engineering. It is good background for 571 — 572.

Advisory Prerequisite: ENGR 101; one of MATH 216, 256, 286, or 316, and one of MATH 215, 217, 417, or 419.

 
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